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Wireless Sensor Networks WSN - self organising, self healing networks of small "nodes" - have huge potential across industrial, military and other many other sectors. While appreciable sales have now been established, major progress depends on standards and achieving twenty year life.
EXECUTIVE SUMMARY AND CONCLUSIONS
1. INTRODUCTION
1.1. Active vs passive RFID
1.2. Three generations of active RFID
1.3. Second Generation is RTLS
1.4. Third Generation is WSN
1.4.1. Managing chaos and imperfection
1.4.2. The whole is much greater than the parts
1.4.3. Achilles heel - power
1.4.4. View from UCLA
1.4.5. View of Institute of Electronics, Information and Communication Engineers
1.4.6. View of the International Telecommunications Union
1.4.7. View of the Kelvin Institute
1.4.8. Contrast with other short range radio
1.4.9. A practical proposition
1.4.10. Wireless mesh network structure
1.5. Three waves of adoption
1.5.2. Subsuming earlier forms of active RFID?
1.6. Ubiquitous Sensor Networks (USN) and TIP
1.7. Defining features of the three generations
1.8. WSN paybacks
1.9. Supply chain of the future
1.1. Active vs passive RFID
1.2. Three generations of active RFID
1.3. Second Generation is RTLS
1.4. Third Generation is WSN
1.4.1. Managing chaos and imperfection
1.4.2. The whole is much greater than the parts
1.4.3. Achilles heel - power
1.4.4. View from UCLA
1.4.5. View of Institute of Electronics, Information and Communication Engineers
1.4.6. View of the International Telecommunications Union
1.4.7. View of the Kelvin Institute
1.4.8. Contrast with other short range radio
1.4.9. A practical proposition
1.4.10. Wireless mesh network structure
1.5. Three waves of adoption
1.5.2. Subsuming earlier forms of active RFID?
1.6. Ubiquitous Sensor Networks (USN) and TIP
1.7. Defining features of the three generations
1.8. WSN paybacks
1.9. Supply chain of the future
2. PHYSICAL STRUCTURE, SOFTWARE AND PROTOCOLS
2.1. Physical network structure
2.2. Power management
2.2.1. Power Management of mesh networks
2.3. Operating systems and signalling protocols in 2010
2.3.1. Standards still a problem in 2010
2.3.2. WSN as part of overall physical layer standards
2.3.3. Why not use ZigBee IEEE 802.15.4?
2.3.4. Protocol structure of ZigBee
2.3.5. IP for Smart Objects Alliance
2.3.6. WirelessHART, Hart Communication Foundation
2.3.7. ISA100.11a
2.3.8. IEEE 802.15.4a to the rescue?
2.3.9. 6lowplan and TinyOS
2.3.10. Associated technologies and protocols
2.3.11. Potential ANSI specification Wireless Systems for Automation
2.4. Dedicated database systems
2.5. Programming language nesC / JAVA
2.1. Physical network structure
2.2. Power management
2.2.1. Power Management of mesh networks
2.3. Operating systems and signalling protocols in 2010
2.3.1. Standards still a problem in 2010
2.3.2. WSN as part of overall physical layer standards
2.3.3. Why not use ZigBee IEEE 802.15.4?
2.3.4. Protocol structure of ZigBee
2.3.5. IP for Smart Objects Alliance
2.3.6. WirelessHART, Hart Communication Foundation
2.3.7. ISA100.11a
2.3.8. IEEE 802.15.4a to the rescue?
2.3.9. 6lowplan and TinyOS
2.3.10. Associated technologies and protocols
2.3.11. Potential ANSI specification Wireless Systems for Automation
2.4. Dedicated database systems
2.5. Programming language nesC / JAVA
3. ACTUAL AND POTENTIAL WSN APPLICATIONS
3.1. General
3.2. Precursors of WSN
3.3. Intelligent buildings
3.3.1. WSN in buildings
3.3.2. Self-Powered Wireless Keycard Switch Unlocks Hotel Energy Savings
3.4. Military and Homeland Security
3.5. Oil and gas
3.5.1. EnerPak harvesting power management for wireless sensors
3.6. Healthcare
3.7. Farming
3.8. Environment monitoring
