DSDCS: Detection of Safe Driving via Crowd Sensing


Traffic safety plays an important role in smart transportation, and it has become a social issue worthy of attention. For detection of safe driving, we focus on the collection, processing, distribution, exchange, analysis and utilization of information, and aim at providing diverse services for drivers and passengers. By adopting crowdsourcing and crowd-sensing, we monitor the extreme driving behavior during the process of driving, trying to reduce the probability of traffic accidents. The smartphones are carried by passengers, which can sense the driving state of the vehicles with our proposed incentive mechanism. After the data is integrated, we are able to monitor the driving behavior more accurately, and finally secure the public transit. Finally, we developed a safe driving App for monitoring and evaluation.

16th International Conference on Advanced Data Mining and Applications

This work is supported by National Natural Science Foundation of China (61672284, 41301407), Funding of Security Ability Construction of Civil Aviation Administration of China (AS-SA2015/21), Fundamental Research Funds for the Central Universities (NJ20160028, NT2018028, NS2018057).