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Design and implementation of system prediction and traffic conditions visualization in two dimensional map (Case study: Bandung city)
Anggraini D.a, Siswantoko W.a, Henriyan D.a, Subiyanti D.P.a, Aziz M.V.G.a, Prihatmanto A.S.a
a Control and Computer System Laboratory, School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2016 IEEE.Traffic jam today in the city is one of the focus from the government, because it has a very big impact, from wasting a lot of time, the fuel until air pollution. Searching information about traffic conditions in the city has been widely available through the Twitter account @infobdg, with hashtag #lalinbdg and from the website bandung247.com. However, the rapid development of online information services resulted in the lack of time to read the complete information and for extracting the right information. To resolve these problems, it is necessary to design and implementation the visualization of traffic conditions in the form of map, which the information obtained from Twitter, cctv, user and operator prfm (the radio information about traffic conditions in Bandung). And then designing the predictive system for traffic conditions based on information from Twitter, so the people can predict traffic conditions for one week ahead. Making the visualization begins with taking a summary of the information that will be used for the visualization on the map. From the information Twitter, cctv, user and operator has been able to display traffic conditions in real time and predictive traffic conditions to allow users to know the traffic conditions.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Complete information,Design and implementations,Online information services,Predictive systems,Real time,Time series prediction,Traffic conditions,Two-dimensional map[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]extract traffic condition,real time chat,time series prediction,visualization[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/FIT.2016.7857544[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]