Data science of the connected vehicle: perspectives, applications and trends

#News(IoTStack) [ via IoTForIndiaGroup ]

Data of value that can be extracted from the vehicle (assuming presence of the relevant on-board sensors) and potential use-cases are shown in Figure 2 and include:

GPS location and speed. Use cases for this data include real-time congestion reporting and forecasting based on GPS traces.At Intelematics, we employ data from millions of GPS points in Australia to provide a real-time traffic service to drivers in Australia, this is known as the “SUNA Traffic Channel” (http://www.sunatraffic.com.au/).

High-resolution (i.e. > 100 samples per second) vehicle-internal bus voltages including the voltage/current of the car battery during the ignition event (i.e. when the driver turns the key). Use-cases here include predictive models that can forecast battery failure and automate the process involved with offering battery replacements to motorist before the actual battery failure event.

High-resolution accelerometer and gyroscope data, which canbe leveragedto automatically detectaccidents and abnormal driving behaviourswith predictive models that look for patterns that signify a crash and/or other abnormalities.

Vehicle-internal error codes that signify faults (diagnostic trouble codes, DTCs). These can pinpoint individual faults with individual components as well as be aggregated, as part of a classification model, to identify higher-level faults.

Radar sensors and dashboard video cameras that broadcast information about road conditions, parking conditions and road signageback to a central provider for analysis and broadcasting.

Real-time traffic light and road intersection conditions/states (Figure 3). Use-cases here includetraffic light states being broadcast directly into the vehicle and predictive models that forecast traffic light conditionsto maximise the number of cars arriving at intersections when the traffic light is green. In the future, this information could also be fed into autonomous vehicles to optimise both inter- and intra-vehicle coordination.

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