{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T08:40:19Z","timestamp":1726044019331},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030308582"},{"type":"electronic","value":"9783030308599"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-30859-9_14","type":"book-chapter","created":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T12:03:26Z","timestamp":1568203406000},"page":"157-167","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Approach to the Analysis of the Vehicle Movement on the Organization Territory"],"prefix":"10.1007","author":[{"given":"Evgenia","family":"Novikova","sequence":"first","affiliation":[]},{"given":"Yana","family":"Bekeneva","sequence":"additional","affiliation":[]},{"given":"Andrey","family":"Shorov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,9,12]]},"reference":[{"key":"14_CR1","unstructured":"Millonig, A., Maierbrugger, G.: Identifying unusual pedestrian movement behavior in public transport infrastructures. In: Proceedings of Movement Pattern Analysis Workshop (MPA2010), Zurich, pp. 106\u2013110 (2010)"},{"key":"14_CR2","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.apgeog.2011.05.011","volume":"32","author":"M Versichele","year":"2012","unstructured":"Versichele, M., Neutens, T., Delafontaine, M., van de Weghe, N.: The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: a case study of the Ghent Festivities. Appl. Geogr. 32, 208\u2013220 (2012)","journal-title":"Appl. Geogr."},{"issue":"4","key":"14_CR3","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1111\/gean.12063","volume":"46","author":"Y Lerman","year":"2014","unstructured":"Lerman, Y., Rofe, Y., Omer, I.: Using space syntax to model pedestrian movement in urban transportation planning. Geog. Anal. 46(4), 392\u2013410 (2014)","journal-title":"Geog. Anal."},{"issue":"3","key":"14_CR4","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1080\/17489725.2010.537449","volume":"4","author":"D Guo","year":"2010","unstructured":"Guo, D., Liu, S., Jin, H.: A graph-based approach to vehicle trajectory analysis. J. Location Based Serv. 4(3), 183\u2013199 (2010)","journal-title":"J. Location Based Serv."},{"issue":"1","key":"14_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/s40462-015-0032-y","volume":"3","author":"U Dem\u0161ar","year":"2015","unstructured":"Dem\u0161ar, U., et al.: Analysis and visualisation of movement: an interdisciplinary review. Mov. Ecol. 3(1), 5 (2015)","journal-title":"Mov. Ecol."},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Brennand, C.A., da Cunha, F.D., Maia, G., Cerqueira, E., Loureiro, A.A., Villas, L.A.: FOX: a traffic management system of computer-based vehicles FOG. In: 2016 IEEE Symposium on Computers and Communication (ISCC), IEEE, pp. 982\u2013987 (2016)","DOI":"10.1109\/ISCC.2016.7543864"},{"issue":"2","key":"14_CR7","doi-asserted-by":"publisher","first-page":"157","DOI":"10.3390\/s16020157","volume":"16","author":"K Nellore","year":"2016","unstructured":"Nellore, K., Hancke, G.: A survey on urban traffic management system using wireless sensor networks. Sensors 16(2), 157 (2016)","journal-title":"Sensors"},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1155\/2015\/432389","volume":"2015","author":"C Bai","year":"2015","unstructured":"Bai, C., Peng, Z.R., Lu, Q.C., Sun, J.: Dynamic bus travel time prediction models on road with multiple bus routes. Comput. Intell. Neurosci. 2015, 63 (2015)","journal-title":"Comput. Intell. Neurosci."},{"issue":"4","key":"14_CR9","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1111\/mice.12315","volume":"33","author":"B Yu","year":"2018","unstructured":"Yu, B., Wang, H., Shan, W., Yao, B.: Prediction of bus travel time using random forests based on near neighbors. Comput. Aided Civ. Infrastruct. Eng. 33(4), 333\u2013350 (2018)","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"issue":"5","key":"14_CR10","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/MWC.2018.1700415","volume":"25","author":"V Petrov","year":"2018","unstructured":"Petrov, V., Andreev, S., Gerla, M., Koucheryavy, Y.: Breaking the limits in urban video monitoring: massive crowd sourced surveillance over vehicles. IEEE Wireless Commun. 25(5), 104\u2013112 (2018)","journal-title":"IEEE Wireless Commun."},{"issue":"12","key":"14_CR11","doi-asserted-by":"publisher","first-page":"3484","DOI":"10.1109\/TITS.2016.2552639","volume":"17","author":"N Bekiaris-Liberis","year":"2016","unstructured":"Bekiaris-Liberis, N., Roncoli, C., Papageorgiou, M.: Highway traffic state estimation with mixed connected and conventional vehicles. IEEE Trans. Intell. Transp. Syst. 17(12), 3484\u20133497 (2016)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Xu, B., Barkley, T., Lewis, A., MacFarlane, J., Pietrobon, D., Stroila, M.: Real-time detection and classification of traffic jams from probe data. In: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, p. 79, October 2016","DOI":"10.1145\/2996913.2996988"},{"key":"14_CR13","volume-title":"Car accident detection and notification system using smartphone","author":"HM Ali","year":"2017","unstructured":"Ali, H.M., Alwan, Z.S.: Car accident detection and notification system using smartphone. LAP LAMBERT Academic Publishing, Saarbrucken (2017)"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Kumar, J.M., Mahajan, R., Prabhu, D., Ghose, D.: Cost effective road accident prevention system. In: 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), IEEE, pp. 353\u2013357, December 2016","DOI":"10.1109\/IC3I.2016.7917988"},{"issue":"5","key":"14_CR15","doi-asserted-by":"publisher","first-page":"2487","DOI":"10.1007\/s11042-015-2637-y","volume":"75","author":"Y Li","year":"2016","unstructured":"Li, Y., Liu, W., Huang, Q.: Traffic anomaly detection based on image descriptor in videos. Multimedia Tools Appl. 75(5), 2487\u20132505 (2016)","journal-title":"Multimedia Tools Appl."