Fire Alarm System for Smart Cities Using Edge Computing
Author | Mahgoub, Asma |
Author | Tarrad, Nourhan |
Author | Elsherif, Rana |
Author | Ismail, Loay |
Author | Al-Ali, Abdulla |
Available date | 2024-08-14T06:12:19Z |
Publication Date | 2020 |
Publication Name | 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 |
Resource | Scopus |
Abstract | The current urban planning trend is to build smart cities that are advanced, safe and sustainable. To build these cities several technologies could be exploited including the Internet of Things (IoT) and edge computing. This motivated us to develop an IoT-based fire alarm system that uses edge computing. The developed system would be suitable in smart cities, as it mitigates issues faced by the existing fire alarm systems like installation overhead and lack of remote warning. Our system is an ad-hoc network of several sensing nodes and a single central node. Each of these sensing nodes consists of an ESP8266-nodeMCU connected to different types of sensors, such as smoke, temperature, humidity, flame, Methane and Carbon Monoxide (CO) sensors. These nodes are responsible for sensing the environment and detecting fire which means that they are smart end nodes and hence satisfying one of the characteristics of edge computing. The nodes transfer their readings to a centralized node that was implemented with a Raspberry Pi computer. Communication between the sensing node and the central node is through Message Queuing Telemetry Transport (MQTT) protocol which is carried via a bridge node. When a node detects fire, it signals the centralized node to alert the user and the fire department using the attached 4G module. An SMS is sent to them and the user is called. Users can inquire about the status of their home by sending an SMS. A prototype for the system performed the desired functionalities successfully with an average delay of less than 30 seconds and a node coverage of 1400m2. |
Sponsor | This paper was supported by Qatar university Internal Grant No. QUST-1-CENG-2019-30. The findings achieved herein are solely the responsibility of the author[s]. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Ad-hoc network Edge Computing ESP8266 Fire Alarm System Internet of Things (IoT) Mesh network MQTT Raspberry Pi Smart City |
Type | Conference Paper |
Pagination | 597-602 |
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Computer Science & Engineering [2284 items ]