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Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms

Katherine Ellis, Suneeta Godbole, Simon Marshall, Gert Lanckriet, John Staudenmayer, Jacqueline Kerr
2014 Frontiers in Public Health  
Methods: We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a  ...  In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data.  ...  The net distance covered feature is computed from the GPS data, by simply computing the distance between the first and last latitude and longitude points in a data window.  ... 
doi:10.3389/fpubh.2014.00036 pmid:24795875 pmcid:PMC4001067 fatcat:twewgjua3neglo23ojmdao5maa

An Adaptive Staying Point Recognition Algorithm Based on Spatiotemporal Characteristics Using Cellular Signaling Data

Ming Cai, Zixuan Zhang, Chen Xiong, Chao Gou
2021 IEEE transactions on intelligent transportation systems (Print)  
Then, rules to distinguish the staying or moving cluster are made from individual travel characteristics.  ...  In this work, a "spatiotemporal window"-based algorithm is proposed to recognize individual staying and moving states.  ...  We mapped the staying points identified from each travel trajectory in Fig. 13 and compared them with the actual staying positions. D.  ... 
doi:10.1109/tits.2021.3094636 fatcat:2qi7z674v5av5hndlqtt2cftyi

An open-source tool to identify active travel from hip-worn accelerometer, GPS and GIS data

Duncan S. Procter, Angie S. Page, Ashley R. Cooper, Claire M. Nightingale, Bina Ram, Alicja R. Rudnicka, Peter H. Whincup, Christelle Clary, Daniel Lewis, Steven Cummins, Anne Ellaway, Billie Giles-Corti (+2 others)
2018 International Journal of Behavioral Nutrition and Physical Activity  
We also manually identified the travel behaviour of both 21 participants from ENABLE London (402,749 points), and 10 participants from a separate study (STAMP-2, 210,936 points), who were not included  ...  Here we provide an open source tool to quantify time spent stationary and in four travel modes(walking, cycling, train, motorised vehicle) from accelerometer measured physical activity data, combined with  ...  First, we extracted a subset of the training data to test different moving window sizes: if a participant contributed multiple days to the training data, we took the first day to test moving windows.  ... 
doi:10.1186/s12966-018-0724-y pmid:30241483 pmcid:PMC6150970 fatcat:6bnpol2o4zbunelr3nfo7hzf4a

Urban travel time data cleaning and analysis for Automatic Number Plate Recognition

Jie Li, Henk van Zuylen, Yuansheng Deng, Yun Zhou
2020 Transportation Research Procedia  
Travel time extracted from ANPR data includes some outliers which are often caused by drivers who have an intermediate stop between two observation points or deviate from the straight route.  ...  The wavelet analysis method is compared with the Rapid-Moving Window method and shows to be more accurate in outlier identification.  ...  Fig. 1 . 1 (a) Raw travel times; (b) Outliers identified with Rapid-Moving Window method for Link 1225-1227 on Apr. 20, 2015.  ... 
doi:10.1016/j.trpro.2020.03.151 fatcat:j4pxkne7gzhi7af5bg725bstsa

A Review of GPS Trajectories Classification Based on Transportation Mode

Xue Yang, Kathleen Stewart, Luliang Tang, Zhong Xie, Qingquan Li
2018 Sensors  
GPS trajectories generated by moving objects provide researchers with an excellent resource for revealing patterns of human activities.  ...  From a GPS data acquisition point of view, this paper macroscopically classifies the transportation mode of GPS data into single-mode and mixed-mode.  ...  Compared with passive data collection, transportation mode of GPS data using active way mainly depends on users' behavior.  ... 
doi:10.3390/s18113741 pmid:30400204 fatcat:mj2czfs5hvae5im4du5fzw4zky

MARITIME BIG DATA ANALYSIS WITH ARLAS

W. Gautier, S. Falquier, S. Gaudan
2021 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
We use a Hidden Markov Model (HMM) to identify when a vessel is still or moving and we create "courses", embodying the travel of the vessel. Then we derive the travel indicators.  ...  However, the exploitation of these numerous messages requires tools based on Big Data principles.Acknowledgement of origin, destination, travel duration and distance of each vessel can help transporters  ...  like to thank the Gisaïa team for this collective effort, particularly Laurent Dezou for leading a company that values innovation and research for societal issues, Mohamed Hamou for his wonderful help with  ... 
doi:10.5194/isprs-archives-xlvi-4-w2-2021-71-2021 fatcat:hkxczpqxhjdkhgntd2p4k5aqs4

VJAǴǴ– A Thick-Client Smart-Phone Journey Detection Algorithm [article]

Michael P. J. Camilleri, Adrian Muscat, Victor Buttigieg, Maria Attard
2020 arXiv   pre-print
The algorithm can be embedded in the client app of the transport service provider or in a general purpose mobility data collector.  ...  The thick client setup allows the customer/participant to select which journeys are transferred to the server, keeping customers in control of their personal data and encouraging user uptake.  ...  Vjaġġ is able to anonymously and seamlessly collect travel data from participants, using the device's GPS receiver and accelerometer.  ... 
arXiv:1908.10725v2 fatcat:7c5ef4db4bew3iqeqjhwyo3hem

