A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring
Цифровой двойник умного кампуса для мониторинга устойчивого комфорта
2020-11-05
SCID: 54.1/a53fwate
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Internet of Thingscomfort monitoringdigital twinsmart campuswireless sensor networks
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Abstract (AI)
Interdisciplinary cross-cultural and cross-organizational research offers great opportunities for innovative breakthroughs in the field of smart cities, yet it also presents organizational and knowledge development hurdles. Smart cities must be large towns able to sustain the needs of their citizens while promoting environmental sustainability. Smart cities foment the widespread use of novel information and communication technologies (ICTs); however, experimenting with these technologies in such a large geographical area is unfeasible. Consequently, smart campuses (SCs), which are universities where technological devices and applications create new experiences or services and facilitate operational efficiency, allow experimentation on a smaller scale, the concept of SCs as a testbed for a smart city is gaining momentum in the research community. Nevertheless, while universities acknowledge the academic role of a smart and sustainable approach to higher education, campus life and other student activities remain a mystery, which have never been universally solved. This paper proposes a SC concept to investigate the integration of building information modeling tools with Internet of Things- (IoT)-based wireless sensor networks in the fields of environmental monitoring and emotion detection to provide insights into the level of comfort. Additionally, it explores the ability of universities to contribute to local sustainability projects by sharing knowledge and experience across a multi-disciplinary team. Preliminary results highlight the significance of monitoring workspaces because productivity has been proven to be directly influenced by environment parameters. The comfort-monitoring infrastructure could also be reused to monitor physical parameters from educational premises to increase energy efficiency.
Key Findings
1
Preliminary results emphasize monitoring workspaces because environmental parameters directly influence productivity.
2
The comfort-monitoring infrastructure can be repurposed to monitor educational facilities and improve energy efficiency.
3
The paper proposes a smart-campus digital twin integrating building information modeling with IoT-based wireless sensor networks.
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The smart campus is presented as a smaller-scale testbed for experimenting with smart-city technologies and supporting local sustainability initiatives through multidisciplinary knowledge sharing.
5
The system monitors environmental conditions and detects emotions to assess occupants’ comfort in campus spaces.
Research Object
Smart campus digital twin integrating Building Information Modeling and IoT-based wireless sensor networks for environmental and emotion monitoring
Research Subject
the integration of environmental-parameter and emotion monitoring to assess occupant comfort and support workspace productivity and energy efficiency
Publication Details
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2020-11-05
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