A Scoping Review of Technological Approaches to Environmental Monitoring

Indoor environment quality (IEQ) can negatively affect occupant health and wellbeing. Air quality, as well as thermal, visual and auditory conditions, can determine how comfortable occupants feel within buildings. Some can be measured objectively, but many are assessed by interpreting qualitative responses. Continuous monitoring by passive sensors may be useful to identify links between environmental and physiological changes. Few studies localise measurements to an occupant level perhaps due to many environmental monitoring solutions being large and expensive. Traditional models for occupant comfort analysis often exacerbate this by not differentiating between individual building occupants. This scoping review aims to understand IEQ and explore approaches as to how it is measured with various sensing technologies, identifying trends for monitoring occupant health and wellbeing. Twenty-seven studies were reviewed, and more than 60 state-of-the-art and low-cost IEQ sensors identified. Studies were found to focus on the home or workplace, but not both. This review also found how wearable technology could be used to augment IEQ measurements, creating personalised approaches to health and wellbeing. Opportunities exist to make individuals the primary unit of analysis. Future research should explore holistic personalised approaches to health monitoring in buildings that analyse the individual as they move between environments

Personalised Environmental Monitoring of Building Occupants: Integration of Scalable Technologies

Urbanised societies spend most of their time indoor. These are places to conduct habitual activities that impact across the life course and are generating discussions on the built environment and its interplay with health and wellbeing. To understand the effect buildings and their enclosed spaces have on people/occupants, there is a need to monitor Indoor Environmental Quality (IEQ) and occupant responses. State-of-the-art monitoring approaches exist, but they have limited utility outside of bespoke scenarios due to their limited pragmatism and large cost. Other emergent technologies exist but questions remain relating to e.g., validity. Other routine/traditional subjective approaches for evaluating building IEQ often negate to account for the experiences of individual occupants, adding to complications. This thesis explores current monitoring IEQ trends, uncovering the needs to make the individual the unit of analysis. Research undertaken explores contemporary needs and shifting trends to pragmatic approaches, localised sensors to provide richer data that could enable a better understanding of environmental and occupant changes. Quantitative measurement of the environmental conditions local to individuals are explored to understand whether spatial density in monitoring can 1) reinforce data pertaining to how building occupants experience indoor conditions and 2) provide additional context to current approaches for data capture, which traditionally focus on qualitative approaches. Through a series of original research this thesis broadly presents the design and development of a multi-modal IEQ monitoring device and a supporting methodological process for monitoring individuals. It identifies that low-cost multi-modal monitoring deployed longitudinally can add significant context to traditional qualitative approaches, with the individual as the unit of analysis. Findings from the thesis present a paradigm shift that could have practical implications for researchers and practitioners, changing the way building performance is assessed and the way its impact on health and wellbeing could be evaluated

Just find it: The Mymo approach to recommend running shoes

Wearing inappropriate running shoes may lead to unnecessary injury through continued strain upon the lower extremities; potentially damaging a runner’s performance. Many technologies have been developed for accurate shoe recommendation, which centre on running gait analysis. However, these often require supervised use in the laboratory/shop or exhibit too high a cost for personal use. This work addresses the need for a deployable, inexpensive product with the ability to accurately assess running shoe-type recommendation. This was achieved through quantitative analysis of the running gait from 203 individuals through use of a tri-axial accelerometer and tri-axial gyroscope-based wearable (Mymo). In combination with a custom neural network to provide the shoe-type classifications running within the cloud, we experience an accuracy of 94.6 in classifying the correct type of shoe across unseen test data

Low-cost, multimodal environmental monitoring based on the Internet of Things

Monitoring Indoor Environmental Quality (IEQ) is of growing interest for health and wellbeing. New building standards, climate targets and adoption of homeworking strategies are creating needs for scalable, monitoring solutions with onward Cloud connectivity. Low-cost Micro-Electromechanical Systems (MEMS) sensors have potential to address these needs, enabling development of bespoke multimodal devices. Here, we present insights into the development of a MEMS-based Internet of things (IoT) enabled multimodal device for IEQ monitoring. A study was conducted to establish the inter-device variability and validity to reference standard sensors/devices. For the multimodal, IEQ monitor, intraclass correlations and Bland-Altman analyses indicated good inter-sensor reliability and good-to-excellent agreement for most sensors. All low-cost sensors were found to respond to environmental changes. Many sensors reported low accuracy but high precision meaning they could be calibrated against reference sensors to increase accuracy. The multimodal device developed here was identified as being fit-for-purpose, providing general indicators of environmental changes for continuous IEQ monitoring

