Precision agriculture by robotic data collection and knowledge based analysis

About the Project

Robots are becoming increasingly essential in the practice of precision agriculture due to labor shortages, higher productivity needs, and the demand for sustainable farming practices. This project will focus on the use of cutting-edge robotic navigation, perception, and data processing capabilities to enable mobile robots and sensor networks to monitor farm fields and greenhouses and produce information in a usable format for use by farmers and environmentalists. Repeatable gathering of crop and environment data is essential to enabling increased situational awareness and intervention capability in precision agriculture practices.

Technologies that can be included in this research project include robust Simultaneous Localization and Mapping (SLAM), kinematic control for sensing and intervention robots, Machine Vision and image analysis systems, and robust telemetry and behaviour execution methodologies suitable for field robotics.

The use of deep learning networks and knowledge-based intelligence for data processing can also be included as appropriate. The goal is to achieve situational awareness, anomaly detection, and a comprehensive analysis of crop anomalies by applying prior knowledge and data localization for weed removal, yield prediction, and disease diagnosis.

This project is intended to be run collaboratively with India's IIT Indore AgriHub. The primary objective of AgriHub is to transform the agriculture sector by harnessing the potential of genomics, phenomics, data analytics, and artificial intelligence. The AgriHub aims to develop a pipeline of technologies for crop improvement, precision agriculture, and pest and disease management, which includes data gathering and intervention technologies.

This project is open-ended making it suitable for MSc by Research and PhD level.

For more details about this project, please contact Dr. Mark Post, email: mark.post@york.ac.uk.

How to Apply:

Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the School of Physics, Engineering and Technology website for details about funding opportunities at York.