Road traffic congestion is a world-wide issue, especially, severe in the developing world which needs specific attention because of the contrasting nature of traffic as compared to developed countries. Traffic in developing countries, like India, is often chaotic with ineffective lane systems and much higher variability in size and speed of vehicles. While the use of public transportation is highly desirable, but uncertainty and overcrowding hinders its effectiveness. This calls for the need of Intelligent Transportation Systems especially designed for developing countries, like India. The project aims to construct an overarching communication framework that can help ease congestion, while also making it much easier for commuters to use public transportation, by harnessing the capabilities of wireless communication and mobile devices. In the project mobile-phone based sensing techniques are being developed and tested under various chaotic road conditions, and are being optimized for metrics such as the mobile’s power consumption. On-road static sensing techniques are also being developed and enhanced. A flexible and scalable Information gathering & dissemination framework is being developed, to collect the (crowdsourced) information centrally, via Mobile internet, WiFi & SMS, as well as disseminate it to interested users. Machine learning techniques are being used to deduce information from the gathered sensor data, and also to develop techniques for identification and elimination of noise/malicious data in crowd-sourced information. Example applications using the CARTS system, will be developed for Android & iOS based smart phone and also for basic phones.
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Remarks: Enrolment 20/semester; offered: 04 times
Links/URL: http://itra.dic.gov.in/data/Documents/CARTS/Project%20Report/20180613171059-Annexure%201%20_%20PEC.docxRemarks: To be offered in the forthcoming semester
Title: Mobile Application Development for undergraduates Remarks: PEC and UIET
Enrolment: 7
Remarks: Enrollment - 8
Links/URL: http://uiet.puchd.ac.in/dic/index.php/inhouse-project/workshopseminar/Remarks: Avg. enrolment per offering: 8
Links/URL: http://uiet.puchd.ac.in/dic/index.php/inhouse-project/workshopseminarRemarks: Date: Jan-Mar 2015
Title: Computer Networks, CSPIT (Gujarat)Remarks: Date: Mar 2015
Title: QEEE course, Comp. Networks, Comp. ArchRemarks: Date: Mar 2015
Title: YCCE (Nagpur), Computer NetworksRemarks: Date: Oct 2015
Title: Expert Talk on IoT Remarks: Participants: 60
Date: 17 April 2017
Remarks: Participants: 15
Date: 24 October 2017
Remarks: Participants: 25
Date: 31 October-11 November 2017
Remarks: Participants: 22
Date: 19-23 December 2017
Remarks: Participants: 50
Year:2015
Remarks: Participants:23
Date: 2-3 September 2017
Remarks: Participants:10
Date: 18 Decemmber 2017
Remarks: Year: 2018;
Audience: 300 school children from the tri city
Remarks: Tic Tic: Find my bus (Mobile App to prdict ETA for CTU buses)
Year: 2016;
Audience: 310 school children from the tri city
Remarks: Collaboration Area:Experimenting with OBDs
Title: MicrosoftRemarks: Collaboration Area: Research & Development Mentorhsip
Title: Mobond: m-indicator appRemarks: Collaboration Area: Interactions on real-time bus/train tracking
Remarks: Collaboration Area: Launch of ETA CTU buses Mobile App
Title: Chandigarh PoliceRemarks: Collaboration Area: Jointly developing App for Detecting Road Accidents
Title: CERTRemarks: Collaboration Area: School bus GPS data
Title: BMTCRemarks: Collaboration Area: Shared their GPS data for analysis
Title: MSRIRemarks: Collaboration Area: Road safety aspects
Title: MHRD: Design & Innovation CenterRemarks: Mobile App developed for detecting the various traffic states, and the commuting modes using acoustics.
Title: E-rickshawRemarks: Mobile App developed for Panjab University by tracking location without GPS
Title: RoadResQRemarks: Mobile App developed for detecting road accidents and promoting safe driving (transferred to Chandigarh Police)
Remarks: Offered to: Chandigarh Smart City Project
1. | Smartphone based traffic state detection using acoustic analysis and crowdsourcing |
2. | A Review on Acoustic Vehicular Classification |
3. | Traffic state detection using smartphone based acoustic sensing |
4. | BaroTrack: Low cost tracking of commuter on road |
5. | A smartphone-based technique to monitor driving behavior using DTW and crowdsensing |
6. | Smart patrolling: An efficient road surface monitoring using smartphone sensors and crowdsourcing |
7. | ETA HTC: Estimating time of arrival under heterogeneous traffic conditions using crowdsensing |