Fraunhofer Center for Assistive Information and Communication Solutions – AICOS
12.04.2022
Digital farming, sensing platform, Computer Vision, rural Africa and small-scale farmers. These concepts may easily sum up Project AFRICA, a three-year project which combined the knowledge and expertise from several renowned institutions: Technische Universiteit Eindhoven (TU/e), Nelson Mandela Metropolitan University (NMMU), University of Cape Coast, Evonik Industries, and the Fraunhofer Portugal AICOS research center (FhP-AICOS).
With profound skills and know-how on such research topics as Digital Farming and Cognitive Connected Solutions, FhP-AICOS’ participation in the project consisted of the development of an IoT sensing platform with the goal of supporting a green-energy driven technology solution to allow the on-site, cost-affordable fertiliser production to small-scale farmers in Africa. Thus, reducing the yield gap these farmers experience due to the difficult access (i.e., their low income, high prices) to fertilizers.
Along with Computer Vision techniques, the developed Internet of Things (IoT) sensing platform provides information on the state of the soil and surrounding environment in terms of pH, moisture, texture, colour, air temperature, and light. Moreover, the platform hardware is housed in a specifically designed robust 3D-printed prototype to allow easy assembly, transport, and protection from the deployment environment. Besides the controlled, in-lab environment testing, the solution was also piloted in real work environment in South Africa.
Since most farmers, especially in rural Africa, are not acquainted with technology, and in order to introduce digital farming in such areas, this ICT solution was developed always bearing in mind its viability and easiness of use. To achieve requirements of usability and reproducibility, the architecture of the IoT sensing platform was based on low-cost, off-the-shelf hardware and software modularity, following a do-it-yourself approach to support its further extension (e.g., adding new sensing capability).