Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments

Vorlíček, Michal; Schipperijn, Jasper; Burian, Jaroslav; Rubín, Lukáš; Dygrýn, Jan; Mitáš, Josef; Duncan, Scott

doi:10.3390/s21217232

Cited by 11 publications

(8 citation statements)

References 44 publications

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“…First, the runners' experiences with measurement errors (see Section 4.1.2). were in line with the tests done for consumer-level self-tracking technologies (e.g., Johansson et al, 2020;Pasadyn et al, 2019;Vorlíček et al, 2021). Similarly, the runners' views about which measurements were more reliable than the others (see Section 4.2.)…”

Section: Discussionsupporting

confidence: 74%

“…Additionally, the wearer's skin color, including tattoos, can affect the quality of the signals of wrist-worn optical meters (Coros, 2022;Parak, 2018). GPS tracking, in turn, is less reliable in mountainous/hilly surroundings or in urban areas with tall buildings due to signal obstruction (Johansson et al, 2020;Vorlíček et al, 2021).…”

Section: Datafied Runner and Contextualized Data Literacymentioning

confidence: 99%

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Contextualizing everyday data literacies: The case of recreational runners

Palsa¹,

Mertala²

2022

Preprint

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Data literacy is typically described in a decontextualized manner, and many data literacy frameworks are detached from the “messy” realities of everyday life. In the present study, we selected a specific context (recreational running), specific data technology (self-tracking devices), and specific viewpoint (accuracy of data and analyses) to construct a substantial theory of (one form of) contextual data literacy. The research question is: How do recreational runners’ everyday data literacy appear in relation to the accuracy of measurements and analyses of self-tracking devices? Through a grounded theory-inspired analysis of qualitative survey data (N = 997), we identified the data literacy actions that runners engaged with when assessing the accuracy of data in relation to their subjective needs, objectives, and life situations. The first-order data literacy actions (comparison and evaluation) captured how runners assessed and analyzed the accuracy of data, and they took place mainly in the immediate context of running. The second-order data literacy actions (acceptance, adaptation, and optimization) were the result of the runners’ reflections of what they sought from running and how they valued data, as well as their broader life situation.

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Section: Discussionsupporting

confidence: 74%

Section: Datafied Runner and Contextualized Data Literacymentioning

confidence: 99%

Contextualizing everyday data literacies: The case of recreational runners

Palsa¹,

Mertala²

2022

Preprint

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“…GPS has become ubiquitous in portable consumer devices, such as smartphones [23] and navigation systems [24], as well as wearable devices, such as smartwatches [25]. As defined by Ye et al, a wearable device is 'a product controlled by electronic components and software that can be incorporated into clothing or worn on the body like accessories' [26].…”

Section: Use Of Gps In Patients With Dementiamentioning

confidence: 99%

Wearable and Portable GPS Solutions for Monitoring Mobility in Dementia: A Systematic Review

Cullen

Mazhar

Smith

et al. 2022

Sensors

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Dementia is the most common neurodegenerative disorder globally. Disease progression is marked by declining cognitive function accompanied by changes in mobility. Increased sedentary behaviour and, conversely, wandering and becoming lost are common. Global positioning system (GPS) solutions are increasingly used by caregivers to locate missing people with dementia (PwD) but also offer a non-invasive means of monitoring mobility patterns in PwD. We performed a systematic search across five databases to identify papers published since 2000, where wearable or portable GPS was used to monitor mobility in patients with common dementias or mild cognitive impairment (MCI). Disease and GPS-specific vocabulary were searched singly, and then in combination, identifying 3004 papers. Following deduplication, we screened 1972 papers and retained 17 studies after a full-text review. Only 1/17 studies used a wrist-worn GPS solution, while all others were variously located on the patient. We characterised the studies using a conceptual framework, finding marked heterogeneity in the number and complexity of reported GPS-derived mobility outcomes. Duration was the most frequently reported category of mobility reported (15/17), followed by out of home (14/17), and stop and trajectory (both 10/17). Future research would benefit from greater standardisation and harmonisation of reporting which would enable GPS-derived measures of mobility to be incorporated more robustly into clinical trials.

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“…The smallest inaccuracy is achieved in open areas and in sparsely built-up areas. For typical GPS receivers, the accuracy of GPS data is significantly less dependent on the type of GPS receiver than on the measurement environment [35]. In an urban area, the accuracy of GPS data is changeable and influenced by building density and the presence of electromagnetic fields interfering with the GPS signal.…”

Section: Introductionmentioning

confidence: 99%

Driving and Energy Profiles of Urban Bus Routes Predicted for Operation with Battery Electric Buses

Czapla,

Sierpiński

2023

Energies

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Battery electric buses are used for operation on urban bus routes. The main disadvantage of battery electric buses is their limited range that depends on energy consumption. This paper presents a new approach to the estimation of energy consumption on urban bus routes based on driving and energy profiles. The energy consumption results from the travel parameters along the bus route. The travel parameters are described by driving profiles. The determination of driving profiles is based on GPS location data recorded by a receiver on a bus. Location data are recorded at consecutive track points at a constant frequency. For each track point, the distance to the preceding track point is determined using the location data, and then the speed and acceleration are calculated. The analyzed bus route is divided into sections. For each section, travel parameters consisting of travel time, speed parameters, and acceleration parameters are determined. Using travel parameters, the energy consumption is estimated for individual sections and the entire bus route. The estimated energy consumption is described by energy profiles. Experimental results have been obtained for the selected urban bus route under various traffic conditions. For the assumed model of energy consumption, the energy consumed on the entire bus route is 1.8 KWh/km at off-peak hours and 2.1 KWh/km at peak hours. The driving and energy profiles describe the urban bus routes well and allow evaluation of the suitability of the bus route for operation with battery electric buses.

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Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments

Cited by 11 publications

References 44 publications

Contextualizing everyday data literacies: The case of recreational runners

Contextualizing everyday data literacies: The case of recreational runners

Wearable and Portable GPS Solutions for Monitoring Mobility in Dementia: A Systematic Review

Driving and Energy Profiles of Urban Bus Routes Predicted for Operation with Battery Electric Buses

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