Just Accepted
Artificial Intelligence of Things: A Survey
Abstract
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we provide a systematic and comprehensive review of AIoT research. We examine AIoT literature related to sensing, computing, and networking & communication, which form the three key components of AIoT. In addition to advancements in these areas, we review domain-specific AIoT systems that are designed for various important application domains. We have also created an accompanying GitHub repository, where we compile the papers included in this survey: https://github.com/AIoT-MLSys-Lab/AIoT-Survey. This repository will be actively maintained and updated with new research as it becomes available. As both IoT and AI become increasingly critical to our society, we believe AIoT is emerging as an essential research field at the intersection of IoT and modern AI. We hope this survey will serve as a valuable resource for those engaged in AIoT research and act as a catalyst for future explorations to bridge gaps and drive advancements in this exciting field.
References
[1]
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016. Deep learning with differential privacy. In Proceedings of the 2016 ACM SIGSAC conference on computer and communications security.
[2]
Daniel A Adler, Dror Ben-Zeev, Vincent WS Tseng, John M Kane, Rachel Brian, Andrew T Campbell, Marta Hauser, Emily A Scherer, and Tanzeem Choudhury. 2020. Predicting early warning signs of psychotic relapse from passive sensing data: an approach using encoder-decoder neural networks. JMIR mHealth and uHealth 8, 8 (2020).
[3]
Neil Agarwal and Ravi Netravali. 2023. Boggart: Towards General-Purpose Acceleration of Retrospective Video Analytics. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23). Boston, MA.
[4]
Fawad Ahmad, Hang Qiu, Ray Eells, Fan Bai, and Ramesh Govindan. 2020. CarMap: Fast 3d feature map updates for automobiles. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20).
[5]
Ali Akbari and Roozbeh Jafari. 2019. Transferring activity recognition models for new wearable sensors with deep generative domain adaptation. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks.
[6]
Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang. 2022. Fedrolex: Model-heterogeneous federated learning with rolling sub-model extraction. Advances in Neural Information Processing Systems 35 (2022).
[7]
Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S Narayanan, Salman Avestimehr, et al. 2023. FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things. arXiv preprint arXiv:2310.00109(2023).
[8]
Kittipat Apicharttrisorn, Jiasi Chen, Vyas Sekar, Anthony Rowe, and Srikanth Krishnamurthy. 2022. Breaking Edge Shackles: Infrastructure-Free Collaborative Mobile Augmented Reality. In Proceedings of the Twentieth ACM Conference on Embedded Networked Sensor Systems. Boston Massachusetts.
[9]
Kittipat Apicharttrisorn, Xukan Ran, Jiasi Chen, Srikanth Krishnamurthy, and Amit Roy-Chowdhury. 2019. Frugal following: power thrifty object detection and tracking for mobile augmented reality. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems. New York New York.
[10]
Roshan Ayyalasomayajula, Aditya Arun, Chenfeng Wu, Sanatan Sharma, Abhishek Sethi, Deepak Vasisht, and Dinesh Bharadia. 2020. Deep learning based wireless localization for indoor navigation. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[11]
Andrew Bae and Susu Xu. 2023. Discovering and Understanding Algorithmic Biases in Autonomous Pedestrian Trajectory Predictions(SenSys ’22). Association for Computing Machinery, New York, NY, USA.
[12]
Arjun Balasingam, Karthik Gopalakrishnan, Radhika Mittal, Venkat Arun, Ahmed Saeed, Mohammad Alizadeh, Hamsa Balakrishnan, and Hari Balakrishnan. 2021. Throughput-fairness tradeoffs in mobility platforms(MobiSys ’21). Association for Computing Machinery, New York, NY, USA.
[13]
Kshitiz Bansal, Keshav Rungta, Siyuan Zhu, and Dinesh Bharadia. 2020. Pointillism: accurate 3D bounding box estimation with multi-radars. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems. Virtual Event Japan.
[14]
Soroush Bateni and Cong Liu. 2020. {NeuOS}: A {Latency-Predictable}{Multi-Dimensional} Optimization Framework for {DNN-driven} Autonomous Systems. In 2020 USENIX Annual Technical Conference (USENIX ATC 20).
[15]
Ali Ali Ben, Marziye Kouroshli, Sofiya Semenova, Zakieh Hashemifar, Steven Ko, and Karthik Dantu. 2022. Edge-SLAM: Edge-assisted visual simultaneous localization and mapping. ACM Transactions on Embedded Computing Systems 22, 1 (2022).
[16]
Daniel J Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Javier Fernandez-Marques, Yan Gao, Lorenzo Sani, Kwing Hei Li, Titouan Parcollet, Pedro Porto Buarque de Gusmão, et al. 2020. Flower: A friendly federated learning research framework. arXiv preprint arXiv:2007.14390(2020).
[17]
Romil Bhardwaj, Zhengxu Xia, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Nikolaos Karianakis, Kevin Hsieh, Paramvir Bahl, and Ion Stoica. 2022. Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). Renton, WA.
[18]
Carlos Bocanegra, Mohammad Khojastepour, Mustafa Arslan, Eugene Chai, Sampath Rangarajan, and Kaushik Chowdhury. 2020. RFGo: a seamless self-checkout system for apparel stores using RFID. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[19]
Tara Boroushaki, Isaac Perper, Mergen Nachin, Alberto Rodriguez, and Fadel Adib. 2021. Rfusion: Robotic grasping via rf-visual sensing and learning. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[20]
Rabaï Bouderhem. 2024. Shaping the future of AI in healthcare through ethics and governance. Humanit. Soc. Sci. Commun. 11, 416 (March 2024).
[21]
Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Haotian Tang, Hanrui Wang, Ligeng Zhu, and Song Han. 2022. Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications. ACM Transactions on Design Automation of Electronic Systems 27, 3(May 2022).
[22]
Sebastian Caldas, Jakub Konečny, H Brendan McMahan, and Ameet Talwalkar. 2018. Expanding the reach of federated learning by reducing client resource requirements. arXiv preprint arXiv:1812.07210(2018).
[23]
Christopher Canel, Thomas Kim, Giulio Zhou, Conglong Li, Hyeontaek Lim, David Andersen, Michael Kaminsky, and Subramanya Dulloor. 2019. Scaling Video Analytics on Constrained Edge Nodes. 1905.13536 [cs.CV]
[24]
Frank Cangialosi, Neil Agarwal, Venkat Arun, Srinivas Narayana, Anand Sarwate, and Ravi Netravali. 2022. Privid: Practical, Privacy-Preserving Video Analytics Queries. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). Renton, WA.
[25]
Jiani Cao, Chengdong Lin, Yang Liu, and Zhenjiang Li. 2023. Gaze Tracking on Any Surface with Your Phone. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (Boston, Massachusetts) (SenSys ’22). New York, NY, USA.
[26]
Qingqing Cao, Noah Weber, Niranjan Balasubramanian, and Aruna Balasubramanian. 2019. Deqa: On-device question answering. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services.
[27]
Yetong Cao, Huijie Chen, Fan Li, and Yu Wang. 2021. Crisp-BP: Continuous wrist PPG-based blood pressure measurement. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[28]
Justin Chan, Nada Ali, Ali Najafi, Anna Meehan, Lisa R Mancl, Emily Gallagher, Randall Bly, and Shyamnath Gollakota. 2022. An off-the-shelf otoacoustic-emission probe for hearing screening via a smartphone. Nature biomedical engineering 6, 11 (2022).
[29]
Justin Chan, Antonio Glenn, Malek Itani, Lisa R Mancl, Emily Gallagher, Randall Bly, Shwetak Patel, and Shyamnath Gollakota. 2023. Wireless earbuds for low-cost hearing screening. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[30]
Zhuoqing Chang, Shubo Liu, Xingxing Xiong, Zhaohui Cai, and Guoqing Tu. 2021. A Survey of Recent Advances in Edge-Computing-Powered Artificial Intelligence of Things. IEEE Internet of Things Journal 8, 18 (September 2021).
[31]
Ishan Chatterjee, Maruchi Kim, Vivek Jayaram, Shyamnath Gollakota, Ira Kemelmacher, Shwetak Patel, and Steven Seitz. 2022. ClearBuds: wireless binaural earbuds for learning-based speech enhancement. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[32]
Baicheng Chen, Huining Li, Zhengxiong Li, Xingyu Chen, Chenhan Xu, and Wenyao Xu. 2020. ThermoWave: a new paradigm of wireless passive temperature monitoring via mmWave sensing. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[33]
Chen Chen, Ke Sun, and Xinyu Zhang. 2021. ExGSense: Toward Facial Gesture Sensing with a Sparse Near-Eye Sensor Array. In Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021). Nashville TN USA.
[34]
Mingshi Chen, Panlong Yang, Jie Xiong, Maotian Zhang, Youngki Lee, Chaocan Xiang, and Chang Tian. 2019. Your Table Can Be an Input Panel: Acoustic-based Device-Free Interaction Recognition. 3, 1, Article 3 (mar 2019).
[35]
Ruirong Chen, Kai Huang, and Wei Gao. 2022. AiFi: AI-Enabled WiFi Interference Cancellation with Commodity PHY-Layer Information. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[36]
Wei Chen and Zhiyuan Li. 2024. Octopus v3: Technical Report for On-device Sub-billion Multimodal AI Agent. arXiv preprint arXiv:2404.11459(2024).
[37]
Zhe Chen, Tianyue Zheng, Chao Cai, and Jun Luo. 2021. MoVi-Fi: Motion-robust vital signs waveform recovery via deep interpreted RF sensing. In Proceedings of the 27th annual international conference on mobile computing and networking.
[38]
Guoxuan Chi, Zheng Yang, Chenshu Wu, Jingao Xu, Yuchong Gao, Yunhao Liu, and Tony Xiao Han. 2024. RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion. In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking.
[39]
Hao-Jen Chien, Hossein Khalili, Amin Hass, and Nader Sehatbakhsh. 2023. Enc2: Privacy-Preserving Inference for Tiny IoTs via Encoding and Encryption. In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking(Madrid, Spain) (ACM MobiCom ’23). Association for Computing Machinery, New York, NY, USA, Article 35.
[40]
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, and Dimitrios Dimitriadis. 2022. Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. International Joint Conference on Artificial Intelligence (IJCAI) (2022).
[41]
Matthew Corbett, Brendan David-John, Jiacheng Shang, Y. Charlie Hu, and Bo Ji. 2023. BystandAR: Protecting Bystander Visual Data in Augmented Reality Systems. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (Helsinki, Finland) (MobiSys ’23). Association for Computing Machinery, New York, NY, USA.
