Event detection and classification for connected car

Moj。moj .io公司是为快速发展的联网汽车行业开发骨干技术的领导者，该公司依赖于连接到车载诊断端口的远程信息处理加密狗收集的信息。除了发动机控制单元提供的信息外，远程信息处理模块还使用少量传感器来提供有关汽车环境和事件检测的感知。Moj。IO一直在寻求仅依靠有限的信息来源来检测玻璃破碎事件的解决方案。他们最初尝试使用一种简单的基于阈值的算法，结果导致了频繁的误报。通过与SFU研究人员的合作，开发了一种改进的算法，仅依靠加速度计提供的数据，就可以可靠地检测到玻璃破碎事件，并将其与类似事件区分开来。提出的研究将建立在我们之前的研究结果的基础上：(i)在Moj.io使用的dongles上实现开发的算法；在donglevel开发信号收集、特征提取和传输算法，尽量减少通信需求；（iii）实现云级事件检测算法，考虑不同汽车中加密狗位置和方向的差异。如果成功，这将为Moj未来几代远程信息处理加密狗的生产奠定基础。Io，具有重要的商业价值。

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.