Wearable Biosensor and Hotspot Analysis–Based Framework to Detect Stress Hotspots for Advancing Elderly’s Mobility

Use of Connected Technologies to Assess Barriers and Stressors for Age and Disability-Friendly Communities

“…In general, the gait pattern has been shown to correlate with physical barriers of urban built environments such as sidewalk defects, curbs, slopes, and holes ( 19 – 23 , 43 – 52 ) (See Table 1 ). Signals, such as electrodermal activity ( 18 , 21 – 25 , 27 – 31 , 36 – 42 ), electrocardiography or photoplethysmography ( 18 , 20 – 23 , 28 , 36 – 40 , 52 , 53 ) and brain activity ( 26 , 32 , 40 , 54 , 55 ), have been separately used to understand psychological states toward stressors in relation to negative environmental stimuli (e.g., broken houses, barking dogs, and steep stairs) and the mood of walking paths such as urban busy and quiet areas ( 23 , 30 – 32 ). Despite the premise and potential of ambulatory monitoring approaches to overcome the subjectivity related to traditional approaches (e.g., self-reporting and surveys), physiological data collected in real-life environments are confounded by various factors (e.g., weather conditions, physical movement, and the discomfort of wearing sensors) ( 20 , 23 – 27 ).…”

City Digital Twin Potentials: A Review and Research Agenda

“…In data management, for instance, one of the biggest concerns is the large-sized, complex, and heterogeneous nature of the city data [13,33,35,39,59]. In light of that, data acquisition and processing are threatened by the requirements of higher levels of computing powers and interoperability among the huge and various sets of data.…”

“…Some studies have addressed some aspects of including these non-physical components in the city digital twin model, such as behavior modeling according to agents' needs and mental features [48,49]. Others investigated monitoring citizens' health conditions, movement patterns, and stress detection for the elders [40,58,59]; that is, placing the human factor at the center of the digital twin is gaining research attention. Yet, many applications can be anticipated from integrating the non-physical components that can enhance several city domains such as urban planning, mobility, and the environment.…”

Engineering Smarter Cities with Smart City Digital Twins

“…In order to solidify the theoretical and scholarly foundation of a smart city digital twin paradigm, largely established in a National Science Foundation Smart City Digital Twin Convergence Conference (Taylor et al 2019), and highlight the latest discoveries across the spectrum of SCDT research, in this special collection we feature papers that explore topics ranging in foci from theory, scale, and system architecture for smart city digital twins (Lu et al 2020;Austin et al 2020); data, sensing, IoT, and analytics for smart city digital twins (Ruhlandt et al 2020;Zhao et al 2020;Lu et al 2020;Francisco et al 2020); human-infrastructure interdependencies, connectivity, and citizen engagement (Lee et al 2020;Ham and Kim 2020;Fan et al 2020); information management and decision support for smart city digital twins (Du et al 2020;Lin and Cheung 2020;Francisco et al 2020); digital twin virtualization (virtual reality/augmented reality/mixed reality) of smart cities (Chen et al 2020;Ham and Kim 2020); to implications for operational readiness, context-aware simulation, and crisis management (Ford and Wolf 2020;Fan et al 2020;Du et al 2020;Lee et al 2020 2020) introduce an integrated SCDT framework for textual-visual-geo social sensing during disruptive events (e.g., case of 2017 Hurricane Harvey). This framework, consisting of a graph-based detection approach, an image-ranking algorithm, and a kernel density estimate, enables capturing the critical situational information and interpreting the results for situational awareness and disruption response.…”

“…Using the University of Cambridge as a case study, they explore the methodological and implementation challenges of developing the SCDT of the West Cambridge Campus, including integration of heterogeneous data, analysis, and decision-making processes in O&M management.•Austin et al (2020) further explore various approaches and challenges of architecting the operation of SCDT from a combined multidomain semantic modeling and rule-based reasoning perspective. Taking the Chicago metropolitan area as a case study, they propose a semantic modeling and machine learning integrated SCDT system architecture that supports data collection and processing, identification of events, and automated decision making.•Ruhlandt et al (2020) investigate the implications of SCDT from the perspective of smart cities' utilization of data and analytics by identifying the condition (e.g., structures, leadership, strategy, culture, data infrastructure, data governance, budgets) and outcome variables (e.g., intention, frequency, purpose) that could influence or have an impact on cities' decision-making process from both theoretical and practical standpoints Lee et al (2020). propose a human-centered SCDT simulation framework for capturing the stressful interactions of the elderly population with the built environment.…”