Assessing personal exposure to urban greenery using wearable cameras and machine learning

Zhang, Zhaoxi; Long, Ying; Chen, Long; Chen, Chun

doi:10.1016/j.cities.2020.103006

Cited by 27 publications

(14 citation statements)

References 33 publications

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“…Wearable camera technology has recently been used in health studies to assess physical activity, nutrition, and the environment. 90 91 92 Since previous studies have usually depended on participants’ motivation and memory to acquire information, they are potentially biased. Salmon, et al 90 reported on wearable cameras in combination with a personal PM 2.5 monitor.…”

Section: Section 3: Effects and Management Of Environmental Exposurementioning

confidence: 99%

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Digital Healthcare for Airway Diseases from Personal Environmental Exposure

2022

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Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies’ abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.

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Section: Section 3: Effects and Management Of Environmental Exposurementioning

confidence: 99%

“…A wearable camera can automatically and passively record abundant imagery of an individual’s exposure to greenery, which together with the technology of image detection helps clarify the role of greenery during individual lifelogging. 91 …”

Section: Section 3: Effects and Management Of Environmental Exposurementioning

confidence: 99%

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

2022

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“…It is obvious that urban greenery is a significant part of human civilization and its role is unreplaceable. Urban green areas contribute to numerous benefits to the urban environment and the society, such as maintaining ecological processes, generating ecosystem services (Bertram and Rehdanz, 2015; Andersson-Sköld et al, 2018), providing the space for recreation and physical activities (Schipperijn et al, 2013;Yang et al, 2021) as well as exerting direct and indirect impact on human well-being and health (Zhang et al, 2021;Zhou et al, 2021). Green areas are increasingly considered as tools for mitigation of climate change (including urban-heat islands, floods) and as biodiversity refuges (Byrne et al, 2015;Boulton et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Promoting Biodiversity: Vegetation in a Model Small Park Located in the Research and Educational Centre

Winkler¹,

Jeznach²,

Koda³

et al. 2022

J. Ecol. Eng.

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University campuses, as important elements of urban greenery, are related with a positive impact on student health and well-being. They provide unique possibilities for estimating biodiversity change. This study focused on the biodiversity in the Campus. The study aimed at: assessing the plant biodiversity occurring in the park; assessing the representation of native species and determining the frequency at which invasive species occur; as well as recommending an adaptation of the park management. The Park was sub-divided into biotopes and a phytocoenological relevé was recorded. Park projects create biodiversity islands that may contribute to improve urban space. A species composition that is close to natural vegetation creates a space for native species, which thus better adapt to living in urban conditions. Localities created by humans, which imitate natural ecosystems, increase the biodiversity and are valuable natural islands in cities. The semi-natural phytocoenoses however, do not resist the occurrence of invasive plant species. Regarding the small size of the studied park, manual elimination or cutting of invasive plant species is sufficient.

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“…These life activities, in most cases, involve visitation to places (also called points of interest (POI)). Hence, with the growing availability of urban sensing and location-based data, a number of recent studies have examined human visitation and activities to unveil important characteristics about urban lifestyles (Xu et al, 2020;Zhang et al, 2021;Zhao et al, 2021). However, the existing literature related to characterizing population lifestyles is limited in two important aspects.…”

Section: Introductionmentioning

confidence: 99%

“…The growing availability of urban-scale big data and sensing technologies has been a major driver of recent studies focusing on aspects of urban dynamics and complexity. We have recently witnessed the following becoming significant data sources for researchers to characterize urban dynamics and complexity: mobile phone calls from almost any location (Zhao et al, 2021), purchases made with credit cards (Xu et al, 2020), blog entries through online social media (Hasnat & Hasan, 2018), and even movements captured by video cameras (Zhang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Characterizing Urban Lifestyle Signatures Using Motif Properties in Network of Places

Ma¹,

Li²,

Mostafavi³

2022

Preprint

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The lifestyles of urban dwellers could reveal important insights regarding the dynamics and complexity of cities. The availability of human movement data, anonymized and aggregated data captured from cell phone movement, enables characterization of distinct and recurrent human daily visitation patterns. Despite a growing body of research on analysis and evaluation of lifestyle patterns in cities, little is known about the characteristics of people's lifestyles patterns at urban scale. This limitation is primarily due to challenges in characterizing lifestyle patterns when human movement data is aggregated to protect the privacy of users. To address this gap, in this study, we model cities based on aggregated human visitation data to construct a network of places. We then examine the subgraph signatures (i.e., motifs) in the networks of places to map and characterize lifestyle patterns at city scale. Location-based data from Harris County, Dallas County, New York County, and Broward County in the United States were examined to reveal lifestyle signatures in cities. For the motif analysis, two-node, three-node, and four-node motifs without location attributes were extracted from human visitation networks. Second, homogenized nodes in motifs were encoded with location categories from NAICS codes. Multiple statistical measures, including network metrics and motif properties, were quantified to characterize lifestyle signatures. The results show that: i) people's lifestyles in urban environments can be well depicted and quantified based on distribution and attributes of motifs in networks of places; ii) motifs in networks of places show stability in quantity and distance as well as periodicity on weekends and weekdays indicating the stability of lifestyle patterns in cities; iii) human visitation networks and lifestyle patterns show similarities across different metropolitan areas implying the universality of lifestyle signatures across cities; iv) lifestyles represented by attributed motifs are spatially heterogeneous suggesting variations of lifestyle patterns within different population groups based on where they live in a city. The findings provide deeper insights into urban lifestyles signatures in urban studies and provide important insights for data-informed urban planning and management.

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Assessing personal exposure to urban greenery using wearable cameras and machine learning

Cited by 27 publications

References 33 publications

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

Promoting Biodiversity: Vegetation in a Model Small Park Located in the Research and Educational Centre

Characterizing Urban Lifestyle Signatures Using Motif Properties in Network of Places

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