Identifying Points of Interest for Elderly in Singapore through Mobile Crowdsensing

Marakkalage, Sumudu Hasala; Lau, Billy Pik Lik; Kadaba, Viswanath Sanjana; Balasubramaniam, Thirunavukarasu; Yuen, Chau; Yuen, Belinda; Nayak, Richi

doi:10.5220/0006309300600066

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…As for the topics of research interest, nearly 70% of the inclusions (24/35) concentrate on gerontology, namely, biomarkers (3) [33][34][35], frailty index (1) [36], epigenetics of aging (1) [37], aging of brain functional connectivity networks (1) [38], ARDs (16) that contain dementia (6) [39][40][41][42][43][44], stroke (2) [45,46], Parkinson's Disease (1 ) [47], fracture (1) [48], hypertension (1) [49], mild cognitive impairment (1) [50], depression (1) [51], pressure ulcers (1) [52], polypharmacy side-effects (1) [53], and mortality related to sarcopenia and frailty (1) [54]. The rest are devoted to technical support and decision support like cloud-based healthcare platforms focusing on dementia (1) [55], memory recall training (1) [56]), fraud detection in medicare (2) [57,58], prediction of readmission risk (2) [59,60], well-being (2) [61,62], population portraits (1) [63], built environment and health outcomes (1) [64], patterns of living activities (1) [65], trajectories (1) [66], and geospatial patterns of points of interest (1) [67].…”

Section: Research Topicsmentioning

confidence: 99%

“…Individual behaviours can reflect the inner function changes during the aging process. It is worth studying the purpose, frequency, strength, pattern [67], and characteristics [65] of the movement, as well as the space and place during these interactions, especially focusing on changes as elderly gradually lose independence and mobility [121]. With GPS location available, life-space mobility (proposed and developed by Cantor [122,123]) has become favourable to reflect the health status of the elderly in respect to cognitive health and independence [124].…”

Section: Mapping Support In Hunman-environment Interactionsmentioning

confidence: 99%

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The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework

Zhang

Gao

et al. 2021

Sustainability

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Big data has been prominent in studying aging and older people’s health. It has promoted modeling and analyses in biological and geriatric research (like cellular senescence), developed health management platforms, and supported decision-making in public healthcare and social security. However, current studies are still limited within a single subject, rather than flourished as interdisciplinary research in the context of big data. The research perspectives have not changed, nor has big data brought itself out of the role as a modeling tool. When embedding big data as a data product, analysis tool, and resolution service into different spatial, temporal, and organizational scales of aging processes, it would present as a connection, integration, and interaction simultaneously in conducting interdisciplinary research. Therefore, this paper attempts to propose an ecological framework for big data based on aging and older people’s health research. Following the scoping process of PRISMA, 35 studies were reviewed to validate our ecological framework. Although restricted by issues like digital divides and privacy security, we encourage researchers to capture various elements and their interactions in the human-environment system from a macro and dynamic perspective rather than simply pursuing accuracy.

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Section: Research Topicsmentioning

confidence: 99%

Section: Mapping Support In Hunman-environment Interactionsmentioning

confidence: 99%

The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework

Zhang

Gao

et al. 2021

Sustainability

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Characterization of Individual Mobility for Non-routine Scenarios from Crowd Sensing and Clustered Data

Cunha

Simões

Alves

et al. 2019

Lecture Notes in Computer Science

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Indoor positioning using similarity-based sequence and dead reckoning without training

Liu

Yuen

et al. 2017

2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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For the traditional fingerprinting-based positioning approach, it is essential to collect measurements at known locations as reference fingerprints during a training phase, which can be time-consuming and labor-intensive. This paper proposes a novel approach to track a user in an indoor environment by integrating similarity-based sequence and dead reckoning. In particular, we represent the fingerprinting map as location sequences based on distance ranking of the APs (access points) whose positions are known. The fingerprint used for online positioning is represented by a ranked sequence of APs based on the measured Received Signal Strength (RSS), which is refereed to as RSS sequence in this paper. Embedded into a particle filter, we achieve the tracking of a mobile user by fusing the sequencebased similarity and dead reckoning. Extensive experiments are conducted to evaluate the proposed approach.Index Terms-indoor positioning, similarity-based sequence, particle filtering, dead reckoning.

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Identifying Points of Interest for Elderly in Singapore through Mobile Crowdsensing

Cited by 5 publications

References 6 publications

The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework

The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework

Characterization of Individual Mobility for Non-routine Scenarios from Crowd Sensing and Clustered Data

Indoor positioning using similarity-based sequence and dead reckoning without training

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