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Conference Papers Year : 2017

Customizable Vehicle Tracking with Intelligent Prediction System

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Abstract

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.
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Dates and versions

hal-01768537 , version 1 (17-04-2018)

Licence

Attribution - CC BY 4.0

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Dhanasekar Sundararaman, Gowtham Ravichandran, R. Jagadeesh, S. Sasirekha, I. Joe Louis Paul, et al.. Customizable Vehicle Tracking with Intelligent Prediction System. 16th Conference on e-Business, e-Services and e-Society (I3E), Nov 2017, Delhi, India. pp.298-310, ⟨10.1007/978-3-319-68557-1_27⟩. ⟨hal-01768537⟩
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