Fire Detection System for Urban Structures with Integrated use of Multisensors in Embodied Technology

Abstract

Objective: Create a sustainable, low-cost and effective fire detection system (FDS) for urban buildings, based on embedded technology, as an alternative to traditional detection systems. Method: experimental research that used the hypothetical-deductive method, with assemble hardware using the ATMEGA328P microcontroller and the MQ2 gas sensors, MLX90614 temperature and LM393 flame. When building the software, a qualitative model was created, based on everyday observations, associating it with a logical expression; Then, a quantitative model was created based on experimental data subjected to computational analysis using the decision tree method, defining a heuristic for early detection of fire patterns with precision. Results and conclusions: The suggested FDS had a shorter response time than the red ampoule sprinkler and an accuracy of 94%. This system proved to be more agile than common detectors, reducing water and energy consumption when fighting fires and the amount of resources used to replace affected assets. Furthermore, it has a low cost, making it accessible even at a residential. Implications of the research: It can be said that this research represents an important step in the construction of sustainable FDS, bringing social, economic and environmental benefits; and efficient due to the use of computational data analysis. Originality/Value: FDS which uses embedded technology and computational analysis to process fire variables, improves this analysis and allows for more agile and accurate detection, in addition to making the detection system cheaper and reducing the use of resources due to the fire.