[42]
Justin Cosentino, Anastasiya Belyaeva, Xin Liu, Nicholas A. Furlotte, Zhun Yang, Chace Lee, Erik Schenck, Yojan Patel, Jian Cui, Logan Douglas Schneider, Robby Bryant, Ryan G. Gomes, Allen Jiang, Roy Lee, Yun Liu, Javier Perez, Jameson K. Rogers, Cathy Speed, Shyam Tailor, Megan Walker, Jeffrey Yu, Tim Althoff, Conor Heneghan, John Hernandez, Mark Malhotra, Leor Stern, Yossi Matias, Greg S. Corrado, Shwetak Patel, Shravya Shetty, Jiening Zhan, Shruthi Prabhakara, Daniel McDuff, and Cory Y. McLean. 2024. Towards a Personal Health Large Language Model. arXiv (June 2024). 2406.06474
[43]
Kaiyan Cui, Yanwen Wang, Yuanqing Zheng, and Jinsong Han. 2021. ShakeReader: ‘Read’ UHF RFID using Smartphone. In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications.
[44]
Yimin Dai, Xian Shuai, Rui Tan, and Guoliang Xing. 2023. Interpersonal distance tracking with mmWave radar and IMUs. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[45]
Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S Dhillon, and Ufuk Topcu. 2022. Faster non-convex federated learning via global and local momentum. In Uncertainty in Artificial Intelligence. PMLR.
[46]
Mallesham Dasari, Kumara Kahatapitiya, Samir Das, Aruna Balasubramanian, and Dimitris Samaras. 2022. Swift: Adaptive Video Streaming with Layered Neural Codecs. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). Renton, WA.
[47]
Yongheng Deng, Weining Chen, Ju Ren, Feng Lyu, Yang Liu, Yunxin Liu, and Yaoxue Zhang. 2022. TailorFL: Dual-Personalized Federated Learning under System and Data Heterogeneity. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[48]
Enmao Diao, Jie Ding, and Vahid Tarokh. 2020. Heterofl: Computation and communication efficient federated learning for heterogeneous clients. arXiv preprint arXiv:2010.01264(2020).
[49]
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Diaz, Andre Manoel, and Robert Sim. 2022. FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations. ArXiv abs/2203.13789(2022).
[50]
Shuya Ding, Zhe Chen, Tianyue Zheng, and Jun Luo. 2020. RF-net: A unified meta-learning framework for RF-enabled one-shot human activity recognition. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[51]
Gaofeng Dong, Jason Wu, Julian De Gortari Briseno, Akash Deep Singh, Justin Feng, Ankur Sarker, Nader Sehatbakhsh, and Mani Srivastava. 2024. RefreshChannels: Exploiting Dynamic Refresh Rate Switching for Mobile Device Attacks. In Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services (Minato-ku, Tokyo, Japan) (MOBISYS ’24). Association for Computing Machinery, New York, NY, USA.
[52]
Jialuo Du, Yidong Ren, Zhui Zhu, Chenning Li, Zhichao Cao, Qiang Ma, and Yunhao Liu. 2023. SRLoRa: Neural-enhanced LoRa Weak Signal Decoding with Multi-gateway Super Resolution. In Proceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing.
[53]
Kuntai Du, Qizheng Zhang, Anton Arapin, Haodong Wang, Zhengxu Xia, and Junchen Jiang. 2022. AccMPEG: Optimizing Video Encoding for Video Analytics. arXiv (April 2022). 2204.12534
[54]
Zachary Englhardt, Chengqian Ma, Margaret E. Morris, Chun-Cheng Chang, Xuhai ”Orson” Xu, Lianhui Qin, Daniel McDuff, Xin Liu, Shwetak Patel, and Vikram Iyer. 2024. From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8, 2, Article 56 (may 2024).
[55]
European Parliament and Council. 2016. Regulation (EU) 2016/679 of the European Parliament and of the Council. https://eur-lex.europa.eu/eli/reg/2016/679/oj.
[56]
Biyi Fang, Jillian Co, and Mi Zhang. 2017. Deepasl: Enabling ubiquitous and non-intrusive word and sentence-level sign language translation. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems.
[57]
Biyi Fang, Xiao Zeng, Faen Zhang, Hui Xu, and Mi Zhang. 2020. Flexdnn: Input-adaptive on-device deep learning for efficient mobile vision. In 2020 IEEE/ACM Symposium on Edge Computing (SEC). IEEE.
[58]
Biyi Fang, Xiao Zeng, and Mi Zhang. 2018. Nestdnn: Resource-aware multi-tenant on-device deep learning for continuous mobile vision. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking.
[59]
Habiba Farrukh, Reham Aburas, Siyuan Cao, and He Wang. 2020. FaceRevelio: a face liveness detection system for smartphones with a single front camera. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[60]
Boyuan Feng, Yuke Wang, Gushu Li, Yuan Xie, and Yufei Ding. 2021. Palleon: A runtime system for efficient video processing toward dynamic class skew. In 2021 USENIX Annual Technical Conference (USENIX ATC 21).
[61]
Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, and Shrikanth Narayanan. 2023. FedMultimodal: A Benchmark For Multimodal Federated Learning. 2306.09486 [cs.DC] https://arxiv.org/abs/2306.09486
[62]
Yuda Feng, Yaxiong Xie, Deepak Ganesan, and Jie Xiong. 2021. Lte-based pervasive sensing across indoor and outdoor. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[63]
Yuda Feng, Yaxiong Xie, Deepak Ganesan, and Jie Xiong. 2022. Lte-based low-cost and low-power soil moisture sensing. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[64]
Andrea Ferlini, Dong Ma, Robert Harle, and Cecilia Mascolo. 2021. EarGate: gait-based user identification with in-ear microphones. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[65]
Yongjian Fu, Shuning Wang, Linghui Zhong, Lili Chen, Ju Ren, and Yaoxue Zhang. 2022. SVoice: Enabling Voice Communication in Silence via Acoustic Sensing on Commodity Devices. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[66]
Ziyan Fu, Ju Ren, Yunxin Liu, Ting Cao, Deyu Zhang, Yuezhi Zhou, and Yaoxue Zhang. 2022. Hyperion: A Generic and Distributed Mobile Offloading Framework on OpenCL. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[67]
Nakul Garg, Yang Bai, and Nirupam Roy. 2021. Owlet: Enabling spatial information in ubiquitous acoustic devices. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services.
[68]
Nakul Garg and Nirupam Roy. 2023. Sirius: A self-localization system for resource-constrained iot sensors. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[69]
Petko Georgiev, Sourav Bhattacharya, Nicholas Lane, and Cecilia Mascolo. 2017. Low-resource multi-task audio sensing for mobile and embedded devices via shared deep neural network representations. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017).
[70]
Petko Georgiev, Nicholas Lane, Kiran Rachuri, and Cecilia Mascolo. 2016. LEO: Scheduling sensor inference algorithms across heterogeneous mobile processors and network resources. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking.
[71]
Seyed Keyarash Ghiasi, Vivian Dsouza, Koen Langendoen, and Marco Zuniga. 2023. SpectraLux: Towards Exploiting the Full Spectrum with Passive VLC. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[72]
Tripat Gill. 2021. Ethical dilemmas are really important to potential adopters of autonomous vehicles. Ethics Inf. Technol. 23, 4 (Dec. 2021).
[73]
In Gim and JeongGil Ko. 2022. Memory-efficient DNN training on mobile devices. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[74]
Graham Gobieski, Brandon Lucia, and Nathan Beckmann. 2019. Intelligence beyond the edge: Inference on intermittent embedded systems. In Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems.
[75]
Yongjie Guan, Xueyu Hou, Nan Wu, Bo Han, and Tao Han. 2022. DeepMix: Mobility-aware, Lightweight, and Hybrid 3D Object Detection for Headsets. http://arxiv.org/abs/2201.08812 arXiv:2201.08812 [cs].
[76]
Yu Guan, Chengyuan Zheng, Xinggong Zhang, Zongming Guo, and Junchen Jiang. 2019. Pano: Optimizing 360° Video Streaming with a Better Understanding of Quality Perception. In Proceedings of the ACM Special Interest Group on Data Communication (Beijing, China) (SIGCOMM ’19). New York, NY, USA.
[77]
Peizhen Guo, Bo Hu, and Wenjun Hu. 2021. Mistify: Automating {DNN} Model Porting for {On-Device} Inference at the Edge. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21).
[78]
Peizhen Guo and Wenjun Hu. 2018. Potluck: Cross-application approximate deduplication for computation-intensive mobile applications. In Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems.
[79]
Unsoo Ha, Salah Assana, and Fadel Adib. 2020. Contactless seismocardiography via deep learning radars. In Proceedings of the 26th annual international conference on mobile computing and networking.
[80]
Unsoo Ha, Junshan Leng, Alaa Khaddaj, and Fadel Adib. 2020. Food and liquid sensing in practical environments using {RFIDs}. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20).
[81]
Mingcong Han, Hanze Zhang, Rong Chen, and Haibo Chen. 2022. Microsecond-scale preemption for concurrent {GPU-accelerated}{DNN} inferences. In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22).
[82]
Rui Han, Qinglong Zhang, Chi Liu, Guoren Wang, Jian Tang, and Lydia Chen. 2021. Legodnn: block-grained scaling of deep neural networks for mobile vision. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[83]
Seungyeop Han, Haichen Shen, Matthai Philipose, Sharad Agarwal, Alec Wolman, and Arvind Krishnamurthy. 2016. Mcdnn: An approximation-based execution framework for deep stream processing under resource constraints. In Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services.
[84]
Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Carl Yang, Han Xie, Lichao Sun, Lifang He, Liangwei Yang, Philip S Yu, Yu Rong, et al. 2021. Fedgraphnn: A federated learning system and benchmark for graph neural networks. arXiv preprint arXiv:2104.07145(2021).
[85]
Chaoyang He, Songze Li, Jinhyun So, Xiao Zeng, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, et al. 2020. Fedml: A research library and benchmark for federated machine learning. arXiv preprint arXiv:2007.13518(2020).
[86]
Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan1Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, and Salman Avestimehr. 2021. Fedcv: a federated learning framework for diverse computer vision tasks. arXiv preprint arXiv:2111.11066(2021).
[87]
Guorong He, Shaojie Chen, Dan Xu, Xiaojiang Chen, Yaxiong Xie, Xinhuai Wang, and Dingyi Fang. 2023. Fusang: Graph-inspired Robust and Accurate Object Recognition on Commodity mmWave Devices. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[88]
Lixing He, Haozheng Hou, Shuyao Shi, Xian Shuai, and Zhenyu Yan. 2023. Towards Bone-Conducted Vibration Speech Enhancement on Head-Mounted Wearables. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[89]
Shibo He, Kun Shi, Chen Liu, Bicheng Guo, Jiming Chen, and Zhiguo Shi. 2022. Collaborative Sensing in Internet of Things: A Comprehensive Survey. IEEE Communications Surveys & Tutorials 24, 3 (2022).
