Building Smart System by Applied Deep Learning and Spatial Indoor Agent Based Model for a New Adaptation University Learning Process Post Covid-19

Adipandang Yudono, Sapto Wibowo, Christia Meidiana, Surjono Surjono, Irnia Nurika, Erryana Martati and Yan Akhbar Pamungkas

A chapter in Sustainable Smart Cities - A Vision for Tomorrow from IntechOpen

Abstract: The impact of COVID-19 implied various restrictions on people's mobility, especially for the higher education communities, by implementing the Learning from Home approach. This approach has altered the behavior of a human on a daily basis for a year long. Subsequently, the global vaccination program has been the advent of a "New Normal" approach as it reenables the direct human interactions by following health protocols to abide such as social distancing. This study investigated the pedestrian flow in the Department of Urban and Regional Planning (DURP) lecture building, Brawijaya University, and predicted the potential crowd spots using the Integrated Agent-Based Model (ABM), Computer Vision, and the Geographical Information System on an Indoor scale. Additionally, alternative designs of pedestrian flow were proposed to prevent crowds from occurring. The results showed the East and West entrance paths of the DURP building have high traffic, so the proper response is to organize the Southside door as an alternative entrance for pedestrian access. Moreover, the opening of the south gate could reduce the crowd spots on the 2nd Floor of the DURP lecture building.

Keywords: pedestrian flow; social distancing; new normal; agent-based modeling; computer vision; geographical information system (search for similar items in EconPapers)
JEL-codes: Q56 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:276676

DOI: 10.5772/intechopen.106508

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