Asset Vision Unveils Revolutionary Autopilot AI to Transform Road Maintenance

In an unprecedented leap forward for municipal infrastructure management, Asset Vision has announced the launch of its latest feature, Autopilot AI. This cutting-edge technology promises to redefine how councils monitor and maintain road networks, utilising sophisticated artificial intelligence to autonomously detect, categorise and report maintenance defects.

In a world where the demands on public infrastructure are growing and the budget constraints are tightening, Asset Vision’s latest feature, Autopilot AI, emerges as a new breakthrough of efficiency and innovation. This new feature, integrated into Asset Vision’s world-renowned Enterprise asset management platform, is set to revolutionise the way local councils approach road maintenance in the future.

How It Works:

Autopilot AI harnesses the power of advanced machine learning algorithms and lidar-enabled high-resolution imaging to continuously survey road networks using a mobile device mounted in the windscreen on municipal vehicles. As these vehicles traverse roadways the cameras capture static images, then the AI scans for a range of defects, including potholes and various types of cracking.

The AI’s deep learning capabilities allow users to identify not only visible defects but also patterns indicative of underlying issues. The capture of regular road images allows road maintainers to intimately monitor the health of their networks and enable a more proactive approach to maintenance rather than reactive ones. 

Key Features:

1. Near Real-Time Defect Detection: Autopilot AI processes the image data as they are uploaded into the AV Platform, enabling immediate notification of maintenance needs. This rapid response capability significantly reduces the time between defect occurrence and remediation, minimising potential hazards for road users, and potential litigation risk for councils.
2. Preventative Scheduling: By analysing trends on historical data, users can more proactively prioritise and address road defects before they become increasingly costly.
3. Automated Reporting: The system automatically generates detailed reports and spatial documentation of detected defects. This automation streamlines workflow and ensures accurate, up-to-date records for operational and budgeting purposes.
4. Seamless Integration: Designed to complement the existing existing EAM platform, Autopilot AI is embedded into Asset Vision’s platform, providing a unified interface for asset management and maintenance planning. Autopilot AI is also able to integrate and complement existing solutions.

Transformative Impact:

The release of Autopilot AI is poised to have a transformative impact on local governments and infrastructure management. Councils can expect to see substantial improvements in road safety and maintenance efficiency, with a significant reduction in manual inspections and human error.

Damian Smith, Co-CEO of Asset Vision, commented on the launch:

“Our mission has always been to empower councils with the tools they need to manage assets effectively. Autopilot AI is a game-changer in this regard. It’s not just about detecting defects; it’s about creating a smarter, more responsive approach to infrastructure management that can adapt to the evolving needs of our communities.”

Looking Ahead:

Asset Vision is currently enhancing AutoPilot to capture LiDAR information accompanying each photo, using the inbuilt hardware available on selected iPhones. With this information we will be able more accurately measure the size of detected defects, as well as their location relative to the road

itself. This approach enables greater defect classification, as we will be able to tell the difference between a defect that is in a traffic lane versus the edge of the road or even on the shoulder, as well as its approximate size in cm. It also enables greater accuracy, as we can disqualify detected defects that are clearly not on the road or shoulder.

Asset Vision is already in discussions with several councils eager to implement Autopilot AI, and we anticipate a wave of interest from those seeking to enhance their infrastructure management practices, save time and precious ratepayer dollars.