The Indoor Environmental Quality (IEQ) combines thermal, visual, acoustic, and air-quality conditions in indoor environments and affects occupants’ health, well-being, and comfort. Performing continuous monitoring to assess IEQ is increasingly proving to be important, also due to the large amount of time that people spend in closed spaces. In the present study, the design, development, and metrological characterization of a low-cost multi-sensor device is presented. The device is part of a wider system, hereafter referred to as PROMET&O (PROactive Monitoring for indoor EnvironmenTal quality & cOmfort), that also includes a questionnaire for the collection of occupants’ feedback on comfort perception and a dashboard to show end users all monitored data. The PROMET&O multi-sensor monitors the quality conditions of indoor environments thanks to a set of low-cost sensors that measure air temperature, relative humidity, illuminance, sound pressure level, carbon monoxide, carbon dioxide, nitrogen dioxide, particulate matter, volatile organic compounds, and formaldehyde. The device architecture is described, and the design criteria related to measurement requirements are highlighted. Particular attention is paid to the calibration of the device to ensure the metrological traceability of the measurements. Calibration procedures, based on the comparison to reference standards and following commonly employed or ad hoc developed technical procedures, were defined and applied to the bare sensors of air temperature and relative humidity, carbon dioxide, illuminance, sound pressure level, particulate matter, and formaldehyde. The next calibration phase in the laboratory will be aimed at analyzing the mutual influences of the assembled multi-sensor hardware components and refining the calibration functions.

Today, building design focuses on optimizing indoor environmental quality (IEQ) and ensuring the comfort and well-being of occupants. In this context, a continuous monitoring infrastructure can provide the necessary data to ensure that the environment adapts proactively and in real-time to the occupants’ needs. This approach, applied in a research context, requires the simultaneous monitoring of three levels of measurement: objective-environmental parameters, using lab-grade instruments in the environment and wearable devices; subjective-psychological parameters, obtained through questionnaires and cognitive tasks; and physiological parameters, gathered via wearable devices. This paper presents a 3-layer monitoring infrastructure and its first demonstration use case, conducted in Politecnico di Torino for two weeks in March 2025. The aim is to investigate whether wearable sensors can provide objective insights into a deeper understanding of the relationship between IEQ and occupants’ comfort and well-being. Some preliminary findings are discussed, along with a review of the state of the art in wearable technologies across the four environmental domains, and the rationale behind the selection of specific devices.

This paper presents the metrological characterization of low-cost sensors integrated into a multi-sensor system for Indoor Environmental Quality monitoring, developed within the MIRABLE project. The analysis focuses on two domains: the thermal domain, using Sensirion SHT45 and SEN55 temperature sensors; and the Indoor Air Quality (IAQ) domain, using an Infineon photoacoustic spectroscopy (PAS)-based sensor for carbon dioxide (CO₂). All tests were conducted under controlled laboratory conditions using calibrated reference instruments. In the thermal domain, the influence of sensor integration within the device case was investigated at temperature (T) between 15 °C and 35 °C and relative humidities (RH) between 30 %rh and 60 %rh. The results revealed self-heating effects in the desk unit, causing temperature biases of up to 0.6 °C. In the IAQ domain, the repeatability and the impact of T and RH on CO₂ measurements were evaluated. T was identified as the main influencing factor; whereas, RH had a negligible effect. These results were supported by statistical analysis ANOVA. A correction strategy based on concentration intervals is proposed for operation between 15 °C and 25 °C, with an expanded uncertainty (k = 2) of (3.26–6.42) ppm for the with-case configuration. These results support the reliable use of the MIRABLE system.