Agrifood electronics · UCL
Royal Academy of Engineering Research Fellow
Department of Electronic and Electrical Engineering, University College London
I build sensing and data systems for climate-smart agriculture: RF and microwave sensors, IoT field networks, drone and satellite observation, and machine learning. The work runs along the whole cassava value chain in sub-Saharan Africa, from the growing crop to the roots that reach processors, and is shaped by the farmers and processors who use it.
Three strands, from yield in the field to quality after harvest.
Predicting and improving cassava yields with in-field IoT sensors, drone and satellite imagery, and machine learning. THRIVE is my five-year Royal Academy of Engineering Engineering for Development Research Fellowship, delivered with the partner institutions listed below.
It includes a systematic review of machine learning methods for cassava yield prediction, now in preparation.
A battery-powered handheld RF reflectometer with a probe that estimates the dry matter and starch content of fresh cassava roots, with readings shown in a companion phone app. The device and app are in development, aiming at fast, low-cost quality checks after harvest.
Microwave dielectric sensing to detect adulteration in high-value foods such as honey and olive oil, aimed at a fast screening test that needs no laboratory. Developed with colleagues at UCL; more detail to follow.
How can new electronic systems enhance food security? A short film from UCL Engineering's Disruptive Thinkers series.
Field surveys, farmer training and deployments with growers, processors and partner institutes.
Interviews, news stories and evidence featuring the work.