[90]
Yuze He, Li Ma, Jiahe Cui, Zhenyu Yan, Guoliang Xing, Sen Wang, Qintao Hu, and Chen Pan. 2022. AutoMatch: Leveraging Traffic Camera to Improve Perception and Localization of Autonomous Vehicles. In Proceedings of the Twentieth ACM Conference on Embedded Networked Sensor Systems. Boston Massachusetts.
[91]
Yuze He, Li Ma, Zhehao Jiang, Yi Tang, and Guoliang Xing. 2021. VI-eye: semantic-based 3D point cloud registration for infrastructure-assisted autonomous driving. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking. New Orleans Louisiana.
[92]
Samuel Horvath, Stefanos Laskaridis, Mario Almeida, Ilias Leontiadis, Stylianos Venieris, and Nicholas Lane. 2021. Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout. Advances in Neural Information Processing Systems 34 (2021).
[93]
Jiahui Hou, Xiang-Yang Li, Peide Zhu, Zefan Wang, Yu Wang, Jianwei Qian, and Panlong Yang. 2019. Signspeaker: A real-time, high-precision smartwatch-based sign language translator. In The 25th Annual International Conference on Mobile Computing and Networking.
[94]
Kun Mean Hou, Xunxing Diao, Hongling Shi, Hao Ding, Haiying Zhou, and Christophe de Vaulx. 2023. Trends and Challenges in AIoT/IIoT/IoT Implementation. Sensors 23, 11 (January 2023). Number: 11 Publisher: Multidisciplinary Digital Publishing Institute.
[95]
Xueyu Hou, Yongjie Guan, and Tao Han. 2022. NeuLens: spatial-based dynamic acceleration of convolutional neural networks on edge. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[96]
Pan Hu, Junha Im, Zain Asgar, and Sachin Katti. 2020. Starfish: Resilient image compression for AIoT cameras. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[97]
Zhizhang Hu, Yue Zhang, Tong Yu, and Shijia Pan. 2022. VMA: Domain Variance-and Modality-Aware Model Transfer for Fine-Grained Occupant Activity Recognition. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[98]
Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin Marlin, and Heesung Kwon. 2020. Clio: Enabling automatic compilation of deep learning pipelines across iot and cloud. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[99]
Kai Huang and Wei Gao. 2022. Real-time neural network inference on extremely weak devices: agile offloading with explainable AI. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[100]
Kai Huang, Boyuan Yang, and Wei Gao. 2023. ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[101]
Loc Huynh, Youngki Lee, and Rajesh Balan. 2017. Deepmon: Mobile gpu-based deep learning framework for continuous vision applications. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services.
[102]
Sinh Huynh, Rajesh Balan, JeongGil Ko, and Youngki Lee. 2019. VitaMon: measuring heart rate variability using smartphone front camera. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems.
[103]
Jinwoo Hwang, Minsu Kim, Daeun Kim, Seungho Nam, Yoonsung Kim, Dohee Kim, Hardik Sharma, and Jongse Park. 2022. CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics. In 2022 USENIX Annual Technical Conference (USENIX ATC 22). Carlsbad, CA.
[104]
Joo Jeong, Jingyu Lee, Donghyun Kim, Changmin Jeon, Changjin Jeong, Youngki Lee, and Byung-Gon Chun. 2022. Band: coordinated multi-dnn inference on heterogeneous mobile processors. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[105]
Jeya Jeyakumar, Liangzhen Lai, Naveen Suda, and Mani Srivastava. 2019. SenseHAR: a robust virtual activity sensor for smartphones and wearables. In SenSys ’19: Proceedings of the 17th Conference on Embedded Networked Sensor Systems. New York, NY, USA.
[106]
Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, and Yonina C Eldar. 2021. Adaptive quantization of model updates for communication-efficient federated learning. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.
[107]
Sijie Ji, Yaxiong Xie, and Mo Li. 2022. SiFall: Practical Online Fall Detection with RF Sensing. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[108]
Fucheng Jia, Deyu Zhang, Ting Cao, Shiqi Jiang, Yunxin Liu, Ju Ren, and Yaoxue Zhang. 2022. Codl: efficient cpu-gpu co-execution for deep learning inference on mobile devices. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services. Association for Computing Machinery New York, NY, USA.
[109]
Angela Jiang, Daniel Wong, Christopher Canel, Lilia Tang, Ishan Misra, Michael Kaminsky, Michael Kozuch, Padmanabhan Pillai, David Andersen, and Gregory Ganger. 2018. Mainstream: Dynamic Stem-Sharing for Multi-Tenant Video Processing. In 2018 USENIX Annual Technical Conference (USENIX ATC 18).
[110]
Junchen Jiang, Ganesh Ananthanarayanan, Peter Bodik, Siddhartha Sen, and Ion Stoica. 2018. Chameleon: Scalable Adaptation of Video Analytics. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (Budapest, Hungary) (SIGCOMM ’18). New York, NY, USA.
[111]
Linshan Jiang, Qun Song, Rui Tan, and Mo Li. 2022. PriMask: Cascadable and Collusion-Resilient Data Masking for Mobile Cloud Inference. In Proceedings of the Twentieth ACM Conference on Embedded Networked Sensor Systems. http://arxiv.org/abs/2211.06716 arXiv:2211.06716 [cs].
[112]
Shiqi Jiang, Zhiqi Lin, Yuanchun Li, Yuanchao Shu, and Yunxin Liu. 2021. Flexible high-resolution object detection on edge devices with tunable latency. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[113]
Wenjun Jiang, Chenglin Miao, Fenglong Ma, Shuochao Yao, Yaqing Wang, Ye Yuan, Hongfei Xue, Chen Song, Xin Ma, Dimitrios Koutsonikolas, et al. 2018. Towards environment independent device free human activity recognition. In Proceedings of the 24th annual international conference on mobile computing and networking.
[114]
Wenjun Jiang, Hongfei Xue, Chenglin Miao, Shiyang Wang, Sen Lin, Chong Tian, Srinivasan Murali, Haochen Hu, Zhi Sun, and Lu Su. 2020. Towards 3D human pose construction using WiFi. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[115]
Zhehao Jiang, Neiwen Ling, Xuan Huang, Shuyao Shi, Chenhao Wu, Xiaoguang Zhao, Zhenyu Yan, and Guoliang Xing. 2023. CoEdge: A Cooperative Edge System for Distributed Real-Time Deep Learning Tasks. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[116]
Yincheng Jin, Yang Gao, Xiaotao Guo, Jun Wen, Zhengxiong Li, and Zhanpeng Jin. 2022. EarHealth: an earphone-based acoustic otoscope for detection of multiple ear diseases in daily life. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[117]
Peter Kairouz, H Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al. 2021. Advances and open problems in federated learning. Foundations and trends® in machine learning 14, 1–2(2021).
[118]
Yiping Kang, Johann Hauswald, Cao Gao, Austin Rovinski, Trevor Mudge, Jason Mars, and Lingjia Tang. 2017. Neurosurgeon: Collaborative intelligence between the cloud and mobile edge. ACM SIGARCH Computer Architecture News 45, 1 (2017).
[119]
Momin Ahmad Khan, Virat Shejwalkar, Amir Houmansadr, and Fatima M. Anwar. 2023. Security Analysis of SplitFed Learning(SenSys ’22). Association for Computing Machinery, New York, NY, USA.
[120]
Mehrdad Khani, Ganesh Ananthanarayanan, Kevin Hsieh, Junchen Jiang, Ravi Netravali, Yuanchao Shu, Mohammad Alizadeh, and Victor Bahl. 2023. RECL: Responsive Resource-Efficient Continuous Learning for Video Analytics. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23). Boston, MA.
[121]
Jaehong Kim, Youngmok Jung, Hyunho Yeo, Juncheol Ye, and Dongsu Han. 2020. Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication (Virtual Event, USA) (SIGCOMM ’20). New York, NY, USA.
[122]
Youngsok Kim, Joonsung Kim, Dongju Chae, Daehyun Kim, and Jangwoo Kim. 2019. μlayer: Low latency on-device inference using cooperative single-layer acceleration and processor-friendly quantization. In Proceedings of the Fourteenth EuroSys Conference 2019.
[123]
Hao Kong, Xiangyu Xu, Jiadi Yu, Qilin Chen, Chenguang Ma, Yingying Chen, Yi-Chao Chen, and Linghe Kong. 2022. m3track: mmwave-based multi-user 3d posture tracking. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[124]
Rui Kong, Yuanchun Li, Yizhen Yuan, and Linghe Kong. 2023. ConvReLU++: Reference-based Lossless Acceleration of Conv-ReLU Operations on Mobile CPU. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[125]
Belal Korany, Chitra Karanam, Hong Cai, and Yasamin Mostofi. 2019. XModal-ID: Using WiFi for through-wall person identification from candidate video footage. In The 25th Annual International Conference on Mobile Computing and Networking.
[126]
Young Kwon, Jagmohan Chauhan, and Cecilia Mascolo. 2022. Yono: Modeling multiple heterogeneous neural networks on microcontrollers. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[127]
Fan Lai, Yinwei Dai, Sanjay Singapuram, Jiachen Liu, Xiangfeng Zhu, Harsha Madhyastha, and Mosharaf Chowdhury. 2022. Fedscale: Benchmarking model and system performance of federated learning at scale. In International Conference on Machine Learning. PMLR.
[128]
Fan Lai, Xiangfeng Zhu, Harsha Madhyastha, and Mosharaf Chowdhury. 2021. Oort: Efficient federated learning via guided participant selection. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21).
[129]
Guohao Lan, Bailey Heit, Tim Scargill, and Maria Gorlatova. 2020. GazeGraph: Graph-based few-shot cognitive context sensing from human visual behavior. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[130]
Nicholas Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, and Fahim Kawsar. 2016. Deepx: A software accelerator for low-power deep learning inference on mobile devices. In 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[131]
Nicholas Lane, Petko Georgiev, and Lorena Qendro. 2015. Deepear: robust smartphone audio sensing in unconstrained acoustic environments using deep learning. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing.
[132]
Stefanos Laskaridis, Stylianos Venieris, Mario Almeida, Ilias Leontiadis, and Nicholas Lane. 2020. SPINN: synergistic progressive inference of neural networks over device and cloud. In Proceedings of the 26th annual international conference on mobile computing and networking.