3.9. Transport and logistics
3.10. Aircraft
3.1. General
3.2. Precursors of WSN
3.3. Intelligent buildings
3.3.1. WSN in buildings
3.3.2. Self-Powered Wireless Keycard Switch Unlocks Hotel Energy Savings
3.4. Military and Homeland Security
3.5. Oil and gas
3.5.1. EnerPak harvesting power management for wireless sensors
3.6. Healthcare
3.7. Farming
3.8. Environment monitoring
3.9. Transport and logistics
3.10. Aircraft
4. EXAMPLES OF DEVELOPERS AND THEIR PROJECTS
4.1. Geographical distribution of WSN practitioners and users
4.2. Profiles of 142 WSN suppliers and developers
4.3. Ambient Systems
4.3.1. Introduction
4.3.2. How Ambient Product Series 3000 works
4.3.3. The power of local intelligence: Dynamic Event Reporting
4.3.4. How SmartPoints communicate with the Ambient wireless infrastructure
4.3.5. Ambient Wireless Infrastructure - The power of wireless mesh networks
4.3.6. Ambient network protocol stack
4.3.7. Rapid Reader for high-volume data communication
4.3.8. Ambient Studio: Managing Ambient wireless networks
4.3.9. Comparing Ambient to wireless sensor networks (including ZigBee)
4.3.10. Comparing Ambient to active RFID and Real Time Locating Systems
4.4. Arch Rock
4.5. Auto-ID Labs Korea/ ITRI
4.6. Berkeley WEBS
4.6.1. Epic
4.6.2. SPOT - Scalable Power Observation Tool
4.7. Chungbuk National University Korea
4.8. Dust Networks
4.8.1. Smart Dust components
4.8.2. Examples of benefits
4.8.3. KV Pharmaceuticals
4.8.4. Milford Power
4.8.5. Fisher BioServices
4.8.6. PPG
4.8.7. Wheeling Pittsburgh Steel
4.8.8. SmartMesh Standards
4.8.9. US DOE project
4.9. Crossbow Technology
4.10. Emerson Process Management
4.10.1. Grane offshore oil platform
4.11. GE Global Research
4.12. Holst Research Centre IMEC - Cornell University
4.12.1. Body area networks for healthcare
4.13. Intel
4.14. Kelvin Institute
4.15. Laboratory for Assisted Cognition Environments LACE
4.16. Millennial Net
4.17. Motorola
4.18. National Information Society Agency
4.18.1. The vision for Korea
4.18.2. First trials
4.18.3. Seawater - oxygen, temperature
4.18.4. Setting concrete - temperature, humidity
4.18.5. Greenhouse microclimate - temperature, humidity
4.18.6. Hospital - blood temperature, drug temp and humidity
4.18.7. Recent trials
4.18.8. Program of future work
4.19. National Instruments WSN platform
4.20. Newtrax Technologies
4.20.1. Canadian military
4.20.2. Decentralised architecture
4.20.3. Inexpensive and expendable sensors
4.21. Sensicast
4.22. ScatterWeb
4.22.1. Hardware modularity
4.22.2. Flexible routing
4.22.3. Documented software interfaces
4.22.4. Energy management
4.22.5. Structural health monitoring of bridges
4.23. TelepathX
4.24. University of California Los Angeles CENS
4.25. University of Virginia NEST
4.25.1. NEST: Network of embedded systems
4.25.2. Technical overview
4.25.3. Programming paradigm
4.25.4. Feedback control resource management
4.25.5. Aggregate QoS management and local routing
4.25.6. Event/landmark addressable communication
4.25.7. Team formation
4.25.8. Microcell management
4.25.9. Local services
4.25.10. Information caching
4.25.11. Clock synchronization and group membership
4.25.12. Distributed control and location services
4.25.13. Testing tools and monitoring services
4.25.14. Software release: VigilNet
4.26. Wavenis and Essensium
4.26.1. Essensium's WSN product vision
4.26.2. Fusion of WSN, conventional RFID, RTLS and low power System on Chip integration
4.26.3. Concurrent skill sets to be applied
4.26.4. Integration with end customer.
4.1. Geographical distribution of WSN practitioners and users
4.2. Profiles of 142 WSN suppliers and developers
4.3. Ambient Systems
4.3.1. Introduction
4.3.2. How Ambient Product Series 3000 works
