Support maintenance decisions in your road network by automatically identifying and assessing assets such as pavement defects, signs, and lane markings condition.
Vaisala's Road Asset Management?combines geospatial videos, driver-made annotations, and computer vision analysis into a highly functional tool to support road maintenance.
Let technology provide a shortcut to assessing your road network by automatically identifying assets such as pavement defects, signs, and lane markings condition. The efficiency in data collection enables?deployment into the maintenance patrolling fleet.
This means that videos, and therefore road condition data, are constantly being updated, enabling engineering teams to make decisions based on the current condition of the network. Data and videos can be shared between teams for a variety of purposes, saving time spent on unnecessary site visits.
Vaisala's Road Asset Management provides AI-powered solutions to the most difficult challenges road authorities and smart cities are facing related to infrastructure management, efficiency of operations, and improving and maintaining roadway safety.
Patrolling teams can record a variety of on-site issues with the integrated steering wheel button, while video collection happens in the background. This means that unnecessary stops can be avoided, bringing higher efficiency but also increasing safety, with the inspector not having to step out of the vehicle. Same-day delivery of videos enables teams to respond to public reports from within the office without visiting a site.
The privacy of data captured by Road Asset Management is ensured by autonomous anonymization of people and vehicles within the imagery. Privacy of the individual is a primary concern of Vaisala, and our computer vision technology has developed to comply with regulations such as EU GDPR by being taught to reliably identify and label people or vehicles.
It is crucial that anonymization provides clear images, leave other valuable data objects untouched, and does not interfere with other computer vision detectable objects; such as traffic signs, cracking or potholes, as the processed visual material is used for simultaneous monitoring of multiple infrastructural elements.
Road Asset Management computer vision technology goes beyond pavement defects. With traffic sign detection and management tools and lane marking condition assessment, it provides improved management of kerb-to-kerb assets. In the future we plan to expand the pavement detection capability from asphalt roads into concrete roads, gravel, footways, and cycle ways.
Combines a user-friendly Artificial Intelligence (AI) tool with high-quality video data and reliable methodology to improve and streamline the pavement inventory and management processes with objective visual assessments.
If you’re interested in giving your inspectors the tools they need to thoroughly and efficiently conduct road asset assessments, start with this eBook. It offers a detailed look at how AI is improving road condition inventory worldwide.
Automated, objective road condition assessment and analysis for safety and efficiency.
A concise look at the challenges and optimal solutions in road maintenance decision-making.
From operational efficiency to greater speed and accuracy, experts weigh in on AI's industry impacts.
A comprehensive overview of modern maintenance technologies and practices.
See how RoadAI was used to improve rural surveys under a difficult budget environment.
See how a typical deployment of RoadAI improves road management in the London borough of Bexley.