Smart City Gnosys
Smart city article details
| Title | Iot Based Emergency Detection And Response System |
|---|---|
| ID_Doc | 33657 |
| Authors | Muayad M.F.; Yahya S.K.; Rashid R.A. |
| Year | 2024 |
| Published | Conference Proceedings - IEEE International Conference on Advanced Telecommunication and Networking Technologies: Empowering Telecommunication Technologies for Sustainable Future, ATNT 2024 |
| DOI | http://dx.doi.org/10.1109/ATNT61688.2024.10719072 |
| Abstract | The proliferation of internet-connected devices is expanding exponentially, connecting people and devices to the Internet. This connectivity supports the Internet of Things (IoT), yet IoT safety management remains a challenge in smart cities. Issues like poor coordination among emergency teams, inadequate real-time monitoring, and lack of data-driven responses hinder efficient emergency management, causing delays, casualties, and property damage. This project introduces an efficient emergency response system (EDRS) to tackle fire hazards, gas leaks, and other emergencies. The system utilizes the Raspberry Pi 4B, integrating sensors (flame, gas, temperature, GPS) with the Blynk 2.0 IoT platform. Deep learning and the YOLO algorithm enable object detection to identify emergencies like fire and criminal actions. Results show the system accurately detects dangerous objects with an 85.4% accuracy rate and has a benefit-to-cost ratio of 11% compared to similar systems. The EDRS enhances safety and emergency management efficiency. © 2024 IEEE. |
| Author Keywords | Artificial Intelligent; OpenCV; Python; Raspberrypi |
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