Emergency Incident Detection from Crowdsourced Waze Data using Bayesian Information Fusion

@article{Senarath2020EmergencyID,
  title={Emergency Incident Detection from Crowdsourced Waze Data using Bayesian Information Fusion},
  author={Yasas Senarath and Saideep Nannapaneni and Hemant Purohit and A. Dubey},
  journal={2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)},
  year={2020},
  pages={187-194}
}
  • Yasas Senarath, S. Nannapaneni, +1 author A. Dubey
  • Published 2020
  • Computer Science
  • 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
The number of emergencies have increased over the years with the growth in urbanization. This pattern has overwhelmed the emergency services with limited resources and demands the optimization of response processes. It is partly due to traditional ‘reactive’ approach of emergency services to collect data about incidents, where a source initiates a call to the emergency number (e.g., 911 in U.S.), delaying and limiting the potentially optimal response. Crowdsourcing platforms such as Waze… Expand
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