WreckWatch: Automatic Traffic Accident Detection and Notification with Smartphones
By Jules White, C. Thompson, Hamilton A. Turner, Brian Dougherty, D. Schmidt. Mob. Networks Appl., 2011
369 citations recorded by the source corpus.
Subfields: Building and Construction, Mechanical Engineering, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/9d033b54f7b5278952a3c6e0aa4d9f4b08e3030d
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In Building and Construction
Citations in the corpus
- A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities (2019, background): “Relay is typically employed for real-time monitoring, such as traffic conditions [20], [140], [141], [143], or price comparison [130], [131].”
- A Survey on Platoon-Based Vehicular Cyber-Physical Systems (2016, background): “road travel times estimation by the aid of mobile phones and the traffic accident detection [40] by leveraging accelerometers and acoustic data on mobile phones.”
- A deep learning approach for detecting traffic accidents from social media data (2018, methodology): “The location effectiveness and timeliness features of Twitter can be proved in a recent accident detection study that uses the GPS-enabled smartphones (White et al., 2011) and travel behavior study which has been validated by the household travel survey (Zhang et al., 2017).”