{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T05:37:44Z","timestamp":1733981864366,"version":"3.30.2"},"reference-count":17,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IDT"],"published-print":{"date-parts":[[2024,9,16]]},"abstract":"Many factors affect the precision and accuracy of location data. These factors include, but not limited to, environmental obstructions (e.g., high buildings and forests), hardware issues (e.g., malfunctioning and poor calibration), and privacy concerns (e.g., users denying consent to fine-grained location tracking). These factors lead to uncertainty about users\u2019 location which in turn affects the quality of location-aware services. This paper proposes a novel framework called UMove, which stands for uncertain movements, to manage the trajectory of moving objects under location uncertainty. The UMove framework employs the connectivity (i.e., links between edges) and constraints (i.e., travel time and distance) on road network graphs to reduce the uncertainty of the object\u2019s past, present, and projected locations. To accomplish this, UMove incorporates (i) a set-based pruning algorithm to reduce or eliminate uncertainty from imprecise trajectories; and (ii) a wrapper that can extend user-defined probability models designed to predict future locations of moving objects under uncertainty. Intensive experimental evaluations based on real data sets of GPS trajectories collected by Didi Chuxing in China prove the efficiency of the proposed UMove framework. In terms of accuracy, for past exact-location inference, UMove achieves rates from 88% to 97% for uncertain regions with sizes of 75 meters and 25 meters respectively; for future exact-location inference, accuracy rates reach up to 72% and 82% for 75 meters and 25 meters of uncertain regions.<\/jats:p>","DOI":"10.3233\/idt-240819","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T14:56:29Z","timestamp":1724165789000},"page":"2097-2113","source":"Crossref","is-referenced-by-count":0,"title":["Framework to process vehicles uncertain locations for intelligent transportation"],"prefix":"10.1177","volume":"18","author":[{"given":"Mohammed","family":"Abdalla","sequence":"first","affiliation":[{"name":"Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt"}]},{"given":"Abdullah","family":"Islam","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Statistics, University of Rhode Island, USA"}]},{"given":"Mohamed","family":"Ali","sequence":"additional","affiliation":[{"name":"Institute of Technology, University of Washington, USA"}]},{"given":"Abdeltawab","family":"Hendawi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Statistics, University of Rhode Island, USA"}]}],"member":"179","reference":[{"key":"10.3233\/IDT-240819_ref5","doi-asserted-by":"crossref","first-page":"202","DOI":"10.3390\/info12050202","article-title":"A real-time processing for contact tracing using indoor trajectories","volume":"12","author":"Alarabi","year":"2021","journal-title":"Information"},{"issue":"5","key":"10.3233\/IDT-240819_ref6","doi-asserted-by":"crossref","first-page":"202","DOI":"10.3390\/info12050202","article-title":"Traceall: A real-time processing for contact tracing using indoor trajectories","volume":"12","author":"Alarabi","year":"2021","journal-title":"Information"},{"key":"10.3233\/IDT-240819_ref19","doi-asserted-by":"crossref","first-page":"4438","DOI":"10.1109\/TSP.2020.3008752","article-title":"Multistatic moving object localization by a moving transmitter of unknown location and offset","volume":"68","author":"Zhang","year":"2020","journal-title":"IEEE Transactions on Signal Processing"},{"key":"10.3233\/IDT-240819_ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497415"},{"issue":"4","key":"10.3233\/IDT-240819_ref25","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1007\/s00778-010-0181-y","article-title":"Path prediction and predictive range querying in road network databases","volume":"19","author":"Jeung","year":"2010","journal-title":"The VLDB Journal"},{"issue":"1","key":"10.3233\/IDT-240819_ref29","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.cageo.2006.05.011","article-title":"Uncertain spatial data handling: Modeling, indexing and query","volume":"33","author":"Li","year":"2007","journal-title":"Computers & Geosciences"},{"issue":"1","key":"10.3233\/IDT-240819_ref30","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.14778\/1687627.1687762","article-title":"Effectively indexing uncertain moving objects for predictive queries","volume":"2","author":"Zhang","year":"2009","journal-title":"Proc VLDB Endow"},{"issue":"3","key":"10.3233\/IDT-240819_ref32","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1145\/1272743.1272745","article-title":"Range search on multidimensional uncertain data","volume":"32","author":"Tao","year":"2007","journal-title":"ACM Trans Database Syst"},{"key":"10.3233\/IDT-240819_ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2424321.2424324"},{"issue":"2","key":"10.3233\/IDT-240819_ref36","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s10707-016-0284-8","article-title":"Panda*: A generic and scalable framework for predictive spatio-temporal queries","volume":"21","author":"Hendawi","year":"2017","journal-title":"GeoInformatica"},{"key":"10.3233\/IDT-240819_ref42","doi-asserted-by":"crossref","first-page":"23881","DOI":"10.1109\/ACCESS.2020.2966982","article-title":"DeepMotions: A deep learning system for path prediction using similar motions","volume":"8","author":"Abdalla","year":"2020","journal-title":"IEEE Access"},{"key":"10.3233\/IDT-240819_ref44","doi-asserted-by":"crossref","unstructured":"Mokhtar MAHMO, ElGamal N. HarmonyMoves: A unified prediction approach for moving object future path. International Journal of Advanced Computer Science and Applications. 2020; 11(1).","DOI":"10.14569\/IJACSA.2020.0110178"},{"issue":"3","key":"10.3233\/IDT-240819_ref47","doi-asserted-by":"crossref","first-page":"205","DOI":"10.14778\/2732232.2732239","article-title":"Probabilistic nearest neighbor queries on uncertain moving object trajectories","volume":"7","author":"Niedermayer","year":"2013","journal-title":"Proc VLDB Endow"},{"issue":"0","key":"10.3233\/IDT-240819_ref48","first-page":"1","article-title":"Predicting future locations of moving objects with deep fuzzy-LSTM networks","volume":"0","author":"Li","year":"2018","journal-title":"Transportmetrica A: Transport Science"},{"issue":"3","key":"10.3233\/IDT-240819_ref49","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1007\/s10489-009-0173-z","article-title":"PutMode: Prediction of uncertain trajectories in moving objects databases","volume":"33","author":"Qiao","year":"2010","journal-title":"Applied Intelligence"},{"issue":"6","key":"10.3233\/IDT-240819_ref51","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/TMC.2005.74","article-title":"A mobility prediction architecture based on contextual knowledge and spatial conceptual maps","volume":"4","author":"Samaan","year":"2005","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"10.3233\/IDT-240819_ref53","doi-asserted-by":"publisher","DOI":"10.1145\/1516360.1516460"}],"container-title":["Intelligent Decision Technologies"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/IDT-240819","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T13:43:21Z","timestamp":1733924601000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/IDT-240819"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,16]]},"references-count":17,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/idt-240819","relation":{},"ISSN":["1872-4981","1875-8843"],"issn-type":[{"type":"print","value":"1872-4981"},{"type":"electronic","value":"1875-8843"}],"subject":[],"published":{"date-parts":[[2024,9,16]]}}}