Agricultural technology and smart farming

By combining expertise in digitalisation, machine learning, robotics, automation, and agricultural science, we aim to enhance productivity, sustainability, and efficiency in both crop and livestock farming. These innovations enable precision tasks such as surveying, 3D scanning, and field operations, while optimizing decision making and reducing environmental impact. By integrating AI, robotics, machine learning and data analytics approaches, our research advances the future of smart farming, reducing environmental impact, and ensuring food security.

  • Focus on modernization of Swedish agriculture through the integration of robotics, artificial intelligence, and advanced data analytics
  • We work on developing cutting edge technologies, including AI driven farm management systems, autonomous agricultural robots, and multi modal data integration techniques using different kinds of sensors
Our expertise

Our research projects integrate AI, machine vision and signal processing techniques, utilizing data analytics and machine learning algorithms to monitor and manage agricultural sectors. We also implement AI-powered data analytics to analyse large quantities of data and predict performance, allowing farmers to make informed decisions and assess potential risks in both crop and livestock farming. By analyzing historical and real time data (e.g., ground based sensors, satellite imagery and drones, cameras) we deploy machine learning models and smart sensing techniques to observe farm conditions, predict future patterns, and suggest farm-based solutions. This approach enhances the efficiency of farming practices, improves productivity, and helps mitigate risks in both crop and livestock management.

Our research in robotics and automation is dedicated to transforming modern agriculture through the development of intelligent systems to enhance efficiency, sustainability, and productivity. As a part of this research area, we design and develop custom autonomous robots to perform a variety of agricultural tasks, including crop monitoring, phenotyping, pest and disease detection and control. We also analyze how autonomous robots can be integrated on farms based on the needs of the robots (such as supply of energy, human supervision) and the needs of the agricultural system (such as precise driving and control of implements).

Contact
  • Abozar Nasirahmadi, Professor of digitalisation in agriculture engineering
    Digitalization
    +4618671879 +46703468176