4.3.3. The power of local intelligence: Dynamic Event Reporting
4.3.4. How SmartPoints communicate with the Ambient wireless infrastructure
4.3.5. Ambient Wireless Infrastructure - The power of wireless mesh networks
4.3.6. Ambient network protocol stack
4.3.7. Rapid Reader for high-volume data communication
4.3.8. Ambient Studio: Managing Ambient wireless networks
4.3.9. Comparing Ambient to wireless sensor networks (including ZigBee)
4.3.10. Comparing Ambient to active RFID and Real Time Locating Systems
4.4. Arch Rock
4.5. Auto-ID Labs Korea/ ITRI
4.6. Berkeley WEBS
4.6.1. Epic
4.6.2. SPOT - Scalable Power Observation Tool
4.7. Chungbuk National University Korea
4.8. Dust Networks
4.8.1. Smart Dust components
4.8.2. Examples of benefits
4.8.3. KV Pharmaceuticals
4.8.4. Milford Power
4.8.5. Fisher BioServices
4.8.6. PPG
4.8.7. Wheeling Pittsburgh Steel
4.8.8. SmartMesh Standards
4.8.9. US DOE project
4.9. Crossbow Technology
4.10. Emerson Process Management
4.10.1. Grane offshore oil platform
4.11. GE Global Research
4.12. Holst Research Centre IMEC - Cornell University
4.12.1. Body area networks for healthcare
4.13. Intel
4.14. Kelvin Institute
4.15. Laboratory for Assisted Cognition Environments LACE
4.16. Millennial Net
4.17. Motorola
4.18. National Information Society Agency
4.18.1. The vision for Korea
4.18.2. First trials
4.18.3. Seawater - oxygen, temperature
4.18.4. Setting concrete - temperature, humidity
4.18.5. Greenhouse microclimate - temperature, humidity
4.18.6. Hospital - blood temperature, drug temp and humidity
4.18.7. Recent trials
4.18.8. Program of future work
4.19. National Instruments WSN platform
4.20. Newtrax Technologies
4.20.1. Canadian military
4.20.2. Decentralised architecture
4.20.3. Inexpensive and expendable sensors
4.21. Sensicast
4.22. ScatterWeb
4.22.1. Hardware modularity
4.22.2. Flexible routing
4.22.3. Documented software interfaces
4.22.4. Energy management
4.22.5. Structural health monitoring of bridges
4.23. TelepathX
4.24. University of California Los Angeles CENS
4.25. University of Virginia NEST
4.25.1. NEST: Network of embedded systems
4.25.2. Technical overview
4.25.3. Programming paradigm
4.25.4. Feedback control resource management
4.25.5. Aggregate QoS management and local routing
4.25.6. Event/landmark addressable communication
4.25.7. Team formation
4.25.8. Microcell management
4.25.9. Local services
4.25.10. Information caching
4.25.11. Clock synchronization and group membership
4.25.12. Distributed control and location services
4.25.13. Testing tools and monitoring services
4.25.14. Software release: VigilNet
4.26. Wavenis and Essensium
4.26.1. Essensium's WSN product vision
4.26.2. Fusion of WSN, conventional RFID, RTLS and low power System on Chip integration
4.26.3. Concurrent skill sets to be applied
4.26.4. Integration with end customer.
5. POWER FOR TAGS
5.1. Batteries
5.1.1. Customised and AAA / AA batteries
5.1.2. Planar Energy Devices
5.1.3. AlwaysReady Smart NanoBattery
5.1.4. Energy storage of batteries in standard and laminar formats
5.1.5. Future options for highest energy density
5.2. Laminar fuel cells
5.2.1. Bendable fuel cells: on-chip fuel cell on a flexible polymer substrate
5.3. Energy Harvesting
5.3.1. Energy harvesting with rechargeable batteries
5.3.2. Energy harvesting WSN at SNCF France
5.3.3. Photovoltaics
5.3.4. Battery free energy harvesting
5.3.5. Thermoelectrics in inaccessible places
5.3.6. Other options
5.3.7. Wireless sensor network powered by trees
5.4. Field delivery of power
5.1. Batteries
5.1.1. Customised and AAA / AA batteries
5.1.2. Planar Energy Devices
5.1.3. AlwaysReady Smart NanoBattery
5.1.4. Energy storage of batteries in standard and laminar formats
