AI Road Maintenance Implementation to Reduce CO2 Emissions Case Study

AI Road Maintenance Implementation to Reduce CO2 Emissions: Case Study, in collaboration with state-owned AB Kelių priežiūra and UAV firm Thrust, has pioneered the GreenBee project, a transformative initiative in Lithuania’s national road maintenance.

This case study explores the integration of UAV and Artificial Intelligence to transform the inspection of over 21,000 km of roads, enhancing efficiency and reducing environmental impact.

The Problem with Traditional Road Inspections

Traditionally, road inspections were conducted using manned vehicles that traveled extensively across the road network.

This method was not only time-consuming and inefficient but also had a heavy environmental impact, with significant CO2 emissions resulting from the frequent trips made by inspection vehicles.

Innovative Solutions with UAV and AI Technology

To address these challenges, the GreenBee project utilizes unmanned aerial vehicles (UAVs) equipped with advanced sensors and high-definition cameras.

UAV road inspection
UAV road inspection (Source)

This approach, known as UAV road inspection or AI road inspection, allows for a comprehensive and efficient collection of data from above, without the need for ground vehicles, thereby slashing CO2 emissions by 90%.

By applying our advanced AI and Computer Vision technologies, we can quickly analyze the data captured by UAVs to accurately identify any defects or issues in the road infrastructure.

This method is not only faster but also more precise, minimizing the likelihood of human error and the inconsistencies it can bring.

By rapidly covering large areas and pinpointing areas of potential defects, UAVs and AI analysis will act as a reconnaissance service. This will allow us to efficiently plan manned inspection routes and to dispatch teams to the areas requiring prompt action.
Head of Quality and Technology at AB Kelių priežiūra Jolita Mackienė.

Sustainable and Efficient AI Road Maintenance

AI road inspection results
AI road inspection results (Source)

The use of UAV and AI technology in the GreenBee project represents a significant leap forward in sustainable road maintenance.

By reducing the reliance on manned vehicles, we not only cut down on CO2 emissions but also optimize the use of resources.

This shift allows for more targeted and efficient maintenance efforts, where teams are dispatched only when and where they are most needed, based on accurate AI-driven data analysis.

The length of the EU road network stretches for approximately 5 million kilometers. We estimate that the current road inspection framework requires driving 93,7 million kilometers and committing 3,1 million man-hours every year, with up to 37,5 thousand tons of CO2 emitted into the atmosphere. Employing UAVs for the task cut these emissions by 90%
Head of Business Development at Thrust Gintautas Nedzveckas.

The Future of Road Inspection

The integration of these technologies by in the GreenBee project not only addresses the immediate challenges of traditional road inspection methods but also sets a new standard for the future.

This initiative is a model of how technology can be used to enhance infrastructure management sustainably and efficiently, potentially influencing future practices globally.

AI video analysis is a game-changer in infrastructure inspection. From power lines to gas pipes, solar and wind farms, and other industrial objects, automated inspection frameworks help tackle even the largest projects, which otherwise would not be feasible. In addition, it uniforms the defect spotting process, eliminating the human factors in the process. By reducing costs and improving efficiency, AI analysis is quickly becoming a standard staple in today’s infrastructure diagnostics.
Zygintas-MedonasProduct Development Manager at Žygintas Šitkauskas

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