Sattelite Imaging for Canal Identification Using AI


Image 1
Image 2

Project Team : Shivamani G 121cs0012 & Surya 121ad0004 & Sujan 121ad0011

We are wroking on integration of satellite imagery with advanced data analytics is transforming agriculture by enhancing productivity and promoting sustainable practices. Innovative technologies, such as smart irrigation systems, leverage machine learning and deep learning to optimize resource management, addressing water scarcity challenges.

Our approach employs efficient navigation techniques through advanced algorithms like Near-Optimal Bidirectional Search (NBS), streamlining pathfinding solutions in dynamic environments. This adaptability ensures accurate routing and minimizes travel time for agricultural operations.

Additionally, we implemented NDWI-based segmentation using a U-Net model, improving the accuracy of water body identification. By comparing various pathfinding algorithms, including A*, Dijkstra’s, and Bellman-Ford, we evaluated their efficiency in navigation tasks.

Back