Bhulakshmi Bonthu ¹, Arunava Kar ¹, J. Jabanjalin Hilda ¹

Affiliations
1 School of Computer Science and Engineering, Vellore Institute of Technology, Vellore – 632014, Tamil Nadu, IN

Abstract

The process of detecting stolen vehicles on roads has become very difficult due to increase in the number of vehicles. The proposed technique facilitates the circumstance and aides in finding the stolen vehicles by using intelligent systems. The method is implemented using Radio Frequency IDentification (RFID) tags, Unique IDentification (UID) code, microcontroller, Arduino and LCD display. The modules incorporated extract the UID code from RFID tag and compare with the UID which is already present in database. In the case of matching, the stolen vehicle will be detected and information will be displayed to the administrator at toll plaza. The deployment of this method will provide the details of stolen vehicles without direct contact of vehicles. It has many advantages such as high precision and the system can work under extensive environment and recites from long distance.

Keywords

Arduino, Microcontroller, Protection, RFID, UID, Vehicle, Warning.

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J. Jabanjalin Hilda ¹, C. Srimathi ¹, Bhulakshmi Bonthu ¹

Affiliations
1 School of Computing and Engineering, Vellore Institute of Technology, Katpadi - 632014, Vellore, Tamil Nadu, IN

Abstract

Objectives: Data visualization, the use of images to represent information, is now becoming properly appreciated due to the benefits it can bring to business. This paper focuses on the general background of data visualization and visualization techniques. Methods: Data visualization has the prospective to assist humans in analysing and comprehending large volumes of data, and to detect patterns, clusters and outliers that are not obvious using non-graphical forms of presentation. For this reason, data visualizations have an important role to play in a diverse range of applied problems, including data exploration and mining, Information retrieval and intelligence analysis. In real time various techniques have been used of which Geometric projection techniques, Iconographic display techniques, Pixel-oriented, Hierarchical techniques, Graph-based techniques are discussed. Findings: The major difficultly in big data visualization is to preserve any of the original dimensional information. The taxonomy detailed here show that the local and global structure of the data can be visualized in an interactive manner and has a massive advantage.

Keywords

Parallel Coordinates, Star Coordinates, Visual Analytics, Visualization Techniques.

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