Ideal config and how to record rtk gps and pose for each picture taken

We are building a citizen driven urban/transportation planning online multplayer GUI and are building a digital twin for that purpose. ie. SimCity with real world 3D maps.

I took 150 jpeg picture and ran opensfm. The placement of each camera position and pose is way off, so no useful mesh was produced.

We will mount an IMU and RTK GPS tracker on each cam. We like to take picture with dash, side and rear window cameras. I have heard that SFM algorithms like varied position and poses of camera to get better meshes. sice we are a robotics company we can alter the pose of the dash cam as we travel through scanning areas.

We are working on a cross walk study and want to capture high injury network road segments. These will be used as an augmented reality overlay on a closed course test site and a fully virtual test site for each road section to be simulated. see Red lines are highest risk to pedestrians.

I would assume there is someone who has already done this sine 2014 when it appears mapilary started the OpenSfM project.

We can developing AI (GA) and quantum annealer backends to help the public design optimal communities.

The system's digital twin will receive real-time smart iot sensor data feeds for real-time simulation of a wide variety of mobility systems, traffic conditions, zoning related data.

Let me know where I can find the best open source roadway mesh builder. Has anyone built and iterative reconstruction engine that runs continually to update changes and to improve precision?

Here is a programmatically generated personal rapid transit guideway in Forth Worth.

The issue names OpenSfM and a 150-JPEG reconstruction workflow but no repository file, test, or entry point. Clarify the intended RTK/IMU pose-recording and continuous-reconstruction change first; there is currently no defined completion criterion to verify.