This article describes the design and development of a low-cost, portable monitoring system for indoor environment quality (IEQ). IEQ is a holistic concept that encompasses elements of indoor air quality (IAQ), indoor lighting quality (ILQ), acoustic comfort, and thermal comfort (temperature and relative humidity). The unit is intended for the monitoring of temperature, humidity, PM2.5, PM10, total VOCs (×3), CO2, CO, illuminance, and sound levels. Experiments were conducted in various environments, including a typical indoor working environment and outdoor pollution, to evaluate the unit’s potential to monitor IEQ parameters. The developed system was successfully able to monitor parameter variations, based on specific events. A custom IEQ index was devised to rate the parameter readings with a simple scoring system to calculate an overall IEQ percentage. The advantages of the proposed system, with respect to commercial units, is associated with better customisation and flexibility to implement a variety of low-cost sensors. Moreover, low-cost sensor modules reduce the overall cost to provide a comprehensive, portable, and real-time monitoring solution. This development facilities researchers and interested enthusiasts to become engaged and proactive in participating in the study, management, and improvement of IEQ.

The medical profession is becoming ever more interested in the use of gas-phase biomarkers for disease identification and monitoring. This is due in part to its rapid analysis time and low test cost, which makes it attractive for many different clinical arenas. One technology that is showing promise for analyzing these gas-phase biomarkers is the electronic nose—an instrument designed to replicate the biological olfactory system. Of the possible biological media available to “sniff”, urine is becoming ever more important as it is easy to collect and to store for batch testing. However, this raises the question of sample storage shelf-life, even at −80 °C. Here we investigated the effect of storage time (years) on stability and reproducibility of total gas/vapour emissions from urine samples. Urine samples from 87 patients with Type 2 Diabetes Mellitus were collected over a four-year period and stored at −80 °C. These samples were then analyzed using FAIMS (field-asymmetric ion mobility spectrometry—a type of electronic nose). It was discovered that gas emissions (concentration and diversity) reduced over time. However, there was less variation in the initial nine months of storage with greater uniformity and stability of concentrations together with tighter clustering of the total number of chemicals released. This suggests that nine months could be considered a general guide to a sample shelf-life.

The electronic nose (eNose) is an instrument designed to mimic the human olfactory system. Usage of eNose in medical applications is more popular than ever, due to its low costs and non-invasive nature. The eNose sniffs the gases and vapours that emanate from human waste (urine, breath, and stool) for the diagnosis of variety of diseases. Diabetes mellitus type 2 (DM2) affects 8.3% of adults in the world, with 43% being underdiagnosed, resulting in 4.9 million deaths per year. In this study, we investigated the potential of urinary volatile organic compounds (VOCs) as novel non-invasive diagnostic biomarker for diabetes. In addition, we investigated the influence of sample age on the diagnostic accuracy of urinary VOCs. We analysed 140 urine samples (73 DM2, 67 healthy) with Field-Asymmetric Ion Mobility Spectrometry (FAIMS); a type of eNose; and FOX 4000 (AlphaM.O.S, Toulouse, France). Urine samples were collected at UHCW NHS Trust clinics over 4 years and stored at −80 °C within two hours of collection. Four different classifiers were used for classification, specifically Sparse Logistic Regression, Random Forest, Gaussian Process, and Support Vector on both FAIMS and FOX4000. Both eNoses showed their capability of diagnosing DM2 from controls and the effect of sample age on the discrimination. FAIMS samples were analysed for all samples aged 0–4 years (AUC: 88%, sensitivity: 87%, specificity: 82%) and then sub group samples aged less than a year (AUC (Area Under the Curve): 94%, Sensitivity: 92%, specificity: 100%). FOX4000 samples were analysed for all samples aged 0–4 years (AUC: 85%, sensitivity: 77%, specificity: 85%) and a sub group samples aged less than 18 months: (AUC: 94%, sensitivity: 90%, specificity: 89%). We demonstrated that FAIMS and FOX 4000 eNoses can discriminate DM2 from controls using urinary VOCs. In addition, we showed that urine sample age affects discriminative accuracy.