Collection and Utilization of Indoor Environmental Quality Information Using Affordable Image Sensing Technology

Abstract

Incorporating Internet of Things (IoT) technology into the operation of buildings is expected to generate immense synergy, thereby saving energy and improving occupant comfort by overcoming the limitations of the existing system. Preventing operations in the absence of occupants can save energy, and the occupants’ preferred operating temperature should be used as the control set-point rather than the nominal temperature. In this study, IoT technology and image sensors are used to rapidly detect indoor environment changes, and a method is proposed to utilize air quality and thermal comfort as the control set-points. A real-time ventilation control algorithm is proposed based on the CO2 concentration calculated according to the number of occupants. To check the thermal comfort level, the real-time operating temperature estimated from the surface temperature data of the infrared array sensor is reflected in the comfort zone defined by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). The deficiencies in indoor environment conditions caused by the temporal and spatial lag of sensors in the old system are minimized using IoT technology, which also facilitates wireless communications. The image sensors can be used for multiple purposes based on various interpretations of the image information obtained.

Indoor Environmental Quality (IEQ) and Sustainable Development Goals (SDGs): Technological Advances, Impacts and Challenges in the Management of Healthy and Sustainable Environments

“…Ahn et al [16] note that applying technologies, advanced methodologies, tools and high-performance workstations faces significant challenges, especially related to financial costs. In many places, these approaches are unfeasible due to the primary conditions in which people live in situations of vulnerability, making facilities such as air-conditioning systems inaccessible, for example [10,139,140]. Furthermore, implementing strategies aligned with the SDGs is not trivial, as Luerssen et al highlight [141].…”

“…In this sense, the literature has identified future trends, including integrating the IoT, sensors and High Dynamic Range (HDR) imaging techniques to monitor IEQ parameters [27,102,148] to increase the measurement accuracy. In addition, there is the development of real-time ventilation control algorithms [140], personalized ventilation innovations, sensing and management [104], and the computational analysis of air distribution in the environment employing Computational Fluid Dynamics (CFD) [149] to optimize the ventilation rate and air quality [150,151] and thus reduce the incidence of allergic and infectious diseases and Sick Building Syndrome (SBS), among others [82].…”

Assessing the impact of ventilation systems on indoor air quality: a mock-up experiment in Dubai

“…To investigate the impact of ventilation on improving indoor air quality, the total heat exchange type ventilation system was set to three stages: 0.3, 0.5, and 0.8 times/h (Zhao et al, 2020;Lee et al, 2022). Additionally, three types of ventilation devices were used: total heat exchange type, sensible heat exchange type, and AC type (Choi et al, 2018;Jung and Mahmoud, 2022).…”