Precision Agriculture (PA) is an evolving farming management strategy using digital technologies & techniques to monitor and optimise agricultural production processes. PA methods, harnessing data streams from satellites, mobile phones, Internet of Things (IoT) and technologies such as cloud computing and artificial intelligence, have the potential to increase quantity & quality of agricultural outputs while reducing input (water, energy, fertilisers, pesticides, etc.) and waste. One of the main challenges facing PA is a low rate of adoption of PA technologies & practices, especially concerning the “big data in agriculture”. One of the reasons is the lack of skills for executing efficient communication and in turn fuel the adoption rate of the data-driven PA innovations. There is also a need to enhance scientific & technological (S&T) skills for executing sophisticated data analytics on multiscale/multisource agricultural data, addressing all classes of data source, environment/ region/individual farm/individual animals/plants, in order to extract more accurate and impactful actionable information and knowledge from the combined data. DRAGON capacity-building strategy will enable expertise and skill transfer from Agri- EPI Centre, the UK and Wageningen University in the Netherlands to BIOS in order to enhance 1) BIOS’ researchers’ S&T capacity for performing multi-scale/multi-source data analyses; 2) BIOS’ researchers’ capability to communicate practical big data-related knowledge to various stakeholders across the supply chain and the non-scientific local communities. Specifically, this means that BIOS knowledge technologies research group, currently focused on data analytics only (science-driven research), will be enhanced through DRAGON into BIOS Knowledge & Innovation Group (KIG) concentrating on interdisciplinary innovation-driven R&D within a co-creation environment. Post DRAGON BIOS’ KIG will be competitive in the PA sector on European and Global levels.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 810775.