Mining sensor and mobility data in cyber-physical systems
type: CreativeWork
description: A Cyber-Physical System (CPS) is an integration of physical devices with informational resources. Such a system has many promising applications in both military and civil fields, such as missile defense, battlefield awareness, traffic control, neighborhood watch, environment monitoring and wildlife tracking. The objective of this thesis is to advance the data mining techniques in the novel applications of CPS, and complete the tasks of knowledge discovery by integrating the various properties of physical-world with the information components in cyber-world. This thesis introduces the author's studies on sensor and mobility data mining with CPS applications. First, this thesis investigates the problem of discovering intruders' trajectories from noisy sensor data (i.e., mining lines in the sand). With a large number of sensors (sand) deployed in a designated area, the CPS is required to discover all the trajectories (lines) of passing intruders in real time. There are two crucial challenges that need to be addressed: (1) the collected sensor data are not trustworthy; (2) the intruders do not send out any identity information. The system needs to distinguish multiple intruders and track their movements in real time. This study proposes a method called LiSM (Line-in-the-Sand Miner) to discover trajectories from untrustworthy sensor data. LiSM constructs a model of watching network from sensor data and computes the locations of intruder appearances based on the link information of the network. LiSM retrieves a cone-model from the historical trajectories and tracks multiple intruders based on this model. Then the system validates the mining results and updates sensors' reliability scores in a feedback process. In addition, LoRM (Line-on-the-Road Miner) is proposed for trajectory discovery on road network, (i.e., mining lines on the roads). LoRM employs a filtering-and-refinement framework to reduce the distance computational overhead on road network, and uses a shortest-p…
abstract: A Cyber-Physical System (CPS) is an integration of physical devices with informational resources. Such a system has many promising applications in both military and civil fields, such as missile defense, battlefield awareness, traffic control, neighborhood watch, environment monitoring and wildlife tracking. The objective of this thesis is to advance the data mining techniques in the novel applications of CPS, and complete the tasks of knowledge discovery by integrating the various properties of physical-world with the information components in cyber-world. This thesis introduces the author's studies on sensor and mobility data mining with CPS applications. First, this thesis investigates the problem of discovering intruders' trajectories from noisy sensor data (i.e., mining lines in the sand). With a large number of sensors (sand) deployed in a designated area, the CPS is required to discover all the trajectories (lines) of passing intruders in real time. There are two crucial challenges that need to be addressed: (1) the collected sensor data are not trustworthy; (2) the intruders do not send out any identity information. The system needs to distinguish multiple intruders and track their movements in real time. This study proposes a method called LiSM (Line-in-the-Sand Miner) to discover trajectories from untrustworthy sensor data. LiSM constructs a model of watching network from sensor data and computes the locations of intruder appearances based on the link information of the network. LiSM retrieves a cone-model from the historical trajectories and tracks multiple intruders based on this model. Then the system validates the mining results and updates sensors' reliability scores in a feedback process. In addition, LoRM (Line-on-the-Road Miner) is proposed for trajectory discovery on road network, (i.e., mining lines on the roads). LoRM employs a filtering-and-refinement framework to reduce the distance computational overhead on road network, and uses a shortest-p…
author: Tang, Lu An
language: en
keywords: data mining, cyber-physical system, trajectory mining, sensor network
date published: 2014-01-16T18:17:52Z
date modified: 2026-07-22T22:25:38Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/46836