Bialystok University of Technology Develops AGRO-AI System for Farm Machinery Diagnostics

President Karol Nawrocki signed a decree on July 27, 2026, granting Dr. Habil. Eng. Arkadiusz Mystkowski the title of professor of engineering and technical sciences. It formally caps several years of work by the researcher from the Faculty of Electrical Engineering at Bialystok University of Technology on an artificial intelligence system that has been monitoring and diagnosing farm machinery made by Podlasie-based manufacturer SaMASZ.

Mystkowski is a graduate of automation and robotics at Bialystok University of Technology. He earned his doctorate at AGH University of Science and Technology in 2007 and completed his habilitation there eight years later. For years he has headed the Department of Automation and Robotics at the university's Faculty of Electrical Engineering, running projects that combine industrial automation with machine learning, mainly for agricultural and medical applications.

How the AGRO-AI system works

The system, known as AGRO-AI, was developed as part of the broader Agricultural Valley 4.0 concept, an ecosystem of agricultural innovation being built in the Podlaskie region. Its job is to collect data from sensors mounted on farm machinery, covering vibration, temperature, torque and GPS position. The data is sent over a GPRS network to a telemetry platform, where AI algorithms analyze it for early warning signs of failure.

The goal is predictive diagnostics: the system is meant to flag the need to replace oil, gearboxes or bearings before a fault causes a breakdown in the field, which during the harvest season can cost a farmer the most. The solution was tested on tedders and rakes made by SaMASZ, a Bialystok-based company that, according to the university, is among a small handful of manufacturers worldwide capable of producing this type of farm machinery.

University-industry collaboration

AGRO-AI builds on earlier cooperation between Bialystok University of Technology and SaMASZ from 2021-2023, during which the team deployed an autonomous diagnostic system across four types of farm machinery. That solution took third place in the competition run by the Association of Polish Mechanical Engineers and Technicians (Stowarzyszenie Inżynierów i Techników Mechaników Polskich) for Best Technical Achievement of 2023, in the agricultural implementation category. A nine-person team of specialists from the Faculty of Electrical Engineering worked on the project.

Cooperation between industry and the academic community can lead to real and lasting innovation - SaMASZ, in a statement after receiving the Podlaska Marka 2024 award

The Minister of Science and Higher Education award, which Mystkowski received in Torun in February 2025, recognized not only the SaMASZ system but also his other projects, including the DYL-HP Digital Youth Health Platform, developed with partners from Turkey and Belgium under the Erasmus+ program, which uses convolutional neural networks to analyze teenagers' health data. His body of work also includes patents for vibration energy-recovery systems and intelligent vision systems used in industrial automation.

Significance for Polish agriculture

AI deployments in Polish agriculture are still rare compared with the financial or service sectors, and most such projects are limited to large farms or pilots funded by EU grants. The AGRO-AI example shows, however, that a local farm machinery manufacturer and a regional technical university can jointly build and commercialize a predictive maintenance system instead of buying a ready-made solution from a foreign supplier.

For Bialystok University of Technology itself, Mystkowski's professorship is also a signal that regional research centers can build competence in applied artificial intelligence without support from the major hubs in Warsaw or Krakow. The Faculty of Electrical Engineering is running several parallel projects combining automation, machine learning and cooperation with local industry, of which AGRO-AI is so far the most heavily funded and most widely awarded.

The next test for the project will be scaling it beyond the fleet of SaMASZ machines covered by current EU funding, and checking whether predictive diagnostics actually translates into fewer breakdowns during the field season rather than just awards and academic publications.