Telemetry Data Mining Techniques, Applications, and Challenges

Telemetry Data Mining Techniques, Applications, and Challenges

Sara Ahmed (Al Azhar University, Egypt & Scientific Research Group in Egypt (SRGE), Egypt), Tarek Gaber (Suez Canal University, Egypt & Scientific Research Group in Egypt (SRGE), Egypt) and Aboul Ella Hassanien (Cairo University, Egypt & Scientific Research Group in Egypt (SRGE), Egypt)
Copyright: © 2017 |Pages: 10
DOI: 10.4018/978-1-5225-2229-4.ch040
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Abstract

The most recent rise of telemetry is around the use of Radio-telemetry technology for tracking the traces of moving objects. Initially, the radio telemetry was first used in the 1960s for studying the behavior and ecology of wild animals. Nowadays, there's a wide spectrum application of can benefits from radio telemetry technology with tracking methods, such as path discovery, location prediction, movement behavior analysis, and so on. Accordingly, rapid advance of telemetry tracking system boosts the generation of large-scale trajectory data of tracking traces of moving objects. In this study, we survey various applications of trajectory data mining and review an extensive collection of existing trajectory data mining techniques to be used as a guideline for designing future trajectory data mining solutions.
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Trajectory Data Model

A spatial trajectory is a trace generated by a moving object in geographical spaces, which is consisting of an ordered set of spatiotemporal points (Frentzos, 2007). This can be defined for any trajectory “T” which can be seen as an ordered set of spatiotemporal points consisting of 3 dimensions: location in terms of x-coordinate “x”, y-coordinate “y” and temporal dimension in terms of time “t” This is formally defined as, and can be seen in Figure1, (Al-Serafi, 2015)

(1)
Figure 1.

Trajectory consisting of “n” points

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Application Of Trajectory Data Mining

There exists a wide spectrum of applications driven and improved by trajectory data mining, such as; knowing moving objects locations in advance can be substantial. Discovery of behavioral patterns and prediction of future movement can greatly influence different fields, such as analysis of the wild animals’ movement in order to predict their migrations, monitoring and analysis of vehicle movement in order to predict traffic congestions, mobile user movement and access point availability prediction in order to assure the requested level of quality of service or analysis and location prediction of the movement of aircrafts or space crafts (Ivana, 2006). In the section, we classify these applications based on the derivation of trajectories categories. The derivation of trajectories can be classified into four major categories, mobility of people, mobility of animals, mobility of vehicles and mobility of natural phenomena.

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