Huzaifa Muhammad

This presentation highlights a data-driven smart agriculture system that tracks soil health and crop yields. Modern day agriculture utilizes many digital methods and tools for precision farming and smart resource use. The system is designed to be remotely powered with longrange wireless communication and have effective machine learning for farming decisions. Environmental and soil data is collected through a smart controller and displayed on a webbased dashboard.

A moisture prediction model was constructed with 2,000 accurate field observations. It is capable of anomaly detections, moisture forecasts and a soil energy composite index. The project is in active development. The completed phases along with the future directions and goals will be discussed. This data agriculture system is an important contribution in developing sustainable methods in smart farming. Speaker Name: 

Biography:

Huzaifa Muhammad is a graduate engineering student at McMaster University with a background in manufacturing and mechatronics. He has extensive experience in various digital systems and sensor-based networks. Exploring the connections between data-driven applications, engineering systems, and machine learning is an area that he is actively working on.