Citation
Abstract
In recent years, fire detection technologies have helped safeguard lives and property from hazards. Early fire warning methods, such as smoke or gas sensors, are ineffectual. Many fires have caused deaths and property damage. IoT is a fast-growing technology. It contains equipment, buildings, electrical systems, vehicles, and everyday things with computing and sensing capabilities. These objects can be managed and monitored remotely as they are connected to the Internet. In the Internet of Things concept, low-power devices like sensors and controllers are linked together using the concept of Low Power Wide Area Network (LPWAN). Long Range Wide Area Network (LoRaWAN) is an LPWAN product used on the Internet of Things (IoT). It is well suited for networks of things connected to the Internet, where terminals send a minute amount of sensor data over large distances, providing the end terminals with battery lifetimes of years. In this article, we design and implement a LoRaWAN-based system for smart building fire detection and prevention, not reliant upon Wireless Fidelity (Wi-Fi) connection. A LoRa node with a combination of sensors can detect smoke, gas, Liquefied Petroleum Gas (LPG), propane, methane, hydrogen, alcohol, temperature, and humidity. We developed the system in a real-world environment utilizing Wi-Fi Lora 32 boards. The performance is evaluated considering the response time and overall network delay. The tests are carried out in different lengths (0–600 m) and heights above the ground (0–2 m) in an open environment and indoor (1st Floor–3rd floor) environment. We observed that the proposed system outperformed in sensing and data transfer from sensing nodes to the controller boards.
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Official URL or Download Paper: https://www.mdpi.com/1424-8220/22/21/8411
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Computer Science and Information Technology |
DOI Number: | https://doi.org/10.3390/s22218411 |
Publisher: | Multidisciplinary Digital Publishing Institute |
Keywords: | Internet of Things; LPWAN; LoRaWAN; Fire detection; Response time |
Depositing User: | Ms. Nur Faseha Mohd Kadim |
Date Deposited: | 17 Jul 2024 03:18 |
Last Modified: | 17 Jul 2024 03:18 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/s22218411 |
URI: | http://psasir.upm.edu.my/id/eprint/100146 |
Statistic Details: | View Download Statistic |
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