Depends on what sort of analysis you want to do (does it have to involve machine learning or will you use stats/data mining/traditional traffic engineering algorithms). Where will the analysis happen? Will it happen on the vehicle IoT device or in a central server?
It shouldn’t be too hard to setup a pipeline that includes nupic (or other tools like scipy/sklearn) if they already have the data.
That said, I’ve got some telemetry data (from OBD (speed, rpm, MAF etc.) joined with GPS, this data will be private for confidentiality reasons). Eventually I’ll probably try to detect anomalous traffic flow in a spatiotemporal sense. ie. if we look at a sequence of telemetry data on a stretch of road(s):
- Is the driving anomalous (in time and space)?
- Does it indicate congestion?
- Does it indicate an incident? (this is hard without more up to date data than I currently have)
- Compare to existing ITS algorithms for congestion/incident detection for probe vehicles
PhD thesis and papers coming soon™