At imajing, the problem was handled differently. Instead of accumulating various separate data sources to have each one serving a single need, we have tried to minimize the data volume and optimize the use of each element in order to leverage them with the other parts. We believe it is more efficient and practical. For example, on the imajbox® mobile mapping system, we use the camera sensor to generate a new source of relative orientation that is integrated in the navigation kalman filtering to improve GNSS/IMU solutions.
From our RGB sensor, we not only provide fancy images, but we also calculate the depth with different techniques (feature tracking, correlation, AI) to deliver information at the smallest computing cost according to the needs, while minimizing data storage.
From a practical standpoint, being able to easily handle the system and move it onto any car, truck or train rapidly is the key to reactivity. It also helps to reduce overhead and logistics costs and allows anyone to run a survey by themselves. This is made possible by the size and weight of imajing’s mobile mapping technology. Doing measurements from images is also a benefit because it allows us to work from behind a windshield, which can’t be done with lidar.
The imajbox® mobile mapping technology integrates all of these concepts and delivers the information needed on a very large scale, at a minimized operational, computing and storage cost. As a consequence, running regular surveys becomes affordable when using imajing mobile mapping technologies, enabling new approaches in network monitoring and change detection.
