Driver’s State Monitoring: A Case Study on Big Data Analytics

摘要: Driver’s distraction, inattention, sleepiness, stress, etc. are identified as causal factors of vehicle crashes and accidents. Today, we know that physiological signals convenient reliable measures driver’s impairments. Heterogeneous sensors generating vast amount signals, which need to be handled analyzed in a big data scenario. Here, propose analytics approach for driver state monitoring using heterogeneous coming from multiple sources, i.e., along with vehicular contextual information. These processed aware impaired drivers.