2021
IJCAI
IJCAI 2021
Predictive Analytics for COVID-19 Social Distancing
Abstract
The COVID-19 pandemic has disrupted the lives of millions across the globe. In Singapore, promoting safe distancing by managing crowds in public areas have been the cornerstone of containing the community spread of the virus. One of the most important solutions to maintain social distancing is to monitor the crowdedness of indoor and outdoor points of interest. Using Nanyang Technological University (NTU) as a testbed, we develop and deploy a platform that provides live and predicted crowd counts for key locations on campus to help users plan their trips in an informed manner, so as to mitigate the risk of community transmission.
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Interdisciplinary Bridge
— Artificial Intelligence and Data Science & Analytics and Machine Learning
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Keyword Pioneer
— crowd prediction
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy
Authors
Topics
Artificial Intelligence > Core AI > Planning
Machine Learning > Core Methods > Regression
Machine Learning > Application Areas > Risk Management
Data Science & Analytics > Applications > Mobility Analysis
Data Science & Analytics > Applications > Disease Surveillance
Machine Learning > Core Methods > Prediction