Projects

Artificial intelligence (AI) has the potential to transform agriculture with applications on multiple farm robots. AI is not reaching its full potential of real-time, high-speed actionable insights because of significant bottlenecks in the data transmission speed between the robots ​where data is collected and high-performance computers where AI processing takes place.This is limiting the use of intelligent technology on farms.

This project is developing a 5G pipeline to unlock the application of AI on UK farms allowing vast quantities of data, with high-precision location information to move rapidly between robotic devices. It will enable growers to deploy AI-driven smart agriculture technologies to increase productivity and reduce costs overall, facilitating the next generation of UK agriculture. Please check the following link to the Ceres website.

This research project aims to build forecasting and decision support systems for the farming industry. These systems will provide farmers with information about the crop yield and crop growing timing. This information will be crucial for better crop utilisation, optimised harvesting, and labour scheduling in agriculture. In this project, I am researching and implementing forecasting tools for this domain. Additionally, I am part of the team in charge of the data collection systems. This project is in partnership with CERES. For more information about the project, please check the following link to the Ceres website. .

This is an ongoing project at King's College London at the interactionLAb. We are focused on studying methods to enable collaborations between human and robots in agricultural settings. Among the multiple research outputs, our studies show how to improve human opinion towards robot ro-workers. For more information about these topics you can take a look to our publications. Within this project, I am particularly interested in adapting computer vision algorithms to make them trustworthy.