%0 Conference Proceedings
%T Customizable Vehicle Tracking with Intelligent Prediction System
%+ Sri Sivasubramaniya Nadar College of Engineering (SSN College of Engineering)
%+ Anna University
%A Sundararaman, Dhanasekar
%A Ravichandran, Gowtham
%A Jagadeesh, R.
%A Sasirekha, S.
%A Joe Louis Paul, I.
%A Swamynathan, S.
%Z Part 3: Analytics for Smart Governance
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 16th Conference on e-Business, e-Services and e-Society (I3E)
%C Delhi, India
%Y Arpan Kumar Kar
%Y P. Vigneswara Ilavarasan
%Y M. P. Gupta
%Y Yogesh K. Dwivedi
%Y Matti Mäntymäki
%Y Marijn Janssen
%Y Antonis Simintiras
%Y Salah Al-Sharhan
%I Springer International Publishing
%3 Digital Nations – Smart Cities, Innovation, and Sustainability
%V LNCS-10595
%P 298-310
%8 2017-11-21
%D 2017
%R 10.1007/978-3-319-68557-1_27
%K Vehicle tracking
%K Prediction methods
%K Artificial neural networks
%K Global positioning system
%K Databases
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X In this work, an efficient vehicle tracking with intelligent prediction system is designed and implemented for tracking the movement of any vehicle from any location. The proposed system uses an inexpensive technology that combines a smartphone application with a microcontroller. The users will be able to continuously monitor a moving vehicle on demand using the smartphone application and determine the estimated distance and time for the vehicle to arrive at a chosen destination. Apart from this, the system is designed further to account for the case of failing to catch one’s vehicle by dynamically suggesting a new vehicle within one’s reach with an estimated time and a route. The data collected using the tracking system is effectively used to predict the estimated arrival time of the vehicles using sophisticated machine learning technique Artificial Neural Networks (ANN). While there are other systems on vehicle tracking, we present a vehicle tracking, dynamic route suggestion on failing to catch one’s vehicle and intelligent arrival time prediction system together making it a comprehensive system for users. The feasibility and effectiveness of the system are presented through experimental results of the vehicle tracking system with the advantages and challenges.
%G English
%Z TC 6
%Z WG 6.1
%2 https://inria.hal.science/hal-01768537/document
%2 https://inria.hal.science/hal-01768537/file/978-3-319-68557-1_27_Chapter.pdf
%L hal-01768537
%U https://inria.hal.science/hal-01768537
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-1
%~ IFIP-I3E
%~ IFIP-LNCS-10595