Sensor Assignment to Missions: A Natural Language Knowledge-Based Approach

Preece, Alun

doi:10.1007/978-3-319-91146-5_7

Cited by 1 publication

(1 citation statement)

References 18 publications

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“…Preece [10] have worked with assignment of sensors to missions by following a natural language based approach. They base their work on a market architecture for sensor management built around a computational economy.…”

Section: Related Workmentioning

confidence: 99%

IFAA: An Intelligent Framework Aware Algorithm to Determine the Boundary of Area under Attack in Military Surveillance and Reconnaissance WSN

Raj¹,

Babu²

2022

RIA

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Wireless sensor networks (WSNs) have proven effective in military applications of surveillance and reconnaissance. Sensors capable of detecting pressure, temperature, movement and presence of specific chemicals are deployed in such applications. Traditionally, sensor data is collected and transferred to a centralized high-capacity node or control station. Analysis of data is carried out at such centralized facilities. Information or intelligence gathered from sensor data after analysis is used to generate control and management commands that are relayed back to sensor nodes. The situation is analogous to an actual wartime scenario where soldiers who are on the field are equivalent to the sensors. Soldiers observe and sense the situation and communicate their observations to the decision maker who is stationed in the control tent. On gathering field information, the decision maker analyses the data and arrives at his decision which is again communicated to the soldiers on the field. Soldiers as well as sensors are not placed illogically or randomly but intentionally and strategically. Observations made on the field ultimately affect how the soldiers or sensors continue to function. Intelligence gained on the field ultimately gets used on the field itself. Our attempt is to observe, analyze and apply intelligence on the field itself. This work proposes an intelligent algorithm that is aware of the sensor network topology, analyses sensor data within the network and uses the network framework to arrive at usable intelligence. Locally generated intelligence avoids communication to and from the command/control and adds value to military surveillance and reconnaissance applications of WSN. Intelligent sensor management allows us to use just the necessary number of sensors while saving resources on otherwise redundant expenditure. In the present work we have designed and applied a dynamic boundary computation algorithm to determine the boundary of the area under attack. We have compared the results of simulation experiments incorporating the proposed algorithm against a control experiment without the algorithm.

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Section: Related Workmentioning

confidence: 99%