Design and Implementation of a Fire Detection andControl System with Enhanced Security and Safety for Automobiles Using Neuro-Fuzzy Logic

Context: The automobile industry has included active and passive safety. Active safety incorporates elements to avoid crashes and collisions. Some elements are ABS brakes and stabilization bars, among others. On the other hand, passive safety avoids or minimizes damage to the occupants in the event of an accident. Some passive safety features include seat belts and front and curtain airbags for the driver and other occupants. Method: In this research work, we propose a new category called Extraordinary Passive Safety (XPS). A model of a sensor network was designed to inspect the conditions inside the car to detect fire, smoke, gases, and extreme temperatures. The sensors send data to a device (DXPS) capable of receiving and storing the data. Results: Each sensor collects data and sends it to the DXPS every period. The sensor sends 0s while there is no risk, and 1s when it detects a risk. When the DXPS receives a 1, the pattern is evaluated, and the risk is identified. Since there are several sensors, the reading pattern is a set of 0s (000000). When a pattern with one or more 1s (000100, 010101) is received, the DXPS can send an alert or activate a device. Conclusions: The proposed solution could save the lives of children left in the car or people trapped when the car catches fire. As future work, it is intended to define the devices to avoid or minimize damage to the occupants such as oxygen supply, gas extraction, regulating the temperature, among others.

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Design and Implementation of a Fire Detection andControl System with Enhanced Security and Safety for Automobiles Using Neuro-Fuzzy Logic

Cited by 2 publications

References 17 publications

Iot-Based Fleet Tracking with Engine Control for Automobiles

Iot-Based Fleet Tracking with Engine Control for Automobiles

Extraordinary Passive Safety in Cars Using a Sensor Network Model

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