Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Bari, Italy
Stefan Rilling
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Sankt Augustin, Germany
Arianna Rana
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Bari, Italy
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Bari, Italy
Mark Hoffmann
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Sankt Augustin, Germany
Jacob Livin Stanly
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Sankt Augustin, Germany
Robotic and multi-sensor technologies are increasingly being adopted in a number of agricultural applications, including seeding, weeding, harvesting, fertilization, and crop monitoring and analysis. However, the lack of interoperability and the predominance of manufacturer-specific closed solutions demand a careful choice of devices, sensors and data processing platforms and hinder the flexible adaption of these systems to the individual farmer’s needs and knowledge exchange. The Horizon 2020 Agriculture Interoperability and Analysis System (ATLAS) project is aimed at overcoming these issues through an open, flexible and distributed interoperability network, which enables the seamless interconnection of sensor systems, machines, and data analysis tools. This paper presents the latest achievements in the context of the ATLAS project, concerning the development of robotic services for in-field crop monitoring and their integration into the ATLAS network.
