2018-2020: IoF2020

The IoF2020 project is dedicated to accelerate adoption of IoT for securing sufficient, safe and healthy food and to strengthen competitiveness of farming and food chains in Europe. It will consolidate Europe’s leading position in the global IoT industry by fostering a symbiotic ecosystem of farmers, food industry, technology providers and research institutes.

http://www2.ual.es/IoF2020/

www.iof2020.eu

The heart of the project is formed by 19 use cases grouped in 5 trials with end users from the Arable, Dairy, Fruits, Vegetables and Meat verticals and IoT integrators that will demonstrate the business case of innovative IoT solutions for a large number of application areas. A lean multi-actor approach focusing on user acceptability, stakeholder engagement and sustainable business models will boost technology and market readiness levels and bring end user adoption to the next stage. This development will be enhanced by an open IoT architecture and infrastructure of reusable components based on existing standards and a security and privacy framework.

The reasonable introduction of technology and certification in the production supply chain provides benefits to the different actors and activities, in terms of improved resource use, less waste, better data access and sharing, and enhanced consumer information access.

Smart farming and related technologies have been adopted heterogeneously in the different phases of the supply chain and in different countries. Moreover, new keywords are appearing that seem to solve many problems in the production process, like big data, modeling and prediction technologies, machine learning, deep learning, blockchain, and others, but all of them rely on high quality (sometimes massive) data.

In the Vegetables Trial we are developing and testing IoT solutions for production systems including indoor and city farming, greenhouses, and open-air farming, integrating heterogeneous data sources in different time scales, facing challenges related to the reliability and management/transmission of high volumes of data. It is essential to provide error free and high quality data to the different algorithms (this is where the abovementioned keywords play a role) used to transform these rough data into useful information for reducing farmers’ workload and improving productivity. These solutions are implemented as DSS (Decision Support Systems), Agricultural APPs and web-based systems, into FMIS (Farm Management Information Systems) or following other approaches.

Our Vegetables Trial is closing the gap between data and productivity