{"created":"2020-09-01T15:21:55.429831+00:00","id":4803,"links":{},"metadata":{"_buckets":{"deposit":"6712a097-624a-45dc-bbb0-c5dd096a8fb7"},"_deposit":{"id":"4803","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4803"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4803","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Prediction System for Traffic Congestion using GPS Data on Hadoop Cloud Storage","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"The high values of vehicles, the inadequateinfrastructure cause traffic congestion. Congestedroads can be avoided by determining the travel-timefor a particular road ahead of time. Traffic predictionand travel time estimation has traditionally relied onexpensive measuring methods such as loop detectors,vehicle identification devices. In this paper, we usemobile GPS equipments on vehicles to gather data forcheaper and real time travel-time estimation. We usethis data to develop the prediction system for trafficcongestion in order to improve the quality and safetyof vehicle movement and for minimization the timeand costs when vehicles are moved at the specifiedroutes. We collect the GPS data and classify themwith K-Means algorithm. Moreover, framework basedon Markov model is used to predict traffic andHadoop is used as cloud storage and platform, toaccelerate the processing computing speed and allow handling of large-scale data."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Traffic Prediction"},{"interim":"GPS"},{"interim":"Markov"},{"interim":"Hadoop"},{"interim":"MapReduce"},{"interim":"K-Means"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-02"}],"displaytype":"preview","filename":"12013.pdf","filesize":[{"value":"118 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4803/files/12013.pdf"},"version_id":"e03631ec-8589-42f8-8cce-3d76aca37eec"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Lwin, Hnin Thant"},{"subitem_authors_fullname":"Naing, Thinn Thu"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2014-02-17"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/70"},"item_title":"Prediction System for Traffic Congestion using GPS Data on Hadoop Cloud Storage","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-02","publish_status":"0","recid":"4803","relation_version_is_last":true,"title":["Prediction System for Traffic Congestion using GPS Data on Hadoop Cloud Storage"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T08:08:09.677555+00:00"}