Agriculture Robotics (Crop Classification and Yield Prediction)

About the Project

The investigation of machine learning techniques for crop classification and yield prediction using robotics and sensors is a promising research area in agriculture robotics. Machine learning algorithms can learn from data collected by sensors mounted on robots, allowing for precise classification of crops and accurate yield predictions. This approach can help farmers optimize their crop management strategies, reduce costs, and increase yields. Moreover, with the integration of robotics, the data collection and analysis process can be automated, saving time and increasing efficiency. The results of this research could potentially revolutionize the way farmers manage their crops and lead to more sustainable and profitable agriculture practices.

Department and Campus

HUT Labs, Electronics and Communication Engineering, School of Engineering, Amritapuri

Skillsets Preferred from Applicants

Good analytical skills in robotics with machine learning or deep learning skills and good experience in one or more of the following areas: software development or embedded design and debugging