Enabling Human Centric Smart Campuses via Edge Computing and Connected Objects

Monti, Lorenzo (2021) Enabling Human Centric Smart Campuses via Edge Computing and Connected Objects, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Computer science and engineering, 33 Ciclo. DOI 10.6092/unibo/amsdottorato/9606.
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Abstract

Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Monti, Lorenzo
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
33
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Edge Computing, Smart Building, Ubiquitous Computing, HCI, Machine Learning
URN:NBN
DOI
10.6092/unibo/amsdottorato/9606
Data di discussione
22 Marzo 2021
URI

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