Traffic Analysis and Prediction Application for Dhaka City Using Clustering and Association Rule Mining and Activity Recognition Using Logistic Regression

Simple item page
dc.contributor.advisorDr. M. Rashedur Rahman
dc.contributor.authorMuyeed Ahmed
dc.contributor.authorMir Tahsin Imtiaz
dc.contributor.authorRaiyan Khan
dc.contributor.id1411256042
dc.contributor.id1330220042
dc.contributor.id1411815042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-08-24
dc.date.accessioned2025-08-24T08:43:43Z
dc.date.available2025-08-24T08:43:43Z
dc.date.issued2017-12-31
dc.description.abstractTraffic is one of the major problems for any populated city. Currently, there are many traffic alert systems available and almost all of them work with user submitted inputs to give those alerts. We worked on developing a system that will not depend on any user’s manual input but it will be able to retrieve traffic and activity related data from the user’s device and vehicle tracking devices automatically in order to use that data to predict traffic and alert users. Our system tries to understand the user’s activity using accelerometer sensor data and speed to determine whether the user is sitting at home or going somewhere by a bus or car. Once it is verified that the particular user’s location and activity is related to traffic conditions, it takes that user’s location related data from his or her device. Using this data from user’s devices and the data from vehicle tracking devices, we intended to predict the traffic conditions and let users know about the traffic for particular routes.
dc.description.degreeUndergraduate
dc.identifier.cd600000257
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1399
dc.language.isoen_US
dc.publisherNorth-south University
dc.rights@ NSU Library
dc.titleTraffic Analysis and Prediction Application for Dhaka City Using Clustering and Association Rule Mining and Activity Recognition Using Logistic Regression
dc.typeProject
oaire.citation.endPage81
oaire.citation.startPage1
Files
Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
600000257-abstract.pdf
Size:
140.67 KB
Format:
Adobe Portable Document Format
Description:
Download
Thumbnail Image
Name:
600000257.pdf
Size:
2.6 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.93 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
Theses - Undergraduate