Multisensor IoT Platform for Optimising IAQ Levels in Buildings through a Smart Ventilation System

Giacomo Chiesa, Silvia Cesari, Miguel Garcia, Mohammad Issa and Shuyang Li
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Giacomo Chiesa: Department of Architecture and Design, Politecnico di Torino, 10125 Turin, Italy
Silvia Cesari: ICT for Smart Society, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
Miguel Garcia: ICT for Smart Society, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
Mohammad Issa: ICT for Smart Society, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
Shuyang Li: ICT for Smart Society, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy

Sustainability, 2019, vol. 11, issue 20, 1-28

Abstract: Indoor Air Quality (IAQ) issues have a direct impact on the health and comfort of building occupants. In this paper, an experimental low-cost system has been developed to address IAQ issues by using a distributed internet of things platform to control and monitor the indoor environment in building spaces while adopting a data-driven approach. The system is based on several real-time sensor data to model the indoor air quality and accurately control the ventilation system through algorithms to maintain a comfortable level of IAQ by balancing indoor and outdoor pollutant concentrations using the Indoor Air Quality Index approach. This paper describes hardware and software details of the system as well as the algorithms, models, and control strategies of the proposed solution which can be integrated in detached ventilation systems. Furthermore, a mobile app has been developed to inform, in real time, different-expertise-user profiles showing indoor and outdoor IAQ conditions. The system is implemented in a small prototype box and early-validated with different test cases considering various pollutant concentrations, reaching a Technology Readiness Level (TRL) of 3–4.

Keywords: indoor air quality index; smart ventilation; IoT; microservice; mobile app; fan-assisted ventilation; indoor air quality (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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