We have developed a machine learning model based on satellite data on characteristics most responsible for locust infestation: wind, humidity, surface temperatures, and vegetation index. The end result is a website map that can be used to detect and assess current risk levels as well as predict locust invasions based on location and time.

It identifies and anticipates locust location and migration in susceptible areas. We tuned our project to create a heat map indicating places most at risk of locust infestation

Farmers, local officials, and companies may observe our model's detections and forecasts in the form of an interactive map thanks to our interactive, AI-powered, user-friendly website.

Overall, our project aims to provide knowledge into locust swarming, giving municipal officials more time to plan and prepare for an infestation, boosting local agriculture, and providing farmers with a much-needed chance to safeguard their crops, ultimately saving billions.