The Fundamentals and Empirical Design of a Smart Fire Detection System

This book introduces a smart fire detection system designed using a wireless sensor network and fuzzy methods. This system predicts, controls, and provides alerts to various events based on intelligent techniques. Routing protocols are performed based on intelligent procedures in which they are clas...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Gharajeh, Mohammad Samadi
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newcastle-upon-Tyne : Cambridge Scholars Publisher, 2020.
Temas:
Fire detectors > Technological innovations.
Wireless sensor networks.
Réseaux de capteurs sans fil.
Artificial intelligence.
Computer networking & communications.
Fire protection & safety.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Table of Contents
  • Acknowledgements
  • Preface
  • Introductory note
  • Chapter One
  • 1.1. Introduction
  • 1.2. Overall structure of sensor networks
  • 1.3. Node structure
  • 1.4. Protocol stack
  • 1.5. Wireless sensor network applications
  • 1.6. Conclusion
  • Chapter Two
  • 2.1. Introduction
  • 2.2. Simulator architecture
  • 2.3. Main features of the network simulator
  • 2.4. Simulation tools
  • 2.4.1. NS-2
  • 2.4.2. OMNeT++
  • 2.4.3. J-Sim
  • 2.4.4. NCTUns
  • 2.4.5. GloMoSim
  • 2.4.6. SSFNet
  • 2.4.7. Ptolemy II
  • 2.4.8. Prowler
  • 2.4.9. TOSSIM
  • 2.4.10. OPNET
  • 2.4.11. WSN Localization Simulator
  • 2.4.12. Mannasim
  • 2.4.13. SensorSim
  • 2.4.14. SENSE
  • 2.4.15. MATLAB/Simulink
  • 2.5. Conclusion
  • Chapter Three
  • 3.1. Introduction
  • 3.2. SmokeNet
  • 3.3. FINDER
  • 3.4. Automatic fire alarm system based on wireless sensor networks
  • 3.5. Embedded neural network for fire classification
  • 3.6. Some hardware devices of fire detection systems
  • 3.6.1. Temperature sensor
  • 3.6.2. Humidity sensor
  • 3.6.3. Light intensity sensor
  • 3.6.4. Wireless transceiver
  • 3.7. Conclusion
  • Chapter Four
  • 4.1. Introduction
  • 4.2. Classical logic
  • 4.3. Fuzzy logic
  • 4.4. Conclusion
  • Chapter Five
  • 5.1. Introduction
  • 5.2. System architecture
  • 5.2.1. Overall view
  • 5.2.2. Types of environments
  • 5.2.2.1. Closed environment
  • 5.2.2.2. Open environment
  • 5.2.2.3. Data transmission process
  • 5.2.3. Identification of system elements
  • 5.3. Packet format
  • 5.4. The state of sensor nodes
  • 5.4.1. Determination of the active and passive states
  • 5.4.2. Evaluation results
  • 5.4.2.1. Effect of initial energy on results
  • 5.4.2.2. Effect of data generation rate on results
  • 5.5. 3D fuzzy routing protocols
  • 5.5.1. Static 3D fuzzy routing protocols
  • 5.5.1.1. Data transmission with static protocols
  • 5.5.1.2. Performance evaluation
  • 5.5.1.2.1. Effect of data generation rate on static protocols
  • 5.5.1.2.2. Effect of buffer size on static protocols
  • 5.5.1.2.3. Effect of initial energy of nodes on static protocols
  • 5.5.1.2.4. Node energy consumption
  • 5.5.1.2.5. The number of live nodes
  • 5.5.1.2.6. Percentage of occupied buffer
  • 5.5.2. Static 3D fuzzy hybrid routing protocol
  • 5.5.3. Dynamic 3D fuzzy routing protocols
  • 5.5.3.1. Data transmission with dynamic protocols
  • 5.5.3.2. Performance evaluation
  • 5.5.3.2.1. Effect of data generation rate on dynamic protocols
  • 5.5.3.2.2. Effect of buffer size on dynamic protocols
  • 5.5.3.2.3. Effect of initial energy of nodes on dynamic protocols
  • 5.5.3.2.4. Node energy consumption
  • 5.5.3.2.5. The number of live nodes
  • 5.5.3.2.6. Percentage of occupied buffer
  • 5.5.4. Dynamic 3D fuzzy hybrid routing protocol
  • 5.6. Data aggregation methods
  • 5.6.1. Individual data aggregation
  • 5.6.2. Improved individual data aggregation
  • 5.6.3. Concise data aggregation

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