Smart workplaces: a system proposal for stress management

Over the past last decades of contemporary society, workplaces have become the primary source of many health issues, leading to mental problems such as stress, depression, and anxiety. Among the others, environmental aspects have shown to be the causes of stress, illness, and lack of productivity. With the arrival of new technologies, especially in the smart workplaces field, most studies have focused on investigating the building energy efficiency models and human thermal comfort. However, little has been applied to occupants’ stress recognition and well-being overall. Due to this fact, this present study aims to propose a stress management solution for an interactive design system that allows the adapting of comfortable environmental conditions according to the user preferences by measuring in real-time the environmental and biological characteristics, thereby helping to prevent stress, as well as to enable users to cope stress when being stressed. The secondary objective will focus on evaluating one part of the system: the mobile application. The proposed system uses several usability methods to identify users’ needs, behavior, and expectations from the user-centered design approach. Applied methods, such as User Research, Card Sorting, and Expert Review, allowed us to evaluate the design system according to Heuristics Analysis, resulting in improved usability of interfaces and experience. The study presents the research results, the design interface, and usability tests. According to the User Research results, temperature and noise are the most common environmental stressors among the users causing stress and uncomfortable conditions to work in, and the preference for physical activities over the digital solutions for coping with stress. Additionally, the System Usability Scale (SUS) results identified that the system’s usability was measured as “excellent” and “acceptable” with a final score of 88 points out of the 100. It is expected that these conclusions can contribute to future investigations in the smart workplaces study field and their interaction with the people placed there.Nas últimas décadas da sociedade contemporânea, o local de trabalho tem se tornado principal fonte de muitos problemas de saúde mental, como o stress, depressão e ansiedade. Os aspetos ambientais têm se revelado como as causas de stress, doenças, falta de produtividade, entre outros. Atualmente, com a chegada de novas tecnologias, principalmente na área de locais de trabalho inteligentes, a maioria dos estudos tem se concentrado na investigação de modelos de eficiência energética de edifícios e conforto térmico humano. No entanto, pouco foi aplicado ao reconhecimento do stress dos ocupantes e ao bem-estar geral das pessoas. Diante disso, o objetivo principal é propor um sistema de design de gestão do stress para um sistema de design interativo que permita adaptar as condições ambientais de acordo com as preferências de utilizador, medindo em tempo real as características ambientais e biológicas, auxiliando assim na prevenção de stress, bem como ajuda os utilizadores a lidar com o stress quando estão sob o mesmo. O segundo objetivo é desenhar e avaliar uma parte do projeto — o protótipo da aplicação móvel através da realização de testes de usabilidade. O sistema proposto resulta da abordagem de design centrado no utilizador, utilizando diversos métodos de usabilidade para identificar as necessidades, comportamentos e as expectativas dos utilizadores. Métodos aplicados, como Pesquisa de Usuário, Card Sorting e Revisão de Especialistas, permitiram avaliar o sistema de design de acordo com a análise heurística, resultando numa melhoria na usabilidade das interfaces e experiência. O estudo apresenta os resultados da pesquisa, a interface do design e os testes de usabilidade. De acordo com os resultados de User Research, a temperatura e o ruído são os stressores ambientais mais comuns entre os utilizadores, causando stresse e condições menos favoráveis para trabalhar, igualmente existe uma preferência por atividades físicas sobre as soluções digitais na gestão do stresse. Adicionalmente, os resultados de System Usability Scale (SUS) identificaram a usabilidade do sistema de design como “excelente” e “aceitável” com pontuação final de 88 pontos em 100. É esperado que essas conclusões possam contribuir para futuras investigações no campo de estudo dos smart workplaces e sua interação com os utilizadores

Enabling Thermally Adaptive and Sustainable Built Environments through Sensing and Modeling of Human-Building Interactions

Fundamental interactions between buildings and their occupants have a multitude of significant impacts. First, built environments critically affect occupants’ health and wellness, especially given that people spend more than 90% of time indoors. Among several environmental factors, the lack of thermal comfort is a common problem despite nearly half of the building energy being consumed by heating, ventilation, and air conditioning (HVAC) systems. Humans, in turn, closely influence the sustainable operation of buildings through various occupant energy-use behaviors. Recent studies indicate that actions performed or abstained by occupants have a major influence on building energy performance and can negate the benefits of investing in energy-efficient building systems. This dissertation focused on these two primary interplays of human-building interactions. First, uncertainties in occupants’ thermal comfort due to the varying human physiological, psychological, and behavioral factors lead to significant thermal dissatisfaction and often result in sick building syndrome. A potential solution is the human-in-the-loop approach to sense thermal comfort and provide more personalized environments. However, existing comfort assessing approaches have several key limitations including the need for continuous human input to adjust setpoints, lack of actionable human data in comfort prediction, intrusiveness and privacy concerns, and difficulty in integrating within HVAC operations. To address these issues, this research first investigated the integration of environmental data with human bio-signals collected from wristbands and smartphones for thermal comfort prediction and achieved 85% classification accuracy. This approach however required humans to provide their information from wearable devices and respond to a polling app. To address these limitations, the research further explored low-cost infrared thermal camera networks to non-intrusively collect facial skin temperature for real-time comfort assessment in both single and multi-occupancy spaces. Similar prediction accuracy is achieved without using any personal devices. Building on these comfort sensing approaches, this dissertation demonstrates how to bridge personal comfort models and physiological predictive models to determine optimum setpoints for improved overall satisfaction or reduced energy use while maintaining comfort. The proposed sensing and optimization methods can serve as a basis for automated environment control to improve human experience and well-being. The second part of this research addressed why behavior interventions result in different energy reduction rates and identified two important gaps: lack of fundamental understanding of behavioral determinants of occupants, and lack of methods to quantitatively describe the varying occupant characteristics which affect the effectiveness of interventions. To address these gaps, the research developed a conceptual framework which explains occupant behaviors with three determining factors - motivation, opportunity, and ability (MOA) incorporating insights from building science and social psychology. Based on MOA levels, clustering analysis and agent-based modeling were applied to classify occupancy characteristics and evaluate the effectiveness of a chosen intervention. The framework was improved by integrating MOA factors with two classical behavioral theories to address the challenges in defining and measuring MOA factors. The results showed an improved explanatory power over a single theory and suggested that favorable behaviors can be promoted by motivating occupants, removing environmental constraints, and improving occupants’ abilities. This framework enables decision-makers to develop effective and economical interventions to solicit behavioral change and achieve building efficiency. Building upon these two perspectives of human-building interactions, future studies can investigate how personalized thermal environments will improve occupant behaviors in interacting with HVAC systems and the corresponding impacts on building energy consumption.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153410/1/dliseren_1.pd