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Friday, 23 February 2018

Collaborative Sensing to Improve Information Quality for Target Tracking in Wireless Sensor Networks(2010)

Collaborative Sensing to Improve 

Information Quality for Target 

Tracking in Wireless Sensor


Due to limited network resources for sensing,communication and computation, information quality (IQ) in awireless sensor network (WSN) depends on the algorithms and protocols for managing such resources. In this paper, for target tracking application in WSNs consisting of active sensors (such as ultrasonic sensors) in which normally a sensor senses the environment actively by emitting energy and measuring the reflected energy, we present a novel collaborative sensing scheme to improve the IQ using joint sensing and adaptive sensor scheduling. With multiple sensors participating in a single sensing operation initiated by an
emitting sensor, joint sensing can increase the sensing region of an individual emitting sensor and generate multiple sensor measurements simultaneously. By adaptive sensor scheduling,
the emitting sensor for the next time step can be selected adaptively according to the predicted target location and the detection probability of the emitting sensor. Extended Kalman filter (EKF) is employed to estimate the target state (i.e., the target location and velocity) using sensor measurements and to predict the target location. A Monte Carlo method is presented to calculate the detection probability of an emitting sensor. It is demonstrated by simulation experiments that collaborative sensing can significantly improve the IQ, and hence the tracking accuracy, as compared to individual sensing.
Existing System:
A serious problem in WSN of active sensors is the inter-sensor interference (lSI) when nearby ultrasonic sensors emit sound wave simultaneously. Such interference will result in erroneous sensor readings and must be dealt with properly. lSI also introduces a new technological constraint in the design and implementation of a WSN. In this paper, we assume the WSN is deployed in a small area where the sensor nodes are in the interference range of each other, and only single target tracking is considered. To avoid lSI, at each time step, only one emitting sensor will be scheduled and the other sensors will participate in joint sensing with the scheduled emitting sensor.
Proposed System:
A novel collaborative sensing scheme is proposed for target tracking application in WSNs by joint sensing and adaptive sensor scheduling. The proposed scheme can increase the detection region of an individual sensor and introduce more simultaneous sensor measurements for a single sensing operation. It is shown by simulations that the IQ of the WSN can be improved significantly using joint sensing. Future research issues include sensor scheduling for joint sensing for large scale WSNs, adaptive tracking algorithms for high maneuvering targets, joint sensing for multi-target tracking, as well as real test-bed development.
Modules :
  • Target tracking
  • Joint sensing
  • Sensor scheduling
  • Collaborative sensing
Hardware Requirements:
• Processor                     : Pentium-III (or) Higher
• Ram                           : 64MB (or) Higher
• Cache                         : 512MB
• Hard disk                    : 10GB 
Software requirements:
  • Technologies                           : Java and J2EE
  • Web Technologies                   : HTML,CSS,JavaScript
  • Database                                 : Oracle10g
  • JDK Version                           : JDK1.5
  • Server                                      : Tomcat5.5

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