Apart from road construction, infrastructure companies are also responsible for Highway Asset Management, that is,
maintenance of the Highway roads and its assets.
Currently, a very tedious, time consuming, error prone manual Highway analysis is conducted in order to record and maintain the assets.
Takleap’s proprietary AHAMS is a state-of-the-art, video analytics-based machine learning solution.
The software is trained with our proprietary computer vision algorithm that detects and analyses all the assets on the highway.
Ability to compare current videos with the master video assets such as signboards, milestones, etc.
Ability to identify potholes, damaged kerbs etc without the need for comparison
Powerfully trained to work under dim lights to check for street lights, solar blinkers etc.
Visualize data in an easy-to-understand user interface to identify discrepancies.
Detects over 100 assets and counting…
Powerful REAL-TIME processing.
Takeleap's proprietary ML Algorithm analyses data and shows discrepancies in the frequency of asset damage which help in uncovering corruption in road infrastructure
Placement of new assets at the right coordinates saves cost.
Map the assets at the right coordinates.
Takes away the manual process of entering and auditing vast amounts of observational data, thereby reducing time taken to action.
Our solution directly reduces the manpower required by half.
Timely reports are critical in fixing critical elements.
Larsen & Toubro
Government of India
Government of Kazakhstan
Government of UAE