Generation of routes through ACO for detection of forest fires in the State of Mexico
DOI:
https://doi.org/10.29298/rmcf.v14i77.1349Keywords:
Ant colony, artificial intelligence, wildfire, route planning, autonomous aerial vehiclesAbstract
Fires are part of the cycle of some ecosystems and can cause the degradation of others. Their main causes are anthropogenic, including, among others, poorly extinguished bonfires, agricultural activities, and dumping of garbage, all of which generate habitat loss and air pollution on a large scale. This paper refers to the application of a genetic algorithm based on an ant colony to generate, at a theoretical level, verification routes for the monitoring and early detection of forest fires in the State of Mexico by means of unmanned aerial devices, as it is one of the entities with the highest number of forest fires in Mexico. The data used in the proposal were drawn from the reports generated by the National Forestry Commission (Comisión Nacional Forestal, Conafor). During the analysis process, those municipalities that have been affected in at least three different geographic locations were filtered out. In the course of the evaluation process, the software developed displayed the routes with the shortest distances, reordering the filtered localities. Finally, a map is displayed pinpointing the localities where a forest fire has occurred and showing the approximate distance of the entire route. The new routes planned with this procedure resulted in an average 54 % reduction compared to a sequential route.
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