[133]
Jinsung Lee, Sungyong Lee, Jongyun Lee, Sandesh Sathyanarayana, Hyoyoung Lim, Jihoon Lee, Xiaoqing Zhu, Sangeeta Ramakrishnan, Dirk Grunwald, Kyunghan Lee, et al. 2020. PERCEIVE: deep learning-based cellular uplink prediction using real-time scheduling patterns. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services.
[134]
Royson Lee, Stylianos Venieris, Lukasz Dudziak, Sourav Bhattacharya, and Nicholas Lane. 2019. Mobisr: Efficient on-device super-resolution through heterogeneous mobile processors. In The 25th annual international conference on mobile computing and networking.
[135]
Seulki Lee. 2023. MicroDeblur: Image Motion Deblurring on Microcontroller-based Vision Systems. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[136]
Seulki Lee and Shahriar Nirjon. 2020. Fast and scalable in-memory deep multitask learning via neural weight virtualization. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services.
[137]
Clayton Leite and Yu Xiao. 2021. Optimal sensor channel selection for resource-efficient deep activity recognition. In Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021).
[138]
Ang Li, Jingwei Sun, Xiao Zeng, Mi Zhang, Hai Li, and Yiran Chen. 2021. Fedmask: Joint computation and communication-efficient personalized federated learning via heterogeneous masking. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[139]
Chenning Li, Hanqing Guo, Shuai Tong, Xiao Zeng, Zhichao Cao, Mi Zhang, Qiben Yan, Li Xiao, Jiliang Wang, and Yunhao Liu. 2021. NELoRa: Towards ultra-low SNR LoRa communication with neural-enhanced demodulation. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[140]
Chenning Li, Zheng Liu, Yuguang Yao, Zhichao Cao, Mi Zhang, and Yunhao Liu. 2020. Wi-fi see it all: generative adversarial network-augmented versatile wi-fi imaging. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[141]
Chenning Li, Yidong Ren, Shuai Tong, Shakhrul Iman Siam, Mi Zhang, Jiliang Wang, Yunhao Liu, and Zhichao Cao. 2024. ChirpTransformer: Versatile LoRa Encoding for Low-power Wide-area IoT. In Proceedings of ACM MobiSys.
[142]
Changming Li, Mingjing Xu, Yicong Du, Limin Liu, Cong Shi, Yan Wang, Hongbo Liu, and Yingying Chen. 2024. Practical Adversarial Attack on WiFi Sensing Through Unnoticeable Communication Packet Perturbation(ACM MobiCom ’24). Association for Computing Machinery, New York, NY, USA.
[143]
Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao. 2022. PyramidFL: A fine-grained client selection framework for efficient federated learning. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[144]
Dong Li, Shirui Cao, Sunghoon Ivan Lee, and Jie Xiong. 2022. Experience: practical problems for acoustic sensing. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[145]
Dong Li, Jialin Liu, Sunghoon Ivan Lee, and Jie Xiong. 2020. FM-track: pushing the limits of contactless multi-target tracking using acoustic signals. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[146]
Daliang Li and Junpu Wang. 2019. Fedmd: Heterogenous federated learning via model distillation. arXiv preprint arXiv:1910.03581(2019).
[147]
Hongyu Li, Hairong Wang, Luyang Liu, and Marco Gruteser. 2018. Automatic Unusual Driving Event Identification for Dependable Self-Driving. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. Shenzhen China.
[148]
Kehan Li, Jiming Chen, Baosheng Yu, Zhangchong Shen, Chao Li, and Shibo He. 2020. Supreme: Fine-grained radio map reconstruction via spatial-temporal fusion network. In 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[149]
Tianxing Li, Jin Huang, Erik Risinger, and Deepak Ganesan. 2021. Low-latency speculative inference on distributed multi-modal data streams. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services.
[150]
Xinyu Li, Yanyi Zhang, Ivan Marsic, Aleksandra Sarcevic, and Randall Burd. 2016. Deep learning for rfid-based activity recognition. In Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM.
[151]
Yuanqi Li, Arthi Padmanabhan, Pengzhan Zhao, Yufei Wang, Guoqing Xu, and Ravi Netravali. 2020. Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication (Virtual Event, USA) (SIGCOMM ’20). New York, NY, USA.
[152]
Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, and Salman Avestimehr. 2021. Fednlp: A research platform for federated learning in natural language processing. arXiv preprint arXiv:2104.08815(2021).
[153]
Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, and Song Han. 2021. Mcunetv2: Memory-efficient patch-based inference for tiny deep learning. arXiv preprint arXiv:2110.15352(2021).
[154]
Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, and Song Han. 2022. On-device training under 256kb memory. Advances in Neural Information Processing Systems 35 (2022).
[155]
Shih-Chieh Lin, Yunqi Zhang, Chang-Hong Hsu, Matt Skach, Md Haque, Lingjia Tang, and Jason Mars. 2018. The Architectural Implications of Autonomous Driving: Constraints and Acceleration. In Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems. Williamsburg VA USA.
[156]
Tao Lin, Lingjing Kong, Sebastian U Stich, and Martin Jaggi. 2020. Ensemble distillation for robust model fusion in federated learning. Advances in neural information processing systems 33 (2020).
[157]
Neiwen Ling, Xuan Huang, Zhihe Zhao, Nan Guan, Zhenyu Yan, and Guoliang Xing. 2022. BlastNet: Exploiting Duo-Blocks for Cross-Processor Real-Time DNN Inference. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[158]
Neiwen Ling, Kai Wang, Yuze He, Guoliang Xing, and Daqi Xie. 2021. Rt-mdl: Supporting real-time mixed deep learning tasks on edge platforms. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[159]
Mieszko Lis, Maximilian Golub, and Guy Lemieux. 2019. Full deep neural network training on a pruned weight budget. Proceedings of Machine Learning and Systems 1 (2019).
[160]
Cihang Liu, Lan Zhang, Zongqian Liu, Kebin Liu, Xiangyang Li, and Yunhao Liu. 2016. Lasagna: towards deep hierarchical understanding and searching over mobile sensing data. In MobiCom ’16: Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking. New York, NY, USA.
[161]
Hansi Liu, Abrar Alali, Mohamed Ibrahim, Bryan Cao, Nicholas Meegan, Hongyu Li, Marco Gruteser, Shubham Jain, Kristin Dana, Ashwin Ashok, et al. 2022. Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[162]
Jianwei Liu, Wenfan Song, Leming Shen, Jinsong Han, Xian Xu, and Kui Ren. 2021. MandiPass: Secure and Usable User Authentication via Earphone IMU. In 2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS).
[163]
Jiesong Liu, Feng Zhang, Jiawei Guan, Hsin-Hsuan Sung, Xiaoguang Guo, Xiaoyong Du, and Xipeng Shen. 2023. Space-Efficient TREC for Enabling Deep Learning on Microcontrollers. In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3.
[164]
Luyang Liu, Hongyu Li, and Marco Gruteser. 2019. Edge Assisted Real-time Object Detection for Mobile Augmented Reality. In The 25th Annual International Conference on Mobile Computing and Networking. Los Cabos Mexico.
[165]
Luyang Liu, Hongyu Li, Jian Liu, Cagdas Karatas, Yan Wang, Marco Gruteser, Yingying Chen, and Richard Martin. 2017. BigRoad: Scaling Road Data Acquisition for Dependable Self-Driving. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services. Niagara Falls New York USA.
[166]
Li Liu, Yuguang Yao, Zhichao Cao, and Mi Zhang. 2021. DeepLoRa: Learning accurate path loss model for long distance links in LPWAN. In INFOCOM.
[167]
Miaomiao Liu, Sikai Yang, Wyssanie Chomsin, and Wan Du. 2022. Real-Time Tracking of Smartwatch Orientation and Location by Multitask Learning. In SenSys ’22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems. New York, NY, USA.
[168]
Sicong Liu, Bin Guo, Cheng Fang, Ziqi Wang, Shiyan Luo, Zimu Zhou, and Zhiwen Yu. 2023. Enabling Resource-Efficient AIoT System With Cross-Level Optimization: A Survey. IEEE Communications Surveys & Tutorials(2023).
[169]
Tiantian Liu, Ming Gao, Feng Lin, Chao Wang, Zhongjie Ba, Jinsong Han, Wenyao Xu, and Kui Ren. 2021. Wavoice: A noise-resistant multi-modal speech recognition system fusing mmwave and audio signals. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[170]
Xiulong Liu, Dongdong Liu, Jiuwu Zhang, Tao Gu, and Keqiu Li. 2021. RFID and camera fusion for recognition of human-object interactions. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[171]
Yang Liu, Zhenjiang Li, Zhidan Liu, and Kaishun Wu. 2019. Real-time Arm Skeleton Tracking and Gesture Inference Tolerant to Missing Wearable Sensors. In MobiSys ’19: Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services. New York, NY, USA.
[172]
Yan Liu, Anlan Yu, Leye Wang, Bin Guo, Yang Li, Enze Yi, and Daqing Zhang. 2024. UniFi: A Unified Framework for Generalizable Gesture Recognition with Wi-Fi Signals Using Consistency-guided Multi-View Networks. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, 4 (2024).
[173]
Zida Liu, Guohao Lan, Jovan Stojkovic, Yunfan Zhang, Carlee Joe-Wong, and Maria Gorlatova. 2020. CollabAR: Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality. In 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). Sydney, NSW, Australia.
[174]
Zihan Liu, Jingwen Leng, Zhihui Zhang, Quan Chen, Chao Li, and Minyi Guo. 2022. VELTAIR: towards high-performance multi-tenant deep learning services via adaptive compilation and scheduling. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems.
[175]
Zikun Liu, Gagandeep Singh, Chenren Xu, and Deepak Vasisht. 2021. FIRE: enabling reciprocity for FDD MIMO systems. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[176]
Ziwei Liu, Tianyue Zheng, Chao Hu, Yanbing Yang, Yimao Sun, Yi Zhang, Zhe Chen, Liangyin Chen, and Jun Luo. 2022. CORE-lens: Simultaneous communication and object recognition with disentangled-GAN cameras. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[177]
Chris Lu, Muhamad Saputra, Peijun Zhao, Yasin Almalioglu, Gusmao Pedro De, Changhao Chen, Ke Sun, Niki Trigoni, and Andrew Markham. 2020. milliEgo: single-chip mmWave radar aided egomotion estimation via deep sensor fusion. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[178]
Chris Xiaoxuan Lu, Stefano Rosa, Peijun Zhao, Bing Wang, Changhao Chen, John A Stankovic, Niki Trigoni, and Andrew Markham. 2020. See through smoke: robust indoor mapping with low-cost mmwave radar. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services.
[179]
Yan Lu, Shiqi Jiang, Ting Cao, and Yuanchao Shu. 2023. Turbo: Opportunistic Enhancement for Edge Video Analytics. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (Boston, Massachusetts) (SenSys ’22). New York, NY, USA.
