Event detection and classification for connected car

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Moj.io Inc. is a leader in developing backbone technologies for the rapidly growing connected car industry.Moj.io relies on information collected by a telematics dongle that is connected to the on-board diagnostic portof a car. In addition to the information provided by the engine control unit, the telematics module uses a smallnumber of sensors to provide awareness regarding the car ambient and event detection. Moj.io has beenseeking solutions to detect the glass-breakage event relying only on the limited sources of information. Theirinitial attempts on a simple threshold-based algorithm led to frequent false-positive alarms. Throughcollaborations with the SFU researchers, a modified algorithm was developed that relying on only the dataavailable from accelerometers, the glass breakage event could be reliably detected and distinguished fromsimilar events.The proposed research will build on our earlier results to (i) Implement the developed algorithm on the donglesused by Moj.io; (ii) Develop signal collection, feature extraction, and transmission algorithms at the donglelevel to minimize communication requirements; and (iii) Implement cloud-level event detection algorithmswhich to consider differences between dongle location and orientation in different cars.If successful, this will form the basis for manufacturing of future generations of telematics dongles for Moj.io,with significant commercial importance.