Abstract—The current COVID-19 pandemic has elevated the importance of cleanliness and social distancing. These needs will continue to be important as the world moves to a new normal whilst navigating through a post-covid environment. This paper presents a use case application that focuses on enforcing safe distance measures inside a campus building where there is limited manpower resources. Amidst the social setting within the university, staff or students may at times accidentally congregate, w hich may lead to spread of diseases inconveniencing all affected parties. Our proposed integrated solution consists of a network of video cameras and sensors which allows one to monitor behavior within  the building. The i ntegrated smart devices communicate with (1) an analytics server that processes the data from the various sensors and (2) a platform that integrates the analytic results and optimizes the action items to be reflected to the environment. A pilot prototype has been deployed and evaluated within a living lab setting on campus. Results show that the system is useful in streamlining the operational process resulting in more efficient processes and procedures to help enforce safe management measures needed to maintain  proper social distancing among occupants in campus.   
 

Index Terms—video analytics, internet of things, sensors, crowd detection 
 

Cite: Donny Soh Cheng Lock, Indriyati Atmosukarto, Arthur Loo Wee Yeong, Selvakulasingam Thirunneepan, Toshiki Ishii, Rishabh Ranjan, Shuyang Dou, and Junichi Hirayama, "Improving Operational Processes for COVID-19 Ready Smart Campus," Journal of Advances in Information Technology, Vol. 13, No. 6, pp. 597-603, December 2022.

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