Abstract
The introduction of effective early warning systems is imperative due to the substantial danger that floods pose to individuals, assets, and infrastructure. This abstract presents a cutting-edge Internet of Things (IoT)-enabled flood detection system that is intended to provide prompt notifications and alarms in the case of flooding. The system offers a comprehensive approach to flood monitoring by combining real-time communication, complex data processing algorithms, and sensor networks. The flood detector system is made up of multiple sensor nodes that are precisely and continuously monitoring water levels in flood-prone locations. To deliver real-time, exact water level measurements, these sensor nodes use cutting-edge technology such as ultrasonic and pressure sensors. The data gathered by these sensors is then wirelessly transferred to a centralized server for further processing. The advantages this proposed flood detector system offers distinguish it from conventional flood monitoring techniques. It is excellent at detecting floods in real time, cutting down on response times, improving situational awareness, and enabling efficient coordination amongst different parties. By using the potential of IoT technology, this system helps to build more resilient communities while also reducing the effect of flood-related calamities.
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Mohammad Razali, Mohammad Fazrul Fahmi UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Advisor Mohd Nordin, Atiqah Hamizah 314466 |
Subjects: | T Technology > TC Hydraulic engineering. Ocean engineering > River protective works. Regulation. Flood control T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunication > Wireless communication systems. Mobile communication systems. Access control |
Divisions: | Universiti Teknologi MARA, Johor > Pasir Gudang Campus > College of Engineering |
Programme: | Diploma of Electrical Engineering |
Keywords: | Flood detections, IoT notification |
Date: | 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/97892 |
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