The project is implemented within the framework of the Széchenyi Terv Plusz program, with the support of the European Union and co-financed by the Hungarian state.

Implementation location: 2330 Dunaharaszti, Gomba utca 4.

The project is implemented within the framework of the Széchenyi Terv Plusz program, with the support of the European Union and co-financed by the Hungarian state. The aim of the project is to develop a modern, automated, blockchain-based vehicle diagnostic software that uses data management, which provides independent and branded service stations, fleet managers and insurance companies with objective, accurate and efficient diagnostic solutions. The new system brings significant improvements in the field of condition assessments and inspections, minimizing the risks arising from human errors and reducing the time required for diagnostic processes. The central element of the development is the integration of artificial intelligence and IoT technologies, which enable the visual evolutionary diagnostics of vehicle lighting elements (headlights, turn signals, brake lights), chassis, steering, exhaust system and other structural elements.

Through the use of AI-based decision support and IoT tools, inspections can be placed on an objective basis, and the system will be able to identify changes in displacements, wear and corrosion processes over time. The use of blockchain technology ensures the authenticity and immutability of condition assessment data, enabling accurate registration and traceability of the performed inspections. With the help of smart contracts, the system records the results in an automated manner, which creates a reliable basis for insurance companies and fleet managers to make maintenance decisions. Image processing technologies based on artificial intelligence play a particularly important role in detecting changes in the condition of the chassis and body and corrosion.

The system will be able to evaluate vehicle movements while driving and perform safety compliance checks using video-based analysis. Other objectives of the project include alleviating service capacity issues, automating inspection and diagnostic processes, and reducing maintenance and repair costs. Using NLP (Natural Language Processing), the system will be able to identify the causes of errors and recommend repair steps, thereby accelerating decision-making processes. The development will contribute to a longer vehicle lifespan, increased road safety, and the spread of more sustainable vehicle maintenance solutions.

Energotest Diagnostics and Automation Ltd. is implementing the project within the framework of the Digital Renewal Operative Program Plus, a Dedicated R&D&I and market entry support program for digital economy actors – Corporate digital R&D developments, launched by the Ministry of Energy as the Supporter, based on the call for proposals under the identification number DIMOP Plusz-1.1.2/B-24.