ProvEye is a UCD spin-out company that enables quantitative prediction of agricultural behaviour through our unique state-of-the-art image correction methods.
We can measure properties of land over wide areas that we use to make predictions about farming activity and outcomes, which we can ultimately interpret as behaviour. Optical sensing data are valuable for the digital transformation of agriculture, but the value of such data is limited by quality due to noise masking the important signal during data collection (e.g. UAV missions, satellite overpass or vehicle activity in the field). Poor quality data limits the value of AI and ML tools for digital agriculture. ProvEye has solved the problem of poor-quality images by developing an automatable, consistently reproducible image correction methodology that can be combined with predictive models and embedded in an end-to-end solution for quantitative prediction of agricultural behaviour.
By solving the technical challenge of taking noisy optical image data collected by drones, vehicle mounted sensors and satellites we can extract the important clean signal that can then be used for quantitative modelling and prediction for our B2B customers - who are businesses trading information services to farmers e.g. companies selling inputs, agronomic services and precision agriculture services. This allows for decision support services that can broaden and deepen their own clients experience.
Our B2B customers collect and use data about their clients’ farms or farms in a region, so their services are only as good as the data they collect. The problem of ‘rubbish in, rubbish out’ (RIRO) has never been truer in the age of digital agriculture. The use of wide-area image services (satellite remote sensing, drone imaging, vehicle mounted cameras) is a huge market opportunity for our customers, but its value is not currently being realised because the data collected from images is of poor quality for quantitative analysis, modelling and prediction. Our customers have access to high resolution image data but cannot use it to fully serve their own clients. The can only offer limited services because the data is not consistent and reliable. The ProvEye sensing solution allows a quantitative approach and the ProvEye predictive products convert the “new” quality data into meaningful information (e.g. crop yield and crop quality), enabling reliable prediction of required farm activity and ultimately agricultural behaviour.
ProvEye was cofounded by Tim Buckley (an EI Business Partner), Dr Jerome O’Connell and Professor Nick Holden who are CEO, CTO and Executive Director respectively.