Abstract
Over the last decade, there has been a quantum leap in terms of the evolution of new methodologies to better our quest to understand artificial intelligence and machine learning. One such field, where there has been an unparalleled advancement, is computer vision. The paper aims to design and structure an automated monitoring system that automates the monitoring of the number of people in this COVID-19 scenario in a designated enclosure. We have deployed the system on Raspberry Pi module and integrated a HOG detector which transcends ordinary Haar cascades in terms of performance. This model can then subsequently be connected and integrated with other modules to further enhance its applicability and spectrum of usage.
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Bandopadhyay, D., Jha, V., Bandyopadhyay, A., Roy, P., Halder, R., Majhi, S. (2022). Automated People Monitoring System Using OpenCV and Raspberry Pi. In: Fong, S., Dey, N., Joshi, A. (eds) ICT Analysis and Applications. Lecture Notes in Networks and Systems, vol 314. Springer, Singapore. https://doi.org/10.1007/978-981-16-5655-2_86
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DOI: https://doi.org/10.1007/978-981-16-5655-2_86
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