Abstract: Design and implementation of fire warning and alarm systems for detecting true fire accidents with classified false alarms. The KNN algorithm is used to detect the true presence of fire. In this System mainly two phases. The first phase of Machine Learning and the other phase consist of a IOT. The Internet of Things (IoT) is very helpful for predicting and monitoring this kind of situation. As it can work with real time data as well as the past data that was recorded earlier. This IoT sends data through Wireless Sensor Network (WSN) to the computational devices so that the result can be generated. Thus many have moved from physical parameter fire prediction to real time computational monitoring. The proposed system uses different atmospheric sensors such as humidity, temperature, smoke and flame. The recorded data is stored and passed to the device and thus the result is obtained. This system has been applied to the arduino Uno micro-controller. Sensors are used to collecting data & these data were transferred to arduino Uno microcontroller board. The GSM module alerts the fire warning via SMS.

Keywords: IOT, FDWS, Multi-Sensor, KNN, MATLAB, ThingSpeak.

Works Cited:

Niteenkumar Vaghela, Rushikesh Chaudhari , Jigar Dalvadi, Krutika Trivedi" DAn Intelligent Fire Warning Application Using KNN ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 10, pp. 148-150, 2023. Crossref https://doi.org/10.17148/IJARCCE.2023.121020

PDF | DOI: 10.17148/IJARCCE.2023.121020

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