[180]
Wenjie Luo, Qun Song, Zhenyu Yan, Rui Tan, and Guosheng Lin. 2022. Indoor Smartphone SLAM with Learned Echoic Location Features. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[181]
Zhiqing Luo, Wei Wang, Jun Qu, Tao Jiang, and Qian Zhang. 2018. ShieldScatter: Improving IoT Security with Backscatter Assistance(SenSys ’18). Association for Computing Machinery, New York, NY, USA.
[182]
Qianpiao Ma, Yang Xu, Hongli Xu, Zhida Jiang, Liusheng Huang, and He Huang. 2021. FedSA: A semi-asynchronous federated learning mechanism in heterogeneous edge computing. IEEE Journal on Selected Areas in Communications 39, 12(2021).
[183]
Ajay Mahimkar, Ashiwan Sivakumar, Zihui Ge, Shomik Pathak, and Karunasish Biswas. 2021. Auric: using data-driven recommendation to automatically generate cellular configuration. In Proceedings of the 2021 ACM SIGCOMM 2021 Conference.
[184]
Hongzi Mao, Ravi Netravali, and Mohammad Alizadeh. 2017. Neural Adaptive Video Streaming with Pensieve. In Proceedings of the Conference of the ACM Special Interest Group on Data Communication (Los Angeles, CA, USA) (SIGCOMM ’17). New York, NY, USA.
[185]
Wenguang Mao, Wei Sun, Mei Wang, and Lili Qiu. 2020. DeepRange: Acoustic Ranging via Deep Learning. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 4, Article 143 (dec 2020).
[186]
Wenguang Mao, Mei Wang, Wei Sun, Lili Qiu, Swadhin Pradhan, and Yi-Chao Chen. 2019. Rnn-based room scale hand motion tracking. In The 25th Annual International Conference on Mobile Computing and Networking.
[187]
Akhil Mathur, Anton Isopoussu, Fahim Kawsar, Nadia Berthouze, and Nicholas Lane. 2019. Mic2mic: using cycle-consistent generative adversarial networks to overcome microphone variability in speech systems. In Proceedings of the 18th international conference on information processing in sensor networks.
[188]
Akhil Mathur, Nicholas Lane, Sourav Bhattacharya, Aidan Boran, Claudio Forlivesi, and Fahim Kawsar. 2017. Deepeye: Resource efficient local execution of multiple deep vision models using wearable commodity hardware. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services.
[189]
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Arcas. 2017. Communication-efficient learning of deep networks from decentralized data. In Artificial intelligence and statistics. PMLR.
[190]
Yaxin Mei, Wenhua Wang, Yuzhu Liang, Qin Liu, Shuhong Chen, and Tian Wang. 2023. Privacy-Enhanced Cooperative Storage Scheme for Contact-Free Sensory Data in AIoT with Efficient Synchronization. ACM Trans. Sen. Netw. (sep 2023). Just Accepted.
[191]
Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei, Geza Kovacs, Javier Perez, Yun Liu, Erik Schenck, Nova Hammerquist, Jake Sunshine, Shyam Tailor, Kumar Ayush, Hao-Wei Su, Qian He, Cory Y. McLean, Mark Malhotra, Shwetak Patel, Jiening Zhan, Tim Althoff, Daniel McDuff, and Xin Liu. 2024. Transforming Wearable Data into Health Insights using Large Language Model Agents. arXiv (June 2024). 2406.06464
[192]
Chulhong Min, Alessandro Montanari, Akhil Mathur, and Fahim Kawsar. 2019. A closer look at quality-aware runtime assessment of sensing models in multi-device environments. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems.
[193]
Niluthpol Mithun, Sirajum Munir, Karen Guo, and Charles Shelton. 2018. ODDS: real-time object detection using depth sensors on embedded GPUs. In 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[194]
Brent Mittelstadt. 2017. Ethics of the health-related internet of things: a narrative review. Ethics Inf. Technol. 19, 3 (Sept. 2017).
[195]
Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, and Nicolas Kourtellis. 2021. PPFL: privacy-preserving federated learning with trusted execution environments. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (Virtual Event, Wisconsin) (MobiSys ’21). Association for Computing Machinery, New York, NY, USA.
[196]
Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour, and Mohsen Guizani. 2018. Deep Learning for IoT Big Data and Streaming Analytics: A Survey. IEEE Communications Surveys & Tutorials 20, 4 (2018).
[197]
David C. Mohr, Mi Zhang, and Stephen Schueller. 2017. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology (ARCP) 13, 1 (2017). http://www.annualreviews.org/doi/pdf/10.1146/annurev-clinpsy-032816-044949
[198]
Mahathir Monjur, Yubo Luo, Zhenyu Wang, and Shahriar Nirjon. 2023. SoundSieve: Seconds-Long Audio Event Recognition on Intermittently-Powered Systems. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[199]
Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael Jordan, et al. 2018. Ray: A distributed framework for emerging {AI} applications. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18).
[200]
John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, and Dzmitry Huba. 2022. Federated learning with buffered asynchronous aggregation. In International Conference on Artificial Intelligence and Statistics. PMLR.
[201]
Viet Nguyen, Siddharth Rupavatharam, Luyang Liu, Richard Howard, and Marco Gruteser. 2019. HandSense: capacitive coupling-based dynamic, micro finger gesture recognition. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems. New York New York.
[202]
State of California. 2018. California Consumer Privacy Act of 2018. https://leginfo.legislature.ca.gov.
[203]
U.S. Department of Health and Human Services. 1996. Health Insurance Portability and Accountability Act of 1996. https://www.govinfo.gov/content/pkg/PLAW-104publ191/pdf/PLAW-104publ191.pdf.
[204]
Xiaomin Ouyang, Xian Shuai, Jiayu Zhou, Ivy Shi, Zhiyuan Xie, Guoliang Xing, and Jianwei Huang. 2022. Cosmo: contrastive fusion learning with small data for multimodal human activity recognition. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[205]
Xiaomin Ouyang and Mani Srivastava. 2024. LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces. 2403.19857 [cs.AI] https://arxiv.org/abs/2403.19857
[206]
Xiaomin Ouyang, Zhiyuan Xie, Jiayu Zhou, Jianwei Huang, and Guoliang Xing. 2021. Clusterfl: a similarity-aware federated learning system for human activity recognition. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services.
[207]
Arthi Padmanabhan, Neil Agarwal, Anand Iyer, Ganesh Ananthanarayanan, Yuanchao Shu, Nikolaos Karianakis, Guoqing Xu, and Ravi Netravali. 2023. Gemel: Model Merging for Memory-Efficient, Real-Time Video Analytics at the Edge. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23). Boston, MA.
[208]
Jongseok Park, Kyungmin Bin, and Kyunghan Lee. 2022. mGEMM: low-latency convolution with minimal memory overhead optimized for mobile devices. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[209]
JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, and JeongGil Ko. 2023. AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7, 3, Article 116 (sep 2023).
[210]
Keondo Park, You Choi, Inhoe Lee, and Hyung-Sin Kim. 2023. PointSplit: Towards On-device 3D Object Detection with Heterogeneous Low-power Accelerators. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[211]
Seonghoon Park, Yeonwoo Cho, Hyungchol Jun, Jeho Lee, and Hojung Cha. 2023. OmniLive: Super-Resolution Enhanced 360° Video Live Streaming for Mobile Devices. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (Helsinki, Finland) (MobiSys ’23). New York, NY, USA.
[212]
Sibendu Paul, Kunal Rao, Giuseppe Coviello, Murugan Sankaradas, Oliver Po, Y. Hu, and Srimat Chakradhar. 2023. Enhancing Video Analytics Accuracy via Real-Time Automated Camera Parameter Tuning. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (Boston, Massachusetts) (SenSys ’22). New York, NY, USA.
[213]
Jacopo Pegoraro, Jesus O Lacruz, Michele Rossi, and Joerg Widmer. 2022. SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[214]
Daniel F Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes, Thiemo Voigt, Dejan Kostić, and Magnus Boman. 2023. DeepGANTT: A Scalable Deep Learning Scheduler for Backscatter Networks. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[215]
Valentin Radu, Catherine Tong, Sourav Bhattacharya, Nicholas Lane, Cecilia Mascolo, Mahesh Marina, and Fahim Kawsar. 2018. Multimodal deep learning for activity and context recognition. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 1, 4 (2018).
[216]
Tauhidur Rahman, Alexander T Adams, Mi Zhang, Erin Cherry, Bobby Zhou, Huaishu Peng, and Tanzeem Choudhury. 2014. Bodybeat: A Mobile System for Sensing Non-Speech Body Sounds. In The 12th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).
[217]
Enrico Reggiani, Cristóbal Lazo, Roger Bagué, Adrián Cristal, Mauro Olivieri, and Osman Unsal. 2022. Bison-e: A lightweight and high-performance accelerator for narrow integer linear algebra computing on the edge. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems.
[218]
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, and Ramtin Pedarsani. 2020. Fedpaq: A communication-efficient federated learning method with periodic averaging and quantization. In International conference on artificial intelligence and statistics. PMLR.
[219]
Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, and Bo Yuan. 2017. Sc-dcnn: Highly-scalable deep convolutional neural network using stochastic computing. ACM SIGPLAN Notices 52, 4 (2017).
[220]
Yidong Ren, Li Liu, Chenning Li, Zhichao Cao, and Shigang Chen. 2022. Is lorawan really wide? fine-grained lora link-level measurement in an urban environment. In 2022 IEEE 30th International Conference on Network Protocols (ICNP). IEEE.
[221]
Michael Rudow, Francis Yan, Abhishek Kumar, Ganesh Ananthanarayanan, Martin Ellis, and K.V. Rashmi. 2023. Tambur: Efficient loss recovery for videoconferencing via streaming codes. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23). Boston, MA.
[222]
Sohrab Saeb, Mi Zhang, Christopher J Karr, Stephen M Schueller, Marya E Corden, Konrad P Kording, and David C Mohr. 2015. Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study. Journal of Medical Internet Research (JMIR) 17, 7 (2015).
[223]
Sriram Sami, Sean Tan, Bangjie Sun, and Jun Han. 2021. LAPD: Hidden Spy Camera Detection using Smartphone Time-of-Flight Sensors. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[224]
Sandeep Singh Sandha, Bharathan Balaji, Luis Garcia, and Mani Srivastava. 2023. Eagle: End-to-end Deep Reinforcement Learning based Autonomous Control of PTZ Cameras(IoTDI ’23). New York, NY, USA.