5.1.5. Future options for highest energy density
5.2. Laminar fuel cells
5.2.1. Bendable fuel cells: on-chip fuel cell on a flexible polymer substrate
5.3. Energy Harvesting
5.3.1. Energy harvesting with rechargeable batteries
5.3.2. Energy harvesting WSN at SNCF France
5.3.3. Photovoltaics
5.3.4. Battery free energy harvesting
5.3.5. Thermoelectrics in inaccessible places
5.3.6. Other options
5.3.7. Wireless sensor network powered by trees
5.4. Field delivery of power
6. IMPEDIMENTS TO ROLLOUT OF WSN
6.1. Concerns about privacy and radiation
6.2. Reluctance
6.3. Competing standards and proprietary systems
6.4. Lack of education
6.5. Technology improvement and cost reduction needed
6.5.1. Error prone
6.5.2. Scalability
6.5.3. Sensors
6.5.4. Locating Position
6.5.5. Spectrum congestion and handling huge amounts of data
6.5.6. Optimal routing, global directories, service discovery
6.6. Niche markets lead to first success
6.1. Concerns about privacy and radiation
6.2. Reluctance
6.3. Competing standards and proprietary systems
6.4. Lack of education
6.5. Technology improvement and cost reduction needed
6.5.1. Error prone
6.5.2. Scalability
6.5.3. Sensors
6.5.4. Locating Position
6.5.5. Spectrum congestion and handling huge amounts of data
6.5.6. Optimal routing, global directories, service discovery
6.6. Niche markets lead to first success
7. MARKETS 2010-2020
7.1. Background
7.2. Assessments
7.3. History and forecasts.
7.3.1. IDTechEx forecasts 2010-2020
7.3.2. IDTechEx forecast for 2029
7.3.3. Market and technology roadmap to 2029
7.3.4. The overall markets for ZigBee and wireless sensing.
7.1. Background
7.2. Assessments
7.3. History and forecasts.
7.3.1. IDTechEx forecasts 2010-2020
7.3.2. IDTechEx forecast for 2029
7.3.3. Market and technology roadmap to 2029
7.3.4. The overall markets for ZigBee and wireless sensing.
8. 40 PROFILES OF RELEVANT POWER SOURCE SUPPLIERS AND DEVELOPERS
8.1. A123 Systems
8.2. Advanced Battery Technologies
8.3. Altairnano
8.4. BASF - Sion
8.4.1. BASF licenses Argonne Lab's cathode material
8.5. BYD
8.5.1. Volkswagen
8.5.2. Car superlatives
8.5.3. Plans for the USA
8.6. CapXX
8.7. Celxpert
8.8. China BAK
8.9. Cymbet
8.10. Duracell
8.11. Electrovaya
8.12. Enerize USA and Fife Batteries UK
8.13. Front Edge
8.14. Furukawa
8.15. Harvard
8.16. Hitachi Maxell
8.17. Holst
8.18. IBM
8.19. Infinite Power Solutions
8.20. Kokam America
8.21. LGChem
8.22. MIT
8.23. National Renewable
8.24. NEC
8.25. Nippon Chemi-Con Japan
8.26. Oak Ridge
8.27. Panasonic (formerly Matsushita, now owns Sanyo)
8.28. PolyPlus Battery
8.29. Planar
8.30. Renata
8.31. ReVolt
8.32. Saft
8.33. Sandia
8.34. Solicore
8.35. Superlattice
8.36. Tadiran
8.37. Tech Univ Berlin
8.38. Toshiba
8.39. Sony
8.40. Univ Calif
8.1. A123 Systems
8.2. Advanced Battery Technologies
8.3. Altairnano
8.4. BASF - Sion
8.4.1. BASF licenses Argonne Lab's cathode material
8.5. BYD
8.5.1. Volkswagen
8.5.2. Car superlatives
8.5.3. Plans for the USA
8.6. CapXX
8.7. Celxpert
8.8. China BAK
8.9. Cymbet
8.10. Duracell
8.11. Electrovaya
8.12. Enerize USA and Fife Batteries UK
8.13. Front Edge
8.14. Furukawa
8.15. Harvard
8.16. Hitachi Maxell
8.17. Holst
8.18. IBM
8.19. Infinite Power Solutions
8.20. Kokam America
8.21. LGChem
8.22. MIT
8.23. National Renewable
8.24. NEC
8.25. Nippon Chemi-Con Japan
8.26. Oak Ridge
8.27. Panasonic (formerly Matsushita, now owns Sanyo)
8.28. PolyPlus Battery
8.29. Planar
8.30. Renata
8.31. ReVolt
8.32. Saft
8.33. Sandia
8.34. Solicore
8.35. Superlattice
8.36. Tadiran
8.37. Tech Univ Berlin
8.38. Toshiba
8.39. Sony
8.40. Univ Calif
APPENDIX 1: IDTECHEX PUBLICATIONS AND CONSULTANCY
APPENDIX 2: GLOSSARY
APPENDIX 2: GLOSSARY
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