},{"key":"14_CR16","first-page":"1","volume":"3","author":"B Fernandes","year":"2016","unstructured":"Fernandes, B., Alam, M., Gomes, V., Ferreira, J., Oliveira, A.: Automatic accident detection with multi-modal alert system implementation for ITS. Veh. Commun. 3, 1\u201311 (2016)","journal-title":"Veh. Commun."},{"issue":"3","key":"14_CR17","first-page":"1025","volume":"3","author":"A Topinkatti","year":"2015","unstructured":"Topinkatti, A., Yadav, D., Kushwaha, V.S., Kumari, A.: Car accident detection system using GPS and GSM. Int. J. Eng. Res. Gen. Sci. 3(3), 1025\u20131033 (2015)","journal-title":"Int. J. Eng. Res. Gen. Sci."},{"issue":"4","key":"14_CR18","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/s00068-015-0544-6","volume":"42","author":"K Goniewicz","year":"2016","unstructured":"Goniewicz, K., Goniewicz, M., Paw\u0142owski, W., Fiedor, P.: Road accident rates: strategies and programmes for improving road traffic safety. Eur. J. Trauma Emergency Surg. 42(4), 433\u2013438 (2016)","journal-title":"Eur. J. Trauma Emergency Surg."},{"issue":"38","key":"14_CR19","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1177\/0361198118797211","volume":"2672","author":"C Tan","year":"2018","unstructured":"Tan, C., Zhou, N., Wang, F., Tang, K., Ji, Y.: Real-time prediction of vehicle trajectories for proactively identifying risky driving behaviors at high-speed intersections. Transp. Res. Rec. 2672(38), 233\u2013244 (2018)","journal-title":"Transp. Res. Rec."},{"issue":"6","key":"14_CR20","doi-asserted-by":"publisher","first-page":"3017","DOI":"10.1109\/TITS.2015.2462084","volume":"16","author":"S Kaplan","year":"2015","unstructured":"Kaplan, S., Guvensan, M.A., Yavuz, A.G., Karalurt, Y.: Driver behavior analysis for safe driving: a survey. IEEE Trans. Intell. Transp. Syst. 16(6), 3017\u20133032 (2015)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"14_CR21","unstructured":"GPS Fleet Tracking. \n                      http:\/\/smpsolutions.in\/route-alert\/\n                      \n                    . Accessed 20 May 2019"},{"key":"14_CR22","unstructured":"Route Deviation Monitoring. \n                      https:\/\/unitedtracker.com\/route-deviation-monitoring\/\n                      \n                    . Accessed 20 May 2019"},{"key":"14_CR23","unstructured":"Ya, B., Lebedev, S., Kholod, I., Shorov, A., Novikova, E.: Method for transformation of data from heterogeneous monitoring devices for violations detection. In: 2017 XXI IEEE International Conference on Soft Computing and Measurements (SCM), St-Petersburg, 23\u201325 May 2018, pp. 753\u2013756 (2017)"},{"key":"14_CR24","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1016\/j.procs.2019.02.067","volume":"150","author":"YA Bekeneva","year":"2019","unstructured":"Bekeneva, Y.A., Kholod, I.I., Lebedev, S.I., Novikova, E.S., Shorov, A.V.: Violation detection in heterogeneous events streams. Procedia Comput. Sci. 150, 381\u2013388 (2019)","journal-title":"Procedia Comput. Sci."},{"key":"14_CR25","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1111\/j.0016-7363.2006.00682.x","volume":"38","author":"M Caldas de Castro","year":"2006","unstructured":"Caldas de Castro, M., Singer, B.: Controlling the false discovery rate: a new application to account for multiple and dependent test in local statistics of spatial association. Geogr. Anal. 38, 180\u2013208 (2006)","journal-title":"Geogr. Anal."},{"key":"14_CR26","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. JMLR 12, 2825\u20132830 (2011)","journal-title":"JMLR"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Bekeneva, Y.A., Kholod, I.I., Lebedev, S.I., Novikova, E.S., Shorov, A.V.: Towards simulation of the processes related to transport movement within industrial objects. In: Proceedings of the IT&QM&IS \u2013 2018, pp. 304\u2013307 (2018)","DOI":"10.1109\/ITMQIS.2018.8525127"}],"container-title":["Lecture Notes in Computer Science","Internet of Things, Smart Spaces, and Next Generation Networks and Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-30859-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T12:05:39Z","timestamp":1568203539000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-30859-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030308582","9783030308599"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-30859-9_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"12 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ruSMART","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Conference on Internet of Things and Smart Spaces","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"St. Petersburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Russia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"rusmart2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/rusmart.e-werest.org\/2019.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EDAS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"34% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}