[225]
Shamik Sarkar, Milind Buddhikot, Aniqua Baset, and Sneha Kumar Kasera. 2021. DeepRadar: A deep-learning-based environmental sensing capability sensor design for CBRS. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[226]
Khotso Selialia, Yasra Chandio, and Fatima M. Anwar. 2023. Federated Learning Biases in Heterogeneous Edge-Devices: A Case-Study(SenSys ’22). Association for Computing Machinery, New York, NY, USA.
[227]
Hossein Shafagh, Anwar Hithnawi, Lukas Burkhalter, Pascal Fischli, and Simon Duquennoy. 2017. Secure sharing of partially homomorphic encrypted iot data. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems.
[228]
Hailan Shanbhag, Sohrab Madani, Akhil Isanaka, Deepak Nair, Saurabh Gupta, and Haitham Hassanieh. 2023. Contactless Material Identification with Millimeter Wave Vibrometry. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[229]
Zhihao Shen, Wan Du, Xi Zhao, and Jianhua Zou. 2020. DMM: Fast map matching for cellular data. In Proceedings of the 26th annual international conference on mobile computing and networking.
[230]
Junyang Shi, Mo Sha, and Xi Peng. 2021. Adapting wireless mesh network configuration from simulation to reality via deep learning based domain adaptation. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21).
[231]
Shuyao Shi, Jiahe Cui, Zhehao Jiang, Zhenyu Yan, Guoliang Xing, Jianwei Niu, and Zhenchao Ouyang. 2022. VIPS: real-time perception fusion for infrastructure-assisted autonomous driving. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking. Sydney NSW Australia.
[232]
Shaohuai Shi, Qiang Wang, Kaiyong Zhao, Zhenheng Tang, Yuxin Wang, Xiang Huang, and Xiaowen Chu. 2019. A distributed synchronous SGD algorithm with global top-k sparsification for low bandwidth networks. In 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). IEEE.
[233]
Yuanming Shi, Kai Yang, Tao Jiang, Jun Zhang, and Khaled B. Letaief. 2020. Communication-Efficient Edge AI: Algorithms and Systems. http://arxiv.org/abs/2002.09668 arXiv:2002.09668 [cs, eess, math].
[234]
Seungwoo Shim, Hyeonho Shin, Myeongkyun Cho, Youngki Lee, Jinwoo Shin, and Song Kim. 2023. Mosaic: Extremely Low-resolution RFID Vision for Visually-anonymized Action Recognition. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[235]
Jaemin Shin, Yuanchun Li, Yunxin Liu, and Sung-Ju Lee. 2022. FedBalancer: data and pace control for efficient federated learning on heterogeneous clients. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[236]
Xian Shuai, Yulin Shen, Siyang Jiang, Zhihe Zhao, Zhenyu Yan, and Guoliang Xing. 2022. BalanceFL: Addressing class imbalance in long-tail federated learning. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[237]
Akash Deep Singh, Luis Garcia, Joseph Noor, and Mani Srivastava. 2021. I Always Feel Like Somebody’s Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless Sensors. In 30th USENIX Security Symposium (USENIX Security 21). USENIX Association.
[238]
Ruiyuan Song, Dongheng Zhang, Zhi Wu, Cong Yu, Chunyang Xie, Shuai Yang, Yang Hu, and Yan Chen. 2022. Rf-url: unsupervised representation learning for rf sensing. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[239]
Xingzhe Song, Kai Huang, and Wei Gao. 2022. FaceListener: Recognizing Human Facial Expressions via Acoustic Sensing on Commodity Headphones. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[240]
Xingzhe Song, Boyuan Yang, Ge Yang, Ruirong Chen, Erick Forno, Wei Chen, and Wei Gao. 2020. SpiroSonic: monitoring human lung function via acoustic sensing on commodity smartphones. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[241]
Bangjie Sun, Sean Tan, Zhiwei Ren, Mun Chan, and Jun Han. 2022. Detecting counterfeit liquid food products in a sealed bottle using a smartphone camera. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[242]
Jingwei Sun, Ang Li, Lin Duan, Samiul Alam, Xuliang Deng, Xin Guo, Haiming Wang, Maria Gorlatova, Mi Zhang, Hai Li, et al. 2022. FedSEA: A Semi-Asynchronous Federated Learning Framework for Extremely Heterogeneous Devices. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[243]
Ke Sun and Xinyu Zhang. 2021. UltraSE: single-channel speech enhancement using ultrasound. In Proceedings of the 27th annual international conference on mobile computing and networking.
[244]
Ke Sun, Ting Zhao, Wei Wang, and Lei Xie. 2018. Vskin: Sensing touch gestures on surfaces of mobile devices using acoustic signals. In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking.
[245]
Rishub Tamirisa, John Won, Chengjun Lu, Ron Arel, and Andy Zhou. 2024. FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning. 2024 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2024).
[246]
Tianxiang Tan and Guohong Cao. 2021. Efficient execution of deep neural networks on mobile devices with npu. In Proceedings of the 20th International Conference on Information Processing in Sensor Networks (Co-Located with CPS-IoT Week 2021).
[247]
Linpeng Tang, Qi Huang, Amit Puntambekar, Ymir Vigfusson, Wyatt Lloyd, and Kai Li. 2017. Popularity Prediction of Facebook Videos for Higher Quality Streaming. In 2017 USENIX Annual Technical Conference (USENIX ATC 17). Santa Clara, CA.
[248]
Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, et al. 2022. FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. arXiv preprint arXiv:2210.04620(2022).
[249]
Panrong Tong, Mingqian Li, Mo Li, Jianqiang Huang, and Xiansheng Hua. 2021. Large-scale vehicle trajectory reconstruction with camera sensing network. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking. New Orleans Louisiana.
[250]
Vu Tran, Gihan Jayatilaka, Ashwin Ashok, and Archan Misra. 2021. Deeplight: Robust & unobtrusive real-time screen-camera communication for real-world displays. In Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021).
[251]
Marco Trinelli, Massimo Gallo, Myriana Rifai, and Fabio Pianese. 2019. Transparent AR Processing Acceleration at the Edge. In Proceedings of the 2nd International Workshop on Edge Systems, Analytics and Networking. Dresden Germany.
[252]
Linlin Tu, Xiaomin Ouyang, Jiayu Zhou, Yuze He, and Guoliang Xing. 2021. Feddl: Federated learning via dynamic layer sharing for human activity recognition. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[253]
Saeed Vahidian, Mahdi Morafah, and Bill Lin. 2021. Personalized federated learning by structured and unstructured pruning under data heterogeneity. In 2021 IEEE 41st international conference on distributed computing systems workshops (ICDCSW). IEEE.
[254]
Zhongwei Wan, Che Liu, Xin Wang, Chaofan Tao, Hui Shen, Zhenwu Peng, Jie Fu, Rossella Arcucci, Huaxiu Yao, and Mi Zhang. 2024. MEIT: Multi-Modal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation. arXiv (March 2024). 2403.04945
[255]
Chia-Cheng Wang, Jyh-Cheng Chen, Yi Chen, Rui-Heng Tu, Jia-Jiun Lee, Yu-Xin Xiao, and Shan-Yu Cai. 2021. MVP: magnetic vehicular positioning system for GNSS-denied environments. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking. New Orleans Louisiana.
[256]
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, and Wennan Zhu. 2021. A Field Guide to Federated Optimization. 2107.06917 [cs.LG]
[257]
Junyang Wang, Haiyang Xu, Jiabo Ye, Ming Yan, Weizhou Shen, Ji Zhang, Fei Huang, and Jitao Sang. 2024. Mobile-Agent: Autonomous multi-modal mobile device agent with visual perception. arXiv preprint arXiv:2401.16158(2024).
[258]
Kailong Wang, Cong Shi, Jerry Cheng, Yan Wang, Minge Xie, and Yingying Chen. 2022. Solving the WiFi Sensing Dilemma in Reality Leveraging Conformal Prediction. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[259]
Manni Wang, Shaohua Ding, Ting Cao, Yunxin Liu, and Fengyuan Xu. 2021. Asymo: scalable and efficient deep-learning inference on asymmetric mobile cpus. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[260]
Qipeng Wang, Mengwei Xu, Chao Jin, Xinran Dong, Jinliang Yuan, Xin Jin, Gang Huang, Yunxin Liu, and Xuanzhe Liu. 2022. Melon: Breaking the memory wall for resource-efficient on-device machine learning. In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services.
[261]
Rui Wang, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella Harari, Stefanie Tignor, Xia Zhou, Dror Ben-Zeev, and Andrew T Campbell. 2014. StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. In Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing.
[262]
Shibo Wang, Shusen Yang, Hailiang Li, Xiaodan Zhang, Chen Zhou, Chenren Xu, Feng Qian, Nanbin Wang, and Zongben Xu. 2022. SalientVR: saliency-driven mobile 360-degree video streaming with gaze information. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking. Sydney NSW Australia.
[263]
Xin Wang, Zhongwei Wan, Arvin Hekmati, Mingyu Zong, Samiul Alam, Mi Zhang, and Bhaskar Krishnamachari. 2024. IoT in the Era of Generative AI: Vision and Challenges. arXiv preprint arXiv:2401.01923(2024).
[264]
Yichao Wang, Yili Ren, Yingying Chen, and Jie Yang. 2022. Wi-Mesh: A WiFi Vision-based Approach for 3D Human Mesh Construction. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[265]
Ziqi Wang, Ankur Sarker, Jason Wu, Derek Hua, Gaofeng Dong, Akash Singh, and Mani Srivastava. 2022. Capricorn: Towards Real-time Rich Scene Analysis Using RF-Vision Sensor Fusion. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[266]
Mati Wax, Tie-Jun Shan, and Thomas Kailath. 1984. Spatio-temporal spectral analysis by eigenstructure methods. IEEE transactions on acoustics, speech, and signal processing 32, 4(1984).
[267]
Jianyu Wei, Ting Cao, Shijie Cao, Shiqi Jiang, Shaowei Fu, Mao Yang, Yanyong Zhang, and Yunxin Liu. 2023. NN-Stretch: Automatic Neural Network Branching for Parallel Inference on Heterogeneous Multi-Processors. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[268]
Hao Wen, Yuanchun Li, Guohong Liu, Shanhui Zhao, Tao Yu, Toby Jia-Jun Li, Shiqi Jiang, Yunhao Liu, Yaqin Zhang, and Yunxin Liu. 2024. AutoDroid: LLM-powered Task Automation in Android(ACM MobiCom ’24). New York, NY, USA.
[269]
Hao Wu, Jinghao Feng, Xuejin Tian, Edward Sun, Yunxin Liu, Bo Dong, Fengyuan Xu, and Sheng Zhong. 2020. EMO: Real-time emotion recognition from single-eye images for resource-constrained eyewear devices. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services.
