The value of image data in road maintenance and infrastructure maintenance is evident. We have listed some of the main benefits that good quality and systematically collected comparable data over time have for road authorities, road maintenance contractors and consultants.
Good quality images can reveal defects on roads such as cracks, potholes and other possible forms of damage on the road surface and road side assets. Artificial Intelligence (AI) and Machine Learning (ML) can be utilized to help in analyzing and processing images and identifying areas that require maintenance or repair. It is good to remember that trusting solely on AI in making analysis can lead to wrong conclusions. AI is nevertheless of good help for road maintenance professionals to evaluate the need of maintenance activities. The systematic collection of image data over time allows for proactive maintenance strategies. By tracking changes in road conditions through images, maintenance teams can predict potential issues before they escalate, ultimately saving costs and preventing major road failures. This approach not only improves the safety of all road users but also ensures the longevity of our road infrastructure.
When utilizing image data for quality and maintenance purposes, it is extremely important to systematically collect image data for tracking changes over time. This, at it´s best, helps maintenance teams to predict potential issues ahead. Scheduling preventive maintenance tasks is then possible and will save costs, prevents major road failures and adds to safety of all road users. Incorporating image data into asset management processes is also beneficial. Images can be utilized to create detailed inventories of assets such as signs, streetlights, and road markings, facilitating effective maintenance planning. Additionally, AI can aid in analyzing asset conditions and determining maintenance needs, further optimizing asset management practices.
Images are often used to create an inventory of assets found on roads, including signs, streetlights, road markings and other valuable resources. Also in this purpose images are used for effective maintenance of the assets. AI could be of good assistance in analyzing asset conditions and maintenance needs.
The need for manual and remote inspections are reduced due to good quality image data available. Images allow broad coverage of road network inspections in shorter time than manually doing inspections. It boosts efficiency by reducing the need for manual inspections but also enhances safety by identifying potential defects early. By archiving systematically collected images for future reference and analysis, road authorities can conduct longitudinal studies of road conditions and track the impact of maintenance work over time.
When identifying and paying attention to potential road defects early, image data helps in preventing accidents thus improving road safety. Also, the work phases of designing, planning and inspectioning gets safer due to the fact of not needing frequent visits on remote road locations when good quality images are available digitally.
When capturing image data systematically and utilizing it for before and after purposes, it will enable more cost-effective way to manage and maintain roads compared to labor intensive methods. Fewer on-site personnel are needed and images allow also quicker analysis of the road conditions identifying potential defects that would require immediate action.
Systematically collected images over time should be archived for later use for analysis purposes. That will help in use of future reference and in conducting longitudinal studies of road conditions. The use of before and after images is a powerful way of identifying potential defects on roads but also quality improvements after road maintenance work carried out by contractors.
As a conclusion, it is easy to state that image data is very helpful and useful in road maintenance, but also in other infrastructure maintenance environments. Systematic collection of images for road maintenance purposes and other infrastructure management purposes are vital. This enables improved safety of road staff and road users, but adds also to efficiency and cost effectiveness.
Autori provide tools for managing image data (Vista image viewer) for quality assurance and initial data capturing for road maintenance contract management purposes. We have experience in road image data collection and management in 10 different countries. Overall, Autori platform provides unique solutions for road maintenance and other infrastructure maintenance enabling visual, powerful work, quality and asset management.
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