Personal safety monitoring system of electric power construction site based on AIoT Technology
Pages 493 - 504
Abstract
For the purpose of real-time monitoring the hazard information on the electric power construction site, a personal safety monitoring system based on Artificial intelligence internet of things (AIoT) technology is designed. After the system sensing layer collects the gas information of the construction site through the gas sensor, limit current oxygen sensor and DS1820B temperature sensor, the edge computing device of the edge layer directly stores its calculation in the database of the platform layer through the data gateway. The Artificial Intelligence (AI) analysis module of this layer invokes the monitoring data of the power construction site of the database, and uses the personal safety identification method of the power construction site based on artificial intelligence technology, to complete the abnormal identification of monitoring data and realize personal safety monitoring. In addition, the system is also equipped with a power-fail detection module, which can collect the working voltage through the voltage transformer and compare it with the mains power standard to judge whether there is a power-fail risk, so as to prevent the problem of threatening personal safety due to the power-fail of the energized equipment. After testing, the system can monitor the operation status of the construction site in real time to protect personal safety.
References
[1]
Venkatanarayanan A., Vijayavel A. and Rajagopal A., Design of sensor system for air pollution and human vital monitoring for connected cyclists, IET Communications 13(19) (2019), 3181–3186.
[2]
Yan X., Zhang H. and Li H., Estimating Worker-Centric 3D Spatial Crowdedness for Construction Safety Management Using a Single 2D Camera, Journal of Computing in Civil Engineering 33(5) (2019), 04019030.1–04019030.13.
[3]
Chen N., Qiu T. and Zhou X., An intelligent robust networking mechanism for the internet of things, IEEE Communications Magazine 57(11) (2019), 91–95.
[4]
Andreev S., Dao N.D. and Misra P., Internet of Things and Sensor Networks, IEEE Communications Magazine 58(9) (2020), 12–12.
[5]
Abbasikesbi R., Nikfarjam A. and Nemati M., Developed wireless sensor network to supervise the essential parameters in greenhouses for internet of things applications, IET Circuits Devices and Systems 14(8) (2020), 1258–1264.
[6]
Tang M., Gao L. and Huang J., Communication, computation, and caching resource sharing for the internet of things, IEEE Communications Magazine 58(4) (2020), 75–80.
[7]
Wei H., Feng W. and Zhang C., Creating efficient blockchains for the internet of things by coordinated satellite-terrestrial networks, IEEE Wireless Communications 27(3) (2020), 104–110.
[8]
Guo S., Qi Y. and Yu P., When network operation meets blockchain: an artificial-intelligence-driven customization service for trusted virtual resources of IoT, IEEE Network 34(5) (2020), 46–53.
[9]
Zhang K., Zhu Y. and Maharjan S., Edge Intelligence and Blockchain Empowered 5G Beyond for the Industrial Internet of Things, IEEE Network 33(5) (2019), 12–19.
[10]
Pace P., Fortino G. and Zhang Y., Intelligence at the Edge of Complex Networks: The Case of Cognitive Transmission Power Control, IEEE Wireless Communications 26(3) (2019), 97–103.
[11]
Peng M., Quek T. and Mao G., Artificial-Intelligence-Driven Fog Radio Access Networks: Recent Advances and Future Trends, IEEE Wireless Communications 27(2) (2020), 12–13.
[12]
Wang J., Pan J. and Esposito F., Edge Cloud Offloading Algorithms: Issues, Methods, and Perspectives[J], ACM Computing Surveys 52(1) (2019), 1–23.
[13]
Abd-Elmagid M.A., Pappas N. and Dhillon H.S., On the Role of Age of Information in the Internet of Things, IEEE Communications Magazine 57(12) (2019), 72–77.
[14]
Zhang Y., Ma X. and Zhang J., Edge Intelligence in the Cognitive Internet of Things: Improving Sensitivity and Interactivity, IEEE Network 33(3) (2019), 58–64.
[15]
Nikolaou P. and Menounou P., Analytical and numerical methods for efficient calculation of edge diffraction by an arbitrary incident signal, The Journal of the Acoustical Society of America 146(5) (2019), 3577–3589.
[16]
Maier M., Ebrahimzadeh A. and Rostami S., The Internet of No Things: Making the Internet Disappear and “See the Invisible, IEEE Communications Magazine PP(99) (2020), 2–8.
[17]
Liang Y., Hu Z. and Li K., Power consumption model based on feature selection and deep learning in cloud computing scenarios, IET Communications 14(10) (2020), 1610–1618.
[18]
Hung P., Demirkan H. and Huang S.C., Editorial: Special Section on Services Computing Management for Artificial Intelligence and Machine Learning, IEEE Transactions on Engineering Management 68(1) (2021), 101–104.
[19]
Zhao J. and Kamwa I., Guest Editorial: Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control, IET Generation Transmission and Distribution 14(19) (2020), 3943–3944.
[20]
Chai Q., Luo Y. and Ren J., Review on fiber-optic sensing in health monitoring of power grids, Optical Engineering 58(7) (2019), 072007.1–072007.20.
Recommendations
Tunnel construction process monitoring system based on Internet of Things technology
CAIBDA '24: Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and AlgorithmsThe process of tunnel construction is essential. Real-time monitoring of the tunnel construction process can find and solve the problems in the tunnel construction in time to ensure a smooth construction process and stable construction quality. Therefore,...
Intelligent Video Monitoring and Analysis System for Power Grid Construction Site Safety Using Wireless Power Transfer
Power grid construction significantly enhances power grid management and risk control. Inconsistent operations at construction sites can jeopardize grid stability and crew safety. Traditional power lines are less favored due to mobility limitations, ...
Understanding Pedestrians’ Perception of Safety and Safe Mobility Practices
CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing SystemsWalking is one of the greenest and most common travel modes. However, evidence shows a trend of decreased walking, and safety is a key barrier preventing many people from walking. Additionally, there is a limited understanding of pedestrians’ safe ...
Comments
Information & Contributors
Information
Published In
© 2024 – IOS Press. All rights reserved.
Publisher
IOS Press
Netherlands
Publication History
Published: 10 January 2024
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 12 Nov 2024
Other Metrics
Citations
View Options
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