Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Tayyab SalmanSEECSUndergraduateFourthtsalman.bscs15seecs@seecs.edu.pk
1Haseeb AhmadSEECSUndergraduateFourthhaahmad.bscs15seecs@seecs.edu.pk
1Nauman LiaqatSEECSUndergraduateFourthnliaqat.bscs15seecs@seecs.edu.pk

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: Urban Moves
Slogan: Smart Urban Planning
Supervisor Name: Dr. Omar Arif
Supervisor Designation: HOD - SE / Asst Professor
Supervisor School: School of Electrical Engineering and Computer Sciences
Supervisor Department: Software Engineering
Contact number: 9085-2167 (Office No.)
Email ID: omar.arif@seecs.edu.pk
Abstract:
    Predicting traffic flow and intensities at varying times and weather conditions to make Smart Urban Planning through services such as route optimization and better positioning of advertisements etc.
What is the unmet need in society that your idea will fulfill ?
    This project will mine places that are most suitable for advertisement, as well as it can be used to plan Urban City like better positioning of police staff, ambulance route optimization etc. It will also be used to predict traffic flow. Data collected for this project is from public domain.
Who needs it ? How many would benefit ?
   Real estate businessmen and different companies can use this project, so that they'll attract maximum public. Ambulances can use this for best route optimization. Government can use this project for better positioning of police staff.
How will the solution works
    This project aims to collect real time images from google maps at varying time and weather conditions at different possible points (17231) of roads in Islamabad. Traffic intensities data was obtained by applying image processing techniques on these images. Besides this, weather, temperature and time are also recorded to train the model. Prediction has been done by using classifier 'Decision trees'. Accuracy achieved by us is 90%.
Who are your competitors ? How is your solution different
    Google is our competitor. Our solution is different from that of theirs, because we are doing prediction by using only few parameters i.e. temperature, weather, time, longitude and latitude and by using this, accuracy of 90% is obtained. But Google have huge amount of data that they usually use.
Status: new
Entry Date & Time: 2018-12-26 (1829)