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- research-articleJune 2024
Are Large Language Models Capable of Causal Reasoning for Sensing Data Analysis?
EdgeFM '24: Proceedings of the Workshop on Edge and Mobile Foundation ModelsJune 2024, Pages 24–29https://doi.org/10.1145/3662006.3662064The correlation analysis between socioeconomic factors and environmental impact is essential for policy making to ensure sustainability and economic development simultaneously. With the development of Internet of Things (IoT), citizen science IoT ...
- research-articleMarch 2024
IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Volume 8, Issue 1Article No.: 7, Pages 1–29https://doi.org/10.1145/3643516While occlusal diseases - the main cause of tooth loss -- significantly impact patients' teeth and well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing occlusal diseases could result in difficulties in eating, speaking, and ...
- short-paperApril 2024
Poster Abstract: Enhancing Fault Resilience of Air Quality Monitoring in San Joaquin Valley: A Data Equity Analysis
SenSys '23: Proceedings of the 21st ACM Conference on Embedded Networked Sensor SystemsNovember 2023, Pages 514–515https://doi.org/10.1145/3625687.3628384This paper examines fault resilience among citizen-science air quality monitoring networks in California's economically challenged San Joaquin Valley (SJV). We examine disparities in monitoring capabilities and data equity between the SJV and the San ...
- research-articleMay 2023
CMA: Cross-Modal Association Between Wearable and Structural Vibration Signal Segments for Indoor Occupant Sensing
IPSN '23: Proceedings of the 22nd International Conference on Information Processing in Sensor NetworksMay 2023, Pages 96–109https://doi.org/10.1145/3583120.3586960Indoor occupant sensing enables many smart home applications, and various sensing systems have been explored. Based on their installation requirements, we consider two categories of sensors – on- and off-body – and we look into the combination of them ...
- research-articleMay 2023
Augmenting Vibration-Based Customer-Product Interaction Recognition with Sparse Load Sensing
CPS-IoT Week '23: Proceedings of Cyber-Physical Systems and Internet of Things Week 2023May 2023, Pages 266–271https://doi.org/10.1145/3576914.3589560This paper introduces a multimodal solution for autonomous retail customer-product interaction recognition using a combination of vibration and load sensing. Scalable and robust customer-product interaction recognition is important for autonomous ...
- research-articleJanuary 2023
CIPhy: Causal Intervention with Physical Confounder from IoT Sensor Data for Robust Occupant Information Inference
SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor SystemsNovember 2022, Pages 966–972https://doi.org/10.1145/3560905.3568304Occupant information inference with IoT sensor data enables many smart applications, such as patients'/older adults' in-home monitoring. The difficulty of collecting labeled real-world IoT sensor data often leads to reliability and scalability issues for ...
- research-articleJune 2022
MODES: Multi-sensor occupancy data-driven estimation system for smart buildings
e-Energy '22: Proceedings of the Thirteenth ACM International Conference on Future Energy SystemsJune 2022, Pages 228–239https://doi.org/10.1145/3538637.3538852Buildings account for more than 40% of the energy US primary energy consumption. Of all the building services, heating, ventilation, and air-conditioning (HVAC) account for almost 50% of that energy use. Despite all the resources used, many users are ...
- short-paperNovember 2021
Footstep-Induced Floor Vibration Dataset: Reusability and Transferability Analysis
SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor SystemsNovember 2021, Pages 546–551https://doi.org/10.1145/3485730.3494117Footstep-induced floor vibration sensing has been used in many smart home applications, such as elderly/patient monitoring. These systems often leverage data-driven models to infer human information. Therefore, characterizing datasets is crucial for the ...
- research-articleMay 2021
Vibration-Based Indoor Human Sensing Quality Reinforcement via Thompson Sampling
CPHS21: Proceedings of the First International Workshop on Cyber-Physical-Human System Design and ImplementationMay 2021, Pages 33–38https://doi.org/10.1145/3458648.3460012This paper presents an online learning algorithm that recommends sensor locations for structural vibration-based indoor human sensing systems to achieve optimal sensing quality for high learning accuracy. The intuition is that we model the deployment ...
- posterMay 2021
- posterNovember 2020
Inferring finer-grained human information with multi-modal cross-granularity learning: PhD forum abstract
SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor SystemsNovember 2020, Pages 805–806https://doi.org/10.1145/3384419.3430580Existing machine learning algorithms for human information inference are typically data-driven models trained on carefully labeled datasets. Given the significant labeling effort, traditional pure data-driven approaches are challenging to implement for ...
- research-articleSeptember 2020
A window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensor
- Yiwen Dong,
- Jingxiao Liu,
- Yitao Gao,
- Sulagna Sarkar,
- Zhizhang Hu,
- Jonathon Fagert,
- Shijia Pan,
- Pei Zhang,
- Hae Young Noh,
- Mostafa Mirshekari
UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable ComputersSeptember 2020, Pages 390–395https://doi.org/10.1145/3410530.3414336This paper introduces a window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensors. Nurse care activity recognition is an essential part of ensuring high quality patient care ...
- research-articleSeptember 2020
Fine-grained activities recognition with coarse-grained labeled multi-modal data
UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable ComputersSeptember 2020, Pages 644–649https://doi.org/10.1145/3410530.3414320Fine-grained human activities recognition focuses on recognizing event- or action-level activities, which enables a new set of Internet-of-Things (IoT) applications such as behavior analysis. Prior work on fine-grained human activities recognition ...
- short-paperNovember 2019
Device-free Sleep Stage Recognition through Bed Frame Vibration Sensing
DFHS'19: Proceedings of the 1st ACM International Workshop on Device-Free Human SensingNovember 2019, Pages 39–43https://doi.org/10.1145/3360773.3360883Sleep disorder impairs people's health. To better analyze user's sleep quality, it is important to monitor people's sleep stages. Prior methods, such as polysomnography (PSG) and Fitbit, are often intrusive and having potential to change user's daily ...