The use of AI for sustainability can be taken to the next level by using machine learning, a subset of AI, to combat forest fires efficiently and safely and even prevent them from happening altogether.
We all remember the devastation caused by the Australian forest fires of 2019. Similarly, the haunting memories of the California 2021 wildfire are still fresh in our memories. While there is very little we can do on our own to fight forest fires, we can always turn to technology for help.
We are already using AI for sustainability efforts. It is also playing a major role in helping us combat forest fires. In this article, however, we will shift our attention to machine learning, a subset of artificial intelligence.
Let’s have a look at three ways in which machine learning can help us combat forest fires: 
FIRE PREDICTION
Machine learning can be used in two major ways for fire prediction. First, using an image-based approach. Secondly, using a sensor-based approach.
Image-based approach
In this method, a machine learning model is trained to detect forest fires. The model is provided with a dataset of images of forests and other large-scale vegetation areas. The models are then trained to identify images with and without forest fires.
The machine learning model can be used by drones with sensors that are flown over deep, dense vegetation areas. Based on their learning, the drone sends automated fire warnings with the exact location coordinates. This can help douse a fire before it takes a massive form.
Sensor-based approach
In this method, a variety of sensors are placed across the forest to help with forest fire detection. These sensors measure the levels of gases such as carbon monoxide and oxygen. It then analyzes the data along with other parameters like the temperature and humidity levels. The machine learning model is trained with the data. If any anomaly is detected, the machine learning model warns the forest officials of a possible forest fire in the making.
FIREFIGHTER ASSISTANCE
Fighting fires, especially wildfires, is a dangerous job. Firefighters always face the issue of low visibility due to smoke when combating fires. Moreover, they come across various obstacles during the operation.
This issue can be solved with a simple machine learning model. A camera with edge detection and object identification capabilities can be mounted on the cap of the firefighters. The camera will capture the environment data, send it to the processor, which will then process the data using filters and project it on AR glasses worn by them. This will help the firefighters discern their surroundings more clearly.
Another application of machine learning for firefighters’ assistance is monitoring their health parameters along with other data. For example, firefighters are at risk of heart attacks, seizures and suffocation due to the heat and smoke. A machine learning model can be trained to analyze the data from sensors like oxygen level detectors, body temperature detectors and others. The data is then analyzed by the machine learning algorithm to classify the firefighter’s condition as safe or in danger.
This way, only the best-fit firefighters can be used during the operation, reducing the time required and possibly even saving human lives.
The use of AI for sustainability can also be expanded to fighting forest fires and preventing them from happening in the first place. AI, machine learning and other associated technologies have enormous potential in the fire and safety domain.