Visualizing Hidden Themes of Taxi Movement with Semantic Transformation

Ding Chu, David A. Sheets, Ye Zhao, Yingyu Wu, Jing Yang, Maogong Zheng, George Chen
2014 2014 IEEE Pacific Visualization Symposium  
Urban planners, administration, travelers, and drivers can conduct their various knowledge discovery tasks with direct semantic and visual assists.  ...  The effectiveness of this approach is illustrated by case studies using a large taxi trajectory data set acquired from 21,360 taxis in a city.  ...  Speed Compensation The GPS positions that are acquired with regular time intervals create bias toward slower moving roads with more samples.  ... 
doi:10.1109/pacificvis.2014.50 dblp:conf/apvis/ChuSZWYZC14 fatcat:nupfyrsxj5atvogjdvkjcp3lvi

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

Patrick Boissy, Margaux Blamoutier, Simon Brière, Christian Duval
2018 Frontiers in Public Health  
Participants wore, for 14 days during waking hours on the hip, a data logger incorporating a GPS receiver with a 3-axis accelerometer.  ...  The objectives of this paper are to present and illustrate the signal processing workflow and outcomes that can be extracted from an activity and community mobility measurement approach based on GPS and  ...  Activity space, a concept originating from medical geography and defined as "the local areas within which people move or travel in the course of their daily activities" (13) has been used to examine  ... 
doi:10.3389/fpubh.2018.00216 pmid:30151357 pmcid:PMC6099098 fatcat:7w2i4rhicrg4phcnvy7ywkoys4

A behavior observation tool (BOT) for mobile device network connection logs

Ting Wang
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
In order to observe user behavior from this kind of data set, we propose a new algorithm, namely Behavior Observation Tool (BOT), which uses Convex Hull Algorithm with sliding time windows to model the  ...  active areas of users.  ...  Travel Patterns How the user from one active area to another, i.e. the travel pattern, is also often of great interests in mobility observation studies.  ... 
doi:10.1145/2567948.2580069 dblp:conf/www/Wang14 fatcat:72igsfwquve67bd2fkmvw3kb7a

Transportation mode detection – an in-depth review of applicability and reliability

Adrian C. Prelipcean, Gyözö Gidófalvi, Yusak O. Susilo
2016 Transport reviews  
The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed  ...  of data collecting outlets.  ...  The next challenge is related to data acquisition and it is two-fold: 1) identify how to collect data from multiple users without (substantial) extra costs, and 2) having a "benchmark" dataset, which is  ... 
doi:10.1080/01441647.2016.1246489 fatcat:642ssymlbncrlczs63eytnaxrq

Using a Partial Sum Method and GPS Tracking Data to Identify Area Restricted Search by Artisanal Fishers at Moored Fish Aggregating Devices in the Commonwealth of Dominica

Michael Alvard, David Carlson, Ethan McGaffey, Kentaro Q. Sakamoto
2015 PLoS ONE  
Faster, more directed movement is associated with travel.  ...  These patches can be identified behaviorally when a forager shifts from travel to area restricted search, identified by a decrease in speed and an increase in sinuosity of movement.  ...  Variance in speeds is clearly apparent with the points color-coded and showing that activities at the patches involve all three modes of speed identified from the k-means analysis.  ... 
doi:10.1371/journal.pone.0115552 pmid:25647288 pmcid:PMC4315603 fatcat:epsu353gmvgg5ju2acmwvkfobq

Discover User Behaviour from Trajectory as Polygons (TaP)

Ting Wang
2014 International Journal of Applied Physics and Mathematics  
In particular, we found TaP effectively extract trajectory properties from polygons generated by convex hull algorithm with a time window.  ...  A lot of work has been developed to find useful information from these data and various approaches has been proposed.  ...  Travel Patterns How the object from one active area to another, i.e. the travel pattern is also often of great interests in mobility observation studies.  ... 
doi:10.7763/ijapm.2014.v4.250 fatcat:3abkesw2dnco7fdqckp2vmakbe

Analysis of human mobility patterns from GPS trajectories and contextual information

Katarzyna Siła-Nowicka, Jan Vandrol, Taylor Oshan, Jed A. Long, Urška Demšar, A. Stewart Fotheringham
2015 International Journal of Geographical Information Science  
Can these places be identified from GPS traces?  ...  While this has spurred many methodological developments in identifying human movement patterns, many of these methods operate solely from the analytical perspective and ignore the environmental context  ...  It scans each trajectory using two moving windows -one facing backwards and one forwards and then sums the STKW values within both windows.  ... 
doi:10.1080/13658816.2015.1100731 fatcat:stv2r4ve65b7hi53wkhc6hkopq

The Effects of GPS-Based Buffer Size on the Association between Travel Modes and Environmental Contexts

Lee, Kwan
2019 ISPRS International Journal of Geo-Information  
contexts and active travel modes (ATMs) as a subset of physical activity vary with GPS-based buffer size.  ...  with buffer analysis.  ...  Method GPS Data The GPS data and daily activity diaries collected in the Chicago Regional Household Travel Inventory (CRHTI) project were used in this study.  ... 
doi:10.3390/ijgi8110514 fatcat:5nqaend3tzc35l5cwozbk465uq
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