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A Multi-agent Model...
A Multi-agent Model for Fire Detection in Coal Mines using Wireless Sensor Networks
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- Khan, Zeshan Aslam (author)
- Högskolan i Halmstad,Akademin för informationsteknologi,International Islamic University, Islamabad, Pakistan
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- Pignaton de Freitas, Edison, 1979- (author)
- Högskolan i Halmstad,Centrum för forskning om inbyggda system (CERES)
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- Larsson, Tony, 1950- (author)
- Högskolan i Halmstad,Centrum för forskning om inbyggda system (CERES)
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- Abbas, Haider (author)
- King Saud University, Riyadh, Saudi Arabia
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(creator_code:org_t)
- Los Alamitos, CA : IEEE Computer Society, 2013
- 2013
- English.
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In: 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications. - Los Alamitos, CA : IEEE Computer Society. - 9780769550220 ; , s. 1754-1761
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- This paper presents an application for monitoring and detection of fire in coal mines using wireless sensor networks (WSNs). The application uses BDI (Belief, Desire and Intention) based multi-agent model and its implementation on sensor networks. The language used for implementation is interpreted by Jason; an extension of AgentSpeak which is based on the BDI Architecture. The BDI agents are reactive planning systems; systems that are not meant to compute the value of a function and terminate but rather designed to be permanently running and reacting to some form of event. The distributed model of the environment is adopted to overcome the communication overhead, power consumption, network delay and reliability on a centralized base station. © 2013 IEEE.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
Keyword
- Wireless Sensor Networks
- AgentSpeak
- Distributed
- Overhead
- Consumption
- Reliability
- Centralized
Publication and Content Type
- ref (subject category)
- kon (subject category)
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