[270]
Wentai Wu, Ligang He, Weiwei Lin, Rui Mao, Carsten Maple, and Stephen Jarvis. 2020. SAFA: A semi-asynchronous protocol for fast federated learning with low overhead. IEEE Trans. Comput. 70, 5 (2020).
[271]
Yi Wu, Vimal Kakaraparthi, Zhuohang Li, Tien Pham, Jian Liu, and Phuc Nguyen. 2021. BioFace-3D: Continuous 3D facial reconstruction through lightweight single-ear biosensors. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[272]
Ao Xiao, Yunhao Liu, Yang Li, Feng Qian, Zhenhua Li, Sen Bai, Yao Liu, Tianyin Xu, and Xianlong Xin. 2019. An in-depth study of commercial MVNO: Measurement and optimization. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services.
[273]
Rui Xiao, Jianwei Liu, Jinsong Han, and Kui Ren. 2021. Onefi: One-shot recognition for unseen gesture via cots wifi. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[274]
Rui Xiao, Leqi Zhao, Feng Qian, Lei Yang, and Jinsong Han. 2024. Practical Optical Camera Communication Behind Unseen and Complex Backgrounds. In Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services.
[275]
Binbin Xie, Minhao Cui, Deepak Ganesan, Xiangru Chen, and Jie Xiong. 2023. Boosting the long range sensing potential of lora. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[276]
Binbin Xie and Jie Xiong. 2020. Combating interference for long range LoRa sensing. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[277]
Cong Xie, Sanmi Koyejo, and Indranil Gupta. 2020. Asynchronous Federated Optimization. 1903.03934 [cs.DC] https://arxiv.org/abs/1903.03934
[278]
Jiahong Xie, Hao Kong, Jiadi Yu, Yingying Chen, Linghe Kong, Yanmin Zhu, and Feilong Tang. 2023. mm3DFace: Nonintrusive 3D Facial Reconstruction Leveraging mmWave Signals. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[279]
Xiufeng Xie and Kyu-Han Kim. 2019. Source compression with bounded dnn perception loss for iot edge computer vision. In The 25th Annual International Conference on Mobile Computing and Networking.
[280]
Zhiyuan Xie, Xiaomin Ouyang, Xiaoming Liu, and Guoliang Xing. 2021. UltraDepth: Exposing high-resolution texture from depth cameras. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[281]
Zhiyuan Xie, Xiaomin Ouyang, Li Pan, Wenrui Lu, Guoliang Xing, and Xiaoming Liu. 2023. Mozart: A Mobile ToF System for Sensing in the Dark through Phase Manipulation. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[282]
Sijie Xiong, Sujie Zhu, Yisheng Ji, Binyao Jiang, Xiaohua Tian, Xuesheng Zheng, and Xinbing Wang. 2017. iBlink: Smart glasses for facial paralysis patients. In Proceedings of the 15th annual international conference on mobile systems, applications, and services.
[283]
Chenhan Xu, Tianyu Chen, Huining Li, Alexander Gherardi, Michelle Weng, Zhengxiong Li, and Wenyao Xu. 2022. Hearing Heartbeat from Voice: Towards Next Generation Voice-User Interfaces with Cardiac Sensing Functions. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[284]
Chenhan Xu, Zhengxiong Li, Hanbin Zhang, Aditya Singh Rathore, Huining Li, Chen Song, Kun Wang, and Wenyao Xu. 2019. Waveear: Exploring a mmwave-based noise-resistant speech sensing for voice-user interface. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services.
[285]
Daliang Xu, Mengwei Xu, Qipeng Wang, Shangguang Wang, Yun Ma, Kang Huang, Gang Huang, Xin Jin, and Xuanzhe Liu. 2022. Mandheling: Mixed-precision on-device dnn training with dsp offloading. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[286]
Dongzhu Xu, Anfu Zhou, Guixian Wang, Huanhuan Zhang, Xiangyu Li, Jialiang Pei, and Huadong Ma. 2022. Tutti: Coupling 5G RAN and Mobile Edge Computing for Latency-Critical Video Analytics. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (Sydney, NSW, Australia) (MobiCom ’22). New York, NY, USA.
[287]
Huatao Xu, Liying Han, Qirui Yang, Mo Li, and Mani Srivastava. 2024. Penetrative AI: Making LLMs Comprehend the Physical World(HOTMOBILE ’24). New York, NY, USA.
[288]
Huatao Xu, Dong Wang, Run Zhao, and Qian Zhang. 2019. FaHo: Deep learning enhanced holographic localization for RFID tags. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems.
[289]
Huatao Xu, Pengfei Zhou, Rui Tan, Mo Li, and Guobin Shen. 2021. LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications. In SenSys ’21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems. New York, NY, USA.
[290]
Jingao Xu, Hao Cao, Zheng Yang, Longfei Shangguan, Jialin Zhang, Xiaowu He, and Yunhao Liu. 2022. {SwarmMap}: Scaling up real-time collaborative visual {SLAM} at the edge. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22).
[291]
Mengwei Xu, Tiantu Xu, Yunxin Liu, and Felix Lin. 2021. Video Analytics with Zero-streaming Cameras. In 2021 USENIX Annual Technical Conference (USENIX ATC 21).
[292]
Mengwei Xu, Xiwen Zhang, Yunxin Liu, Gang Huang, Xuanzhe Liu, and Felix Lin. 2020. Approximate Query Service on Autonomous IoT Cameras. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services (Toronto, Ontario, Canada) (MobiSys ’20). New York, NY, USA.
[293]
Mengwei Xu, Mengze Zhu, Yunxin Liu, Felix Lin, and Xuanzhe Liu. 2018. Deepcache: Principled cache for mobile deep vision. In Proceedings of the 24th annual international conference on mobile computing and networking.
[294]
Ran Xu, Jayoung Lee, Pengcheng Wang, Saurabh Bagchi, Yin Li, and Somali Chaterji. 2022. LiteReconfig: Cost and content aware reconfiguration of video object detection systems for mobile GPUs. In Proceedings of the Seventeenth European Conference on Computer Systems.
[295]
Ran Xu, Chen lin Zhang, Pengcheng Wang, Jayoung Lee, Subrata Mitra, Somali Chaterji, Yin Li, and Saurabh Bagchi. 2020. ApproxDet: content and contention-aware approximate object detection for mobiles. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[296]
Xiangyu Xu, Jiadi Yu, Yingying Chen, Yanmin Zhu, Linghe Kong, and Minglu Li. 2019. Breathlistener: Fine-grained breathing monitoring in driving environments utilizing acoustic signals. In Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services.
[297]
Hongfei Xue, Qiming Cao, Yan Ju, Haochen Hu, Haoyu Wang, Aidong Zhang, and Lu Su. 2022. M4esh: mmwave-based 3d human mesh construction for multiple subjects. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[298]
Hongfei Xue, Yan Ju, Chenglin Miao, Yijiang Wang, Shiyang Wang, Aidong Zhang, and Lu Su. 2021. mmMesh: Towards 3D real-time dynamic human mesh construction using millimeter-wave. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services.
[299]
Francis Yan, Hudson Ayers, Chenzhi Zhu, Sadjad Fouladi, James Hong, Keyi Zhang, Philip Levis, and Keith Winstein. 2020. Learning in situ: a randomized experiment in video streaming. In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20). Santa Clara, CA.
[300]
Kang Yang and Wan Du. 2022. LLDPC: A low-density parity-check coding scheme for LoRa networks. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[301]
Qiang Yang and Yuanqing Zheng. 2024. DeepEar: Sound Localization With Binaural Microphones. IEEE Transactions on Mobile Computing 23, 1 (2024).
[302]
Zheng Yang, Yi Zhang, Kun Qian, and Chenshu Wu. 2023. {SLNet}: A Spectrogram Learning Neural Network for Deep Wireless Sensing. In 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23).
[303]
Dixi Yao, Liyao Xiang, Zifan Wang, Jiayu Xu, Chao Li, and Xinbing Wang. 2021. Context-aware compilation of dnn training pipelines across edge and cloud. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 4 (2021).
[304]
Shuochao Yao, Jinyang Li, Dongxin Liu, Tianshi Wang, Shengzhong Liu, Huajie Shao, and Tarek Abdelzaher. 2020. Deep compressive offloading: Speeding up neural network inference by trading edge computation for network latency. In Proceedings of the 18th conference on embedded networked sensor systems.
[305]
Shuochao Yao, Yiran Zhao, Huajie Shao, ShengZhong Liu, Dongxin Liu, Lu Su, and Tarek Abdelzaher. 2018. Fastdeepiot: Towards understanding and optimizing neural network execution time on mobile and embedded devices. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems.
[306]
Hyunho Yeo, Chan Chong, Youngmok Jung, Juncheol Ye, and Dongsu Han. 2020. NEMO: Enabling Neural-Enhanced Video Streaming on Commodity Mobile Devices. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking(London, United Kingdom) (MobiCom ’20). New York, NY, USA, Article 28.
[307]
Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin, and Dongsu Han. 2018. Neural Adaptive Content-aware Internet Video Delivery. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18). Carlsbad, CA.
[308]
Hyunho Yeo, Hwijoon Lim, Jaehong Kim, Youngmok Jung, Juncheol Ye, and Dongsu Han. 2022. NeuroScaler: Neural Video Enhancement at Scale. In Proceedings of the ACM SIGCOMM 2022 Conference(Amsterdam, Netherlands) (SIGCOMM ’22). New York, NY, USA.
[309]
Juheon Yi, Sunghyun Choi, and Youngki Lee. 2020. EagleEye: Wearable camera-based person identification in crowded urban spaces. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[310]
Juheon Yi and Youngki Lee. 2020. Heimdall: mobile GPU coordination platform for augmented reality applications. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. London United Kingdom.
[311]
Rongjie Yi, Ting Cao, Ao Zhou, Xiao Ma, Shangguang Wang, and Mengwei Xu. 2023. Boosting DNN Cold Inference on Edge Devices. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (Helsinki, Finland) (MobiSys ’23). New York, NY, USA.
[312]
Xiangyu Yin, Kai Huang, Erick Forno, Wei Chen, Heng Huang, and Wei Gao. 2023. PTEase: Objective Airway Examination for Pulmonary Telemedicine using Commodity Smartphones. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[313]
Yinggang Yu, Dong Wang, Run Zhao, and Qian Zhang. 2019. RFID based real-time recognition of ongoing gesture with adversarial learning. In Proceedings of the 17th Conference on Embedded Networked Sensor Systems.
[314]
Mu Yuan, Lan Zhang, Fengxiang He, Xueting Tong, and Xiang-Yang Li. 2022. Infi: end-to-end learnable input filter for resource-efficient mobile-centric inference. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[315]
Navid Zandi, Awny El-Mohandes, and Rong Zheng. 2022. Individualizing Head-Related Transfer Functions for Binaural Acoustic Applications. In 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE.
