scholarly journals SmartTrolley: An Experimental Mobile Platform for Indoor Localization in Warehouses

2020 ◽  
Author(s):  
Abdelhak Bougouffa ◽  
Emmanuel Seignez ◽  
Samir Bouaziz ◽  
Florian Gardes
Keyword(s):  
Indoor Localization ◽  
Mobile Platform

Design of a Bell-Shaped Ultra Wideband Antenna for Indoor Localization System

2015 ◽  
Vol 5 (6) ◽  
pp. 323 ◽  
Author(s):  
Nadia Ghariani ◽  
Mohamed Salah Karoui ◽  
Mondher Chaoui ◽  
Mongi Lahiani ◽  
Hamadi Ghariani
Keyword(s):  
Indoor Localization ◽  
Ultra Wideband ◽  
Localization System ◽  
Wideband Antenna

IoT-TD: IoT Dataset for Multiple Model BLE-based Indoor Localization/Tracking

2021 ◽  
Author(s):  
Mohammad Salimibeni ◽  
Zohreh Hajiakhondi-Meybodi ◽  
Parvin Malekzadeh ◽  
Mohammadamin Atashi ◽  
Konstantinos N. Plataniotis ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Multiple Model

General approach to the reliability of work of the mini-bakery on the mobile platform

2018 ◽  
Vol 6 (10) ◽  
pp. 248-253
Author(s):  
Ihor Stadnyk ◽  
◽  
Volodymyr Vasyliv ◽  
Tetiana Kos ◽  
◽  
...  
Keyword(s):  
Mobile Platform

Anonymous Attestation Scheme with User-Controlled-Linkability for Trusted Mobile Platform

2014 ◽  
Vol 36 (7) ◽  
pp. 1434-1447
Author(s):  
Xiao-Han YUE ◽  
Fu-Cai ZHOU ◽  
Mu-Qing LIN ◽  
Fu-Xiang LI
Keyword(s):  
Mobile Platform

Physical Activity Behavior of Skilled Nursing Facility Patients: A 21-day Longitudinal Cohort Study (Preprint)

2020 ◽  
Author(s):  
Wenhao Zhang ◽  
Ramin Ramezani ◽  
Zhuoer Xie ◽  
John Shen ◽  
David Elashoff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Intensity ◽  
Indoor Localization ◽  
Pearson Correlation ◽  
Patent Application ◽  
Skilled Nursing Facility ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Longitudinal Changes ◽  
Therapy Room

BACKGROUND The availability of low cost ubiquitous wearable sensors has enabled researchers, in recent years, to collect a large volume of data in various domains including healthcare. The goal has been to harness wearables to further investigate human activity, physiology and functional patterns. As such, on-body sensors have been primarily used in healthcare domain to help predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In the previous studies [9,10] and the patent application [11], we introduced a generic framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and extraction of indoor localization using BLE beacons, in concert. This work is to address the longitudinal analyses of a particular cohort using the introduced framework in a skilled nursing facility. OBJECTIVE (a) To observe longitudinal changes of physical activity and indoor localization features of rehabilitation-dwelling patients, (b) to assess if such changes can be used at early stages during the rehabilitation period to discriminate between patients that will be re-hospitalized versus the ones that will be discharged to a community setting and (c) to investigate if the sensor based longitudinal changes can imitate patients changes captured by therapist assessments over the course of rehabilitation. METHODS Pearson correlation was used to compare occupational therapy (OT) and physical therapy (PT) assessments with sensor-based features. Generalized Linear Mixed Model was used to find associations between functional measures with sensor based features. RESULTS Energy intensity at therapy room was positively associated with transfer general (β=0.22;SE=0.08;p<.05). Similarly, sitting energy intensity showed positive association with transfer general (β=0.16;SE=0.07;p<.05). Laying down energy intensity was negatively associated with hygiene grooming (β=-0.27;SE=0.14;p<.05). The interaction of sitting energy intensity with time (β=-0.13;SE=.06;p<.05) was associated with toileting general. Dressing lower body was strongly correlated with overall energy intensity (r = 0.66), standing energy intensity (r = 0.61), and laying down energy intensity (r = 0.72) on the first clinical assessment session. CONCLUSIONS This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information on the storyline of daily and longitudinal activity patterns of rehabilitation-dwelling patients.

scholarly journals The Technology of Crowd-Sourcing Landmarks-Assisted Smartphone in Indoor Localization

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 57036-57048 ◽  
Author(s):  
Xinxin Wang ◽  
Danyang Qin ◽  
Ruolin Guo ◽  
Min Zhao ◽  
Lin Ma ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Crowd Sourcing
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