Abstract

IoT (Internet of Things) is dominating all over the world for developing technology. It is another information industry following the computer, internet, and mobile connection. In modern society, we must ensure security for leading a comfortable life. Nowadays, security has been affected by different types of matters. Gas leakage and fire incidents are considered among them. At present, there are many undesirable accidents from gas leakage and fire incidents. One way to prevent accidents involving gas leakage and fire incident detection is to affix a gas leakage and fire incident detection device at adequate places. Indeed, when the gas leakage or fire incident occurs, then the temperature can be increased naturally. Our proposed work, a simple system using low-cost devices, has been designed to send a phone call to the user via the GSM module in case of any gas or smoke leakage. It also sends data to the alarm, alerting the users and sending a graphical alert to the server via NodeMCU. Besides, a temperature sensor also detects the temperature of that hazardous situation at the same time and sends data to the web server. We are using different algorithms to know the sensor's early predictions' overall accuracy in real-life-critical situations through the machine learning approach. This proposed work will contribute if gas leaks or fires occur at home or in the industry, then people can take the necessary precaution in advance.

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