Information Content-Based Sensor Selection and Transmission Power Adjustment for Coll
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I am anusha i want to know about this project overview and ideas
about Information Content-Based Sensor Selection and Transmission Power Adjustment for Collaborative Target Tracking

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#2
Abstract

For target tracking applications, wireless sensor nodes provide accurate information since they can be deployed and operated near the phenomenon. These sensing devices have the opportunity of collaboration among themselves to improve the target localization and tracking accuracies. An energy-efficient collaborative target tracking paradigm is developed for wireless sensor networks (WSNs). A mutual-information-based sensor selection (MISS) algorithm is adopted for participation in the fusion process. MISS allows the sensor nodes with the highest mutual information about the target state to transmit data so that the energy consumption is reduced while the desired target position estimation accuracy is met. In addition, a novel approach to energy savings in WSNs is devised in the information-controlled transmission power (ICTP) adjustment, where nodes with more information use higher transmission powers than those that are less informative to share their target state information with the neighboring nodes. Simulations demonstrate the performance gains offered by MISS and ICTP in terms of power consumption and target localization accuracy.
For more:
http://computerportal/web/csdl/doi/10.1109/TMC.2009.12
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#3
presented by:
Afsal C
Salman C

[attachment=8964]
Information Content-Based Sensor Selection and Transmission Power Adjustment for Collaborative Target Tracking
EXISTING SYSTEM
Target tracking sensor networks monitor and track the movement of a target object. Energy management in these sensor networks is crucial to prolong the network lifetime. Protocol EST (energy saving schedule for target tracking sensor networks) that provides a dynamic sleep schedule for the radios such that maximum energy is saved without affecting the sensors' activities. When there is no target, the communication modules of sensor nodes are put into sleep using a static schedule, except the border nodes.
PROPOSED SYSTEM
A mutual-information-based sensor selection (MISS) algorithm is adopted for participation in the fusion process. MISS allows the sensor nodes with the highest mutual information about the target state to transmit data so that the energy consumption is reduced while the desired target position estimation accuracy is met.
MODULES
• DATA PROCESSING ARCHITECTURE
> We define the process model for the target motion.
> The next state of the target is calculated with the knowledge of its current state and the target state transition matrix.
* Process Model
> The process model describes the target motion.
> The process model finds the state of the target at time instant k + 1 given the state of the target at time instant k.
* Observation Model
> Noise is added to the real target state in order to model the sensor observation uncertainties
• MAXIMUM MUTUAL-INFORMATION-BASED SENSOR SELECTION ALGORITHM
Mutual information measures how much uncertainty is removed by one random variable about another one. Bycomputing the mutual information between the target stateand the measurement, one can gain insight as to how much the current observation tells about the current target state.
• INFORMATION-CONTROLLED TRANSMISSION POWER ADJUSTMENT
This ICTP adjustment scheme is the energy-saving strategy, in addition to the MISS algorithm.
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#4

Information Content-Based Sensor Selection and Transmission Power Adjustment for Collaborative Target Tracking
Abstract:

For target tracking applications, wireless sensor nodes provide accurate information since they can be deployed and operated near the phenomenon. These sensing devices have the opportunity of collaboration among themselves to improve the target localization and tracking accuracies. An energy-efficient collaborative target tracking paradigm is developed for wireless sensor networks (WSNs). In addition, a novel approach to energy savings in
WSNs is devised in the information-controlled transmission power (ICTP) adjustment, where nodes with more information use higher
transmission powers than those that are less informative to share their target state information with the neighboring nodes.
Algorithm / Technique used:
ICTP Method.
Algorithm Description:
The ICTP scheme is embodied in the power adjustment logic module in which a node consults the mutual information list index of the sensor node and the preset power adjustment pattern, and subsequently, decides on the transmission power for communicating its information state and information matrix denominations to the network.
Existing System:
Target tracking sensor networks monitor and track the movement of a target object. Energy management in these sensor networks is crucial to prolong the network lifetime. Protocol EST (energy saving schedule for target tracking sensor networks) that provides a dynamic sleep schedule for the radios such that maximum energy is saved without affecting the sensors' activities. When there is no target, the communication modules of sensor nodes are put into sleep using a static schedule, except the border nodes. Interior nodes do not perform the sensing activity in the surveillance state. If a target arrives, the sleep schedule for the radios is changed dynamically in order to send the arrival message to neighboring sensors. By receiving the arrival message, the sleeping neighbor nodes start sensing. The objectives of our protocol are to (1) balance the lifetime of all the sensor nodes in the network to increase the network lifetime (2) reduce the energy consumption by activating the sensors only when the target arrives in that region.
Proposed System:
A mutual-information-based sensor selection (MISS) algorithm is adopted for participation in the fusion process. MISS allows the sensor nodes with the highest mutual information about the target state to transmit data so that the energy consumption is reduced while the desired target position estimation accuracy is met.
Modules:
1. Networking Module.
2. Sensor selection module.
3. ICTP Module.
4. Target tracking Module.
5. Average energy consumed module.
Module Description:
1. Networking Module.

Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.
2. Sensor selection module.
The sensor selection problem only in terms of coverage and energy-saving aspects, without paying attention to detection quality. In tracking applications, when selecting the subset of sensor nodes to contribute to the global decision, we have to consider how informative the sensor nodes are about the state of the target.
3. ICTP Module.
INFORMATION-CONTROLLED TRANSMISSION POWER ADJUSTMENT (ICTP) adjustment scheme as the energy-saving strategy, in addition to the MISS algorithm. The block diagram representation of the sensor node whose task is distributed target tracking with MISS and ICTP. Sensory observation is transferred to the information extractor module to retrieve the information state and the information matrix denomination values from the received observation using (5), which are then passed to the local information filter module where local target tracking takes place according to the operations
4. Target tracking Module.
Deficiency with this approach occurs for tracking applications if all the sensor node local likelihood ratios fall in the no-send region and no belief about the target state is shared among the nodes. In this paper, we concentrate on the WSN part of the C4ISR application depicted in Fig. 1. Sensor nodes try to collaboratively maintain accurate target position and speed estimates to report to the UAV in an energy-efficient manner. We consider the problem of tracking a single target using immobile sensor nodes that collaborate with each other through a broadcast communication mechanism.
5. Average energy consumed module.
If we adjust the transmission powers of the sensor nodes according to
Pattern 3, on average, we achieve 2.14 times less energy usage with respect to the case in which no transmission power adjustment is made .However, power adjustment, on average, doubles the target localization errors as observed .The gain in terms of the exhausted communication energy does not compensate the increase in the target localization error. Hence, reducing the communication transmission power is not desirable.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 256 Mb.
Software Requirements:
• Operating system : - Windows XP Professional.
• Front End : - Asp .Net 2.0.
• Coding Language : - Visual C# .Net.
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