Every year, a significant budget is allocated and spent on road repair and maintenance due to cracks and damages on roads as well as lack of an efficient and systematic management system. This solution is to create a car-free map with deep learning. Such a technique is based on a Drone-to-Mapper platform that removes labeled entities on the road by emerging original images with the machine-learning processed images. Then the orientation of the shadows to calculate shadow vector using Structure from Motion algorithm is analyzed. The severity of the defects such as potholes and cracks for future adjustments are accounted for.
This solution can be used as the main support by intervention or maintenance teams to go address an issue on-site. The vehicle-free road map can be marketed to transport/land ministries or government agencies, expressway corporations, local governments, and etc. Also, the crack,pothole safe maps could be used for autonomous vehicles, portals, and insurance companies.
TECHNOLOGY FEATURES & SPECIFICATIONS
The process overall serves to determine the number of vehicles present on a given site and also has significant importance for detecting intrusions via ML. It will get the orthomosaic of the surveyed zone in tiles and a vector file displaying the detected vehicles and their type as well as a summary table. AI and Deep Learning technologies are used for creating a vehicle-free road map. Drones and spatial information technologies help create crack, pothole safe map for roads and facilities repair and maintenance data.
It is possible to acquire road data more efficiently compared to traditional methods. Previously, surveyors not only had to buy high-end Mobile Mapping System sensor that costs up to a million dollars but also face the limitation of the lane to lane analysis. However, the situation is changed via a drone survey. The data gathered from drones can be used to create surface-level road information, and, even more so, advanced road information for High Definition Safety (HDS) map. This new technology can take pictures of and analyze 8 lanes or more at one time, with less than 1 centimeter of the margin of error. It only takes 25 minutes to process 1 kilometer of road, a huge cut from the time consumed by other previous methods. It is able to acquire a complete road survey that uses drones possible in the sampling survey of roads by existing personnel.
AV/CAV: Acquisition of simulation data and application of actual road data for driving of autonomous vehicles.
Road Repair and Maintenance: by effectively removing the vehicles and on-road noises.
Total Drone Solution
Application to various industries: incorporating drones into vertical infrastructure operations, property inspection, panorama 360º VR and 2D/3D Mapping, precision agriculture, and so on
Drone solutions to deliver cost-effective data to various customers. It aims to help customers avoid the capital expenses and operating risks of establishing their own drone programs and to purchase drone support in a way that better fits their operations and cost profiles. With the industry experiences, it understands customer requirements and deploys the right drones, sensors, and data solutions. It can offer a range of services to fit customer needs.