Towards remote healthcare monitoring using accessible IoT technology: State-of-the-art, insights and experimental design

Healthcare studies are moving toward individualised measurement. There is need to move beyond supervised assessments in the laboratory/clinic. Longitudinal free-living assessment can provide a wealth of information on patient pathology and habitual behaviour, but cost and complexity of equipment have typically been a barrier. Lack of supervised conditions within free-living assessment means there is need to augment these studies with environmental analysis to provide context to individual measurements. This paper reviews low-cost and accessible Internet of Things (IoT) technologies with the aim of informing biomedical engineers of possibilities, workflows and limitations they present. In doing so, we evidence their use within healthcare research through literature and experimentation. As hardware becomes more affordable and feature rich, the cost of data magnifies. This can be limiting for biomedical engineers exploring low-cost solutions as data costs can make IoT approaches unscalable. IoT technologies can be exploited by biomedical engineers, but more research is needed before these technologies can become commonplace for clinicians and healthcare practitioners. It is hoped that the insights provided by this paper will better equip biomedical engineers to lead and monitor multi-disciplinary research investigations

OpenSCAT: Towards the development of an open and extensible digital sports concussion assessment tool to support IoT-based athlete monitoring systems

Athletes that participate in contact sport are at risk of suffering Sports-Related Concussion (SRC). A traditional approach of SRC testing relies on the 5th version of the pen-and-paper based sports concussion assessment tool (SCAT5). An open, digital equivalent may facilitate more efficient and transparent assessment. We describe a co-created developed iOS SCAT5 app to enable an Internet of Things (IoT) assessment

Understanding the scalability of personalised monitoring within indoor spaces

Health and wellness/well-being are multifaceted topics further complicated when trying to understand the environmental impact. Typically, there has been a one size fits all approach when trying to understand the 3-way interaction, but that is a limited approach. Equally, measurement (of each) has often used a limited set of outcomes during short periods to provide insight. A more robust understanding of health and well-being within environments may require longitudinal/continuous assessment that holistically targets individuals. Therefore, there is a growing requirement for careful data management, individual-first methodologies, scalable research designs and new analytical approaches, e.g., artificial intelligence. That presents many challenges but interesting research opportunities for the field of digital medicine

A protocol for longitudinal monitoring of individual building occupants and their environments

Buildings account for approximately 40 of the energy consumption across the European Union, so there is a requirement to strive for better energy performance to reduce the global impact of urbanised societies. However, energy performant buildings can negatively impact building occupants (e.g., comfort, health and/or wellbeing) due to a trade-off between airtightness and air circulation. Thus, there is a need to monitor Indoor Environmental Quality (IEQ) to inform how it impacts occupants and hence redefine value within building performance metrics. An individualised study design would enable researchers to gain new insights into the effects of environmental changes on individuals for more targeted e.g., health interventions or nuanced and improved building design(s). This paper presents a protocol to conduct longitudinal monitoring of an individual and their immediate environment. Additionally, a novel approach to environmental perception gathering is proposed that will monitor environmental factors at an individual level to investigate subjective survey data pertaining to the participant’s perceptions of IEQ (e.g., perceived air quality, thermal conditions, light, and noise). This protocol has the potential to expose time-differential phenomena between environmental changes and an individual’s behavioural and physiological responses. This could be used to support building performance monitoring by providing an interventional assessment of building performance renovations. In the future it could also provide building scientists with a scalable approach for environmental monitoring that focuses specifically on individual health and wellbeing

Diagram of the study setup and passive sensor configuration.

Diagram of the study setup and passive sensor configuration.</p

Variables to be included in dynamic regression model.

Variables to be included in dynamic regression model.</p