Intelligent Car Localization with the Use of Andruino Platform and Cloud Storage

Nowadays the possibility to localize a car is a frequently used method for completion of log-book, analysis of company car effectivity, or most importantly as a part of car security systems in the case of their theft. The proposed solution is designed on financially affordable components and platform-independent open-source software. Thanks to intelligent behaviour of the proposed solution which uses cloud storage and freely accessible Google Earth maps, the solution is competitive not only due to its low acquisition costs, but chiefly because of its operating costs and platform independence.

[1]  Henry Kautz,et al.  Building Personal Maps from GPS Data , 2006, Annals of the New York Academy of Sciences.

[2]  Annette Mossel,et al.  Autonomous Flight using a Smartphone as On-Board Processing Unit in GPS-Denied Environments , 2013, MoMM '13.

[3]  Tinghuai Ma,et al.  Real time services for future cloud computing enabled vehicle networks , 2011, 2011 International Conference on Wireless Communications and Signal Processing (WCSP).

[4]  Girma S. Tewolde,et al.  Tour guide robot using wireless based localization , 2013, IEEE International Conference on Electro-Information Technology , EIT 2013.

[5]  Girma Tewolde,et al.  Design and implementation of vehicle tracking system using GPS/GSM/GPRS technology and smartphone application , 2014, 2014 IEEE World Forum on Internet of Things (WF-IoT).

[6]  T. Hashizume,et al.  A study of precise road feature localization using mobile mapping system , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.

[7]  Michael Himmelsbach,et al.  Autonomous Ground Vehicles—Concepts and a Path to the Future , 2012, Proceedings of the IEEE.

[8]  Enrique V. Carrera,et al.  Acoustic event localization on an Arduino-based wireless sensor network , 2014, 2014 IEEE Latin-America Conference on Communications (LATINCOM).

[9]  Peter Brida,et al.  Proposal of User Adaptive Modular Localization System for Ubiquitous Positioning , 2012, ACIIDS.

[10]  Blanka Klimova,et al.  Investment evaluation of cloud computing in the European business sector , 2015 .

[11]  Peter Brida,et al.  Modular Localization System for Intelligent Transport , 2014, Recent Developments in Computational Collective Intelligence.

[12]  Maan El Badaoui El Najjar,et al.  A Road-Matching Method for Precise Vehicle Localization Using Belief Theory and Kalman Filtering , 2005, Auton. Robots.