Implementing AI in Road Maintenance to Lower CO2 Emissions

Summary: The AI solution optimized routing for road maintenance vehicles to ensure minimal travel distances, thus reducing fuel consumption and emissions by 90%.

Client:  AB Kelių priežiūra

Problem Statement: 

Road inspections usually relied on manned vehicles that covered large sections of the road network. This approach is not only labor-intensive and inefficient but also has a considerable environmental impact, as frequent trips by these vehicles led to high CO2 emissions.

AB Kelių priežiūra, Lithuania’s state-owned company responsible for road maintenance and repair, sought to modernize its approach to road maintenance. The organization aimed to reduce carbon emissions, optimize resource allocation, and increase overall efficiency. With a growing focus on sustainable infrastructure, AB Kelių priežiūra turned to EasyFlow.tech, an AI-based technology provider, to implement a solution for predictive road maintenance that would minimize environmental impact.

Results: 

• Reducing CO2 emissions by 90%.
• Enhancing resource utilization.
• Streamlining maintenance efforts for greater precision and efficiency.

AI Solution Overview:

EasyFlow.tech, together with the state-owned road maintenance company AB Kelių priežiūra and UAV provider Thrust, has launched the GreenBee project, an initiative for road maintenance in Lithuania. 

The GreenBee project uses unmanned aerial vehicles (UAVs) equipped with sophisticated sensors and high-resolution cameras to tackle challenges in road upkeep. This UAV-based road inspection method enables thorough and efficient data collection from the air, eliminating the need for traditional ground vehicles.

With advanced AI and Computer Vision capabilities, EasyFlow.tech quickly processes UAV-captured data to pinpoint road infrastructure issues accurately. This approach not only speeds up inspections but also improves precision, reducing human errors and inconsistencies.

GreenBee’s use of UAV and AI technologies marks a major advancement in sustainable road maintenance. By relying on accurate, AI-driven analysis, maintenance teams can be deployed more strategically—ensuring they are sent exactly when and where needed. 

References: 

1. AI Road Maintenance Implementation to Reduce CO2 Emissions: Case Study. https://easyflow.tech/ai-road-maintenance/ 

Industry: Road Maintenance

Vendor: EasyFlow.tech

Client: AB Kelių priežiūra

Publication Date: 2024