Due to hot and dry weather in Mexico, the country is always facing a high threat of massive wildfires. In the past 20 years wildfires have destroyed 47,000 square kilometers in Mexico.
This project aims at developing a forest monitoring system based on an energy harvesting sensor network, to reduce the risk of massive fire in Mexico.
As Mexico has ample amounts of sunlight during the year, energy-harvesting wireless sensor networks (EH-WSNs) that use solar energy as a power source have great potential to be used for environmental monitoring applications such as forest monitoring around the country.
However in EH-WSNs, due to uncertainty around how much energy can be harvested, reliable data communication that takes in to account the available resources is necessary. For this project we have developed a cross-layer optimisation approach that uses information from different layers of the network.
The development of a reliable wireless network will have multiple benefits. Improved detection of high-risk areas mean that preventative measures can be taken early on, while quicker and more accurate detection of wildfires mean that resources can be deployed effectively. Better detection of fires will give the authorities time to react effectively, increasing the chance that a fire is brought under control quickly and reducing the amount of damage caused.
This project is run in collaboration with researchers from Tecnologico de Monterrey, Mexico.