Analysis of a smart sensing implementation
This thesis explores the potential of smart sensing technology, notably occupancy rate sensors, as a tool for enhancing efficiency in smart cleaning operations. The focus of this research is on the technology's application within the "Sud America" building of the LaVela campus in Madr...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/394740 |
| Acesso em linha: | https://hdl.handle.net/2117/394740 |
| Access Level: | acceso abierto |
| Palavra-chave: | Internet of things Sensor networks InteInternet de les coses Xarxes de sensors Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica |
| Resumo: | This thesis explores the potential of smart sensing technology, notably occupancy rate sensors, as a tool for enhancing efficiency in smart cleaning operations. The focus of this research is on the technology's application within the "Sud America" building of the LaVela campus in Madrid, Spain, offering a practical use-case for sensor integration. Adopting a mixed-methods research design, this study quantitatively assesses the sensor performance against traditional cleaning methods, while gathering qualitative insights from relevant stakeholders, such as industry experts, cleaning service providers, and facility managers. The dual-approach aids in understanding the reliability, efficiency, and challenges of occupancy rate sensor implementation in the context of smart cleaning operations. The findings of the research underline the substantial benefits of employing occupancy rate sensors in smart cleaning services. These sensors detect the occupancy of spaces, which facilitates strategic planning of cleaning operations. This targeted approach leads to optimal resource utilization, a potential reduction in labor costs, and, consequently, greater user satisfaction. Furthermore, the study shows that the integration of these sensors with Internet of Things (IoT) platforms and data analytics tools can foster the development of intelligent, data-responsive cleaning management systems. These systems hold the promise of enhancing decision-making processes, making them more informed, timely, and effective. Despite the promising prospects, the study identifies potential challenges such as initial investment costs, Staff training, data privacy concerns, and regular sensor maintenance needs. It recommends stakeholder collaboration and heightened awareness about the technology's long-term benefits to counter these challenges and expedite its adoption. In conclusion, the research supports the use of smart sensing technology, particularly occupancy rate sensors, as a transformative tool for smart cleaning operations. By addressing inherent challenges and maximizing opportunities, this technology can pave the way for more efficient and sustainable cleaning practices |
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