[316]
Xiao Zeng, Kai Cao, and Mi Zhang. 2017. MobileDeepPill: A small-footprint mobile deep learning system for recognizing unconstrained pill images. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services.
[317]
Xiao Zeng, Biyi Fang, Haichen Shen, and Mi Zhang. 2020. Distream: Scaling Live Video Analytics with Workload-Adaptive Distributed Edge Intelligence. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems (Virtual Event, Japan) (SenSys ’20). New York, NY, USA.
[318]
Xiao Zeng, Ming Yan, and Mi Zhang. 2021. Mercury: Efficient on-device distributed dnn training via stochastic importance sampling. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems.
[319]
Youwei Zeng, Dan Wu, Jie Xiong, Jinyi Liu, Zhaopeng Liu, and Daqing Zhang. 2020. MultiSense: Enabling multi-person respiration sensing with commodity wifi. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 3 (2020).
[320]
Youwei Zeng, Dan Wu, Jie Xiong, Enze Yi, Ruiyang Gao, and Daqing Zhang. 2019. FarSense: Pushing the range limit of WiFi-based respiration sensing with CSI ratio of two antennas. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 3 (2019).
[321]
Anlan Zhang, Chendong Wang, Bo Han, and Feng Qian. 2022. YuZu: Neural-Enhanced Volumetric Video Streaming. In 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). Renton, WA.
[322]
Ben Zhang, Xin Jin, Sylvia Ratnasamy, John Wawrzynek, and Edward Lee. 2018. AWStream: Adaptive Wide-Area Streaming Analytics. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication (Budapest, Hungary) (SIGCOMM ’18). New York, NY, USA.
[323]
Chaoyun Zhang, Marco Fiore, Cezary Ziemlicki, and Paul Patras. 2020. Microscope: mobile service traffic decomposition for network slicing as a service. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking.
[324]
Chaoyun Zhang, Paul Patras, and Hamed Haddadi. 2019. Deep Learning in Mobile and Wireless Networking: A Survey. IEEE Communications Surveys & Tutorials 21, 3 (2019).
[325]
Hanbin Zhang, Chen Song, Aosen Wang, Chenhan Xu, Dongmei Li, and Wenyao Xu. 2019. Pdvocal: Towards privacy-preserving parkinson’s disease detection using non-speech body sounds. In The 25th annual International Conference on Mobile Computing and Networking.
[326]
Huanhuan Zhang, Anfu Zhou, Yuhan Hu, Chaoyue Li, Guangping Wang, Xinyu Zhang, Huadong Ma, Leilei Wu, Aiyun Chen, and Changhui Wu. 2021. Loki: Improving Long Tail Performance of Learning-Based Real-Time Video Adaptation by Fusing Rule-Based Models. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking (New Orleans, Louisiana) (MobiCom ’21). New York, NY, USA.
[327]
Huanhuan Zhang, Anfu Zhou, Jiamin Lu, Ruoxuan Ma, Yuhan Hu, Cong Li, Xinyu Zhang, Huadong Ma, and Xiaojiang Chen. 2020. OnRL: Improving Mobile Video Telephony via Online Reinforcement Learning. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking (London, United Kingdom) (MobiCom ’20). New York, NY, USA, Article 29.
[328]
Jie Zhang, Zhanyong Tang, Meng Li, Dingyi Fang, Petteri Nurmi, and Zheng Wang. 2018. CrossSense: Towards cross-site and large-scale WiFi sensing. In Proceedings of the 24th annual international conference on mobile computing and networking.
[329]
Jing Zhang and Dacheng Tao. 2021. Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things. IEEE Internet of Things Journal 8, 10 (May 2021).
[330]
Jinrui Zhang, Deyu Zhang, Xiaohui Xu, Fucheng Jia, Yunxin Liu, Xuanzhe Liu, Ju Ren, and Yaoxue Zhang. 2020. MobiPose: Real-time multi-person pose estimation on mobile devices. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[331]
Tuo Zhang, Tiantian Feng, Samiul Alam, Dimitrios Dimitriadis, Mi Zhang, Shrikanth S Narayanan, and Salman Avestimehr. 2023. Gpt-fl: Generative pre-trained model-assisted federated learning. arXiv preprint arXiv:2306.02210(2023).
[332]
Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S Narayanan, and Salman Avestimehr. 2023. Fedaudio: A federated learning benchmark for audio tasks. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[333]
Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, and Salman Avestimehr. 2022. Federated Learning for Internet of Things: Applications, Challenges, and Opportunities. IEEE Internet of Things Magazine (IEEE IoTM) (2022).
[334]
Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, and Salman Avestimehr. 2023. TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[335]
Tianfang Zhang, Cong Shi, Payton Walker, Zhengkun Ye, Yan Wang, Nitesh Saxena, and Yingying Chen. 2023. Passive Vital Sign Monitoring via Facial Vibrations Leveraging AR/VR Headsets. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[336]
Wuyang Zhang, Zhezhi He, Luyang Liu, Zhenhua Jia, Yunxin Liu, Marco Gruteser, Dipankar Raychaudhuri, and Yanyong Zhang. 2021. Elf: accelerate high-resolution mobile deep vision with content-aware parallel offloading. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking.
[337]
Xiao Zhang, Hanqing Guo, James Mariani, and Li Xiao. 2022. U-star: An underwater navigation system based on passive 3d optical identification tags. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking.
[338]
Xiao Zhang, Griffin Klevering, Juexing Wang, Li Xiao, and Tianxing Li. 2023. RoFin: 3D Hand Pose Reconstructing via 2D Rolling Fingertips. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services.
[339]
Xiaotong Zhang, Zhenjiang Li, and Jin Zhang. 2022. Synthesized Millimeter-Waves for Human Motion Sensing. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems.
[340]
Xu Zhang, Yiyang Ou, Siddhartha Sen, and Junchen Jiang. 2021. SENSEI: Aligning Video Streaming Quality with Dynamic User Sensitivity. In 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21).
[341]
Xumiao Zhang, Anlan Zhang, Jiachen Sun, Xiao Zhu, Y. Guo, Feng Qian, and Z. Mao. 2021. EMP: edge-assisted multi-vehicle perception. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking. New Orleans Louisiana.
[342]
Yu Zhang, Tao Gu, and Xi Zhang. 2020. MDLdroidLite: A release-and-inhibit control approach to resource-efficient deep neural networks on mobile devices. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems.
[343]
Yu Zhang, Tao Gu, and Xi Zhang. 2021. MDLdroid: A ChainSGD-reduce approach to mobile deep learning for personal mobile sensing. IEEE/ACM Transactions on Networking 30, 1 (2021).
[344]
Yue Zhang, Zhizhang Hu, Uri Berger, and Shijia Pan. 2023. CMA: Cross-Modal Association Between Wearable and Structural Vibration Signal Segments for Indoor Occupant Sensing. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[345]
Ziyang Zhang, Huan Li, Yang Zhao, Changyao Lin, and Jie Liu. 2023. POS: An Operator Scheduling Framework for Multi-model Inference on Edge Intelligent Computing. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks.
[346]
Xiaopeng Zhao, Zhenlin An, Qingrui Pan, and Lei Yang. 2023. Nerf2: Neural radio-frequency radiance fields. In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking.
[347]
Xiaopeng Zhao, Guosheng Wang, Zhenlin An, Qingrui Pan, and Lei Yang. 2024. Understanding Localization by a Tailored GPT. In Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services.
[348]
Yiqin Zhao and Tian Guo. 2021. Xihe: A 3D Vision-based Lighting Estimation Framework for Mobile Augmented Reality. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services.
[349]
Xiaolong Zheng, Zhichao Cao, Jiliang Wang, Yuan He, and Yunhao Liu. 2014. Zisense: towards interference resilient duty cycling in wireless sensor networks. In Proceedings of ACM SenSys.
[350]
Yue Zheng, Yi Zhang, Kun Qian, Guidong Zhang, Yunhao Liu, Chenshu Wu, and Zheng Yang. 2019. Zero-effort cross-domain gesture recognition with Wi-Fi. In Proceedings of the 17th annual international conference on mobile systems, applications, and services.
[351]
Anfu Zhou, Huanhuan Zhang, Guangyuan Su, Leilei Wu, Ruoxuan Ma, Zhen Meng, Xinyu Zhang, Xiufeng Xie, Huadong Ma, and Xiaojiang Chen. 2019. Learning to Coordinate Video Codec with Transport Protocol for Mobile Video Telephony. In The 25th Annual International Conference on Mobile Computing and Networking (Los Cabos, Mexico) (MobiCom ’19). New York, NY, USA, Article 29.
[352]
Qihua Zhou, Song Guo, Zhihao Qu, Jingcai Guo, Zhenda Xu, Jiewei Zhang, Tao Guo, Boyuan Luo, and Jingren Zhou. 2021. Octo:{INT8} training with loss-aware compensation and backward quantization for tiny on-device learning. In 2021 USENIX Annual Technical Conference (USENIX ATC 21).
[353]
Yun Zhu, Yinxiao Liu, Felix Stahlberg, Shankar Kumar, Yu hui Chen, Liangchen Luo, Lei Shu, Renjie Liu, Jindong Chen, and Lei Meng. 2023. Towards an on-device agent for text rewriting. arXiv preprint arXiv:2308.11807(2023).
Index Terms
- Artificial Intelligence of Things: A Survey
Recommendations
Paving the Way Towards Collective Intelligence at the IoT Edge
AbstractWith the scale of data generated and the increasing computing capabilities at the IoT Edge, moving intelligence to end-devices and gateways in IoT networks is within the realms of possibility. There are tremendous hopes on how self-awareness in ...
Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions
AbstractThe Artificial Intelligence of Things (AIoT), a combination of the Internet of Things (IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture (SA). AIoT has been adopted in many applications including ...
Artificial intelligence in Internet of things
Functioning of the Internet is persistently transforming from the Internet of computers (IoC) to the ‘Internet of things (IoT)’. Furthermore, massively interconnected systems, also known as cyber‐physical systems (CPSs), are emerging from the assimilation ...
Comments
Information & Contributors
Information
Published In
EISSN:1550-4867
Table of ContentsCopyright © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Journal Family
Publication History
Online AM: 30 August 2024
Accepted: 07 August 2024
Revised: 08 July 2024
Received: 10 January 2024
Check for updates
Author Tags
Qualifiers
- Survey
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 551Total Downloads
- Downloads (Last 12 months)551
- Downloads (Last 6 weeks)551
Reflects downloads up to 15 Oct 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in