COVID-19: AI-Enabled Social Distancing Detector Using CNN

K, Anitha Kumari; Purusothaman, P.; Dharani, D.; Padmashani, R.

doi:10.1007/978-3-030-68936-0_6

Cited by 2 publications

(2 citation statements)

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“…Ref. [ 69 ] proposed a social distancing detector using the convolution neural network (CNN), and ref. [ 70 ] proposed a system for the detection and tracking of people to implement social distancing measures by means of a novel deep learning detection technique.…”

Section: Discussionmentioning

confidence: 99%

Healthcare Supply Chain Management under COVID-19 Settings: The Existing Practices in Hong Kong and the United States

et al. 2022

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COVID-19 is recognized as an infectious disease generated by serious acute respiratory syndrome coronavirus 2. COVID-19 has rapidly spread all over the world within a short time period. Due to the coronavirus pandemic transmitting quickly worldwide, the impact on global healthcare systems and healthcare supply chain management has been profound. The COVID-19 outbreak has seriously influenced the routine and daily operations of healthcare facilities and the entire healthcare supply chain management and has brough about a public health crisis. As making sure the availability of healthcare facilities during COVID-19 is crucial, the debate on how to take resilience actions for sustaining healthcare supply chain management has gained new momentum. Apart from the logistics of handling human remains in some countries, supplies within the communities are urgently needed for emergency response. This study focuses on a comprehensive evaluation of the current practices of healthcare supply chain management in Hong Kong and the United States under COVID-19 settings. A wide range of different aspects associated with healthcare supply chain operations are considered, including the best practices for using respirators, transport of life-saving medical supplies, contingency healthcare strategies, blood distribution, and best practices for using disinfectants, as well as human remains handling and logistics. The outcomes of the conducted research identify the existing healthcare supply chain trends in two major Eastern and Western regions of the world, Hong Kong and the United States, and determine the key challenges and propose some strategies that can improve the effectiveness of healthcare supply chain management under COVID-19 settings. The study highlights how to build resilient healthcare supply chain management preparedness for future emergencies.

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Section: Discussionmentioning

confidence: 99%

Healthcare Supply Chain Management under COVID-19 Settings: The Existing Practices in Hong Kong and the United States

et al. 2022

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“…For YOLOv1instance, in Mercaldo, Martinelli, and Santone (2021) , a YOLOv1 object detector is employed to detect people before using Euclidean distance between the people centroid to quantify the distance. Similarly, in Anitha Kumari, Purusothaman, Dharani, and Padmashani (2021) , VSDM approach based on YOLOv1 is developed and implemented on a Jetson Nano computing board. In Mercaldo et al (2021) , the YOLOv1 object detector is employed to detect people before using Euclidean distance metric to quantify the physical distances between people’s centroids.…”

Section: Visual Social Distancing Monitoring (Vsdm)mentioning

confidence: 99%