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1. | EXECUTIVE SUMMARY AND CONCLUSIONS |
1.1. | IDTechEx WSN Forecast 2010-2020 with RTLS for comparison |
1.1. | Replacing wired sensor systems |
1.1. | Prediction of the wave of ubiquitous computing by Mark Weiser |
1.2. | The Embedded Internet |
1.2. | What is a mesh network? |
1.2. | WSN and ZigBee node numbers million 2010, 2020, 2030 and market drivers |
1.3. | Average number of nodes per system 2010, 2020, 2030 |
1.3. | The basic mesh network |
1.3. | A basic wireless mesh network |
1.4. | Some possibilities for WSN in buildings |
1.4. | IDTechEx forecasts |
1.4. | Number of systems 2010, 2020, 2030 |
1.5. | WSN node price dollars 2010, 2020, 2030 and cost reduction factors |
1.5. | Node price trends. |
1.5. | Price and volume of IT devices |
1.6. | Meter reading nodes number million 2010-2020 |
1.6. | IDTechEx forecast for 2030 |
1.6. | WSN node total value $ million 2010, 2020, 2030 |
1.7. | WSN systems and software excluding nodes $ million 2010, 2020, 2030 |
1.7. | Three generations of active RFID |
1.7. | Meter reading nodes unit value dollars 2010-2020 |
1.8. | Meter reading nodes total value dollars 2010-2020 |
1.8. | Why the USA is ahead |
1.8. | Total WSN market value $ million 2010, 2020, 2030 |
1.9. | Comparison of the three generations of active RFID |
1.9. | Power for tags |
1.9. | Other nodes number million 2010-2020 |
1.10. | Other nodes unit value dollars 2010-2020 |
1.10. | Trend towards multiple energy harvesting |
1.10. | Overall Wireless Sensor Systems (WSS) market |
1.11. | Other nodes total value dollars 2010-2020 |
1.12. | Total node value billion dollars 2010-2020 |
1.13. | WSN systems and software excluding nodes billion dollars 2010-2020 |
1.14. | Total WSN market million dollars 2010-2020 |
1.15. | WSN and ZigBee node numbers million 2010, 2020, 2030 |
1.16. | Average number of nodes per system 2010, 2020, 2030 |
1.17. | Number of systems 2010, 2020, 2030 |
1.18. | WSN node price dollars 2010, 2020, 2030 |
1.19. | WSN node total value $ million 2010, 2020, 2030 |
1.20. | WSN systems and software excluding nodes $ million 2010, 2020, 2030 |
1.21. | Total WSN market value $ million 2010, 2020, 2030 |
1.22. | WSN value chain |
1.23. | Geographical distribution of 141 profiled WSN practitioners |
2. | INTRODUCTION |
2.1. | Defining features of the three generations of active RFID |
2.1. | Typical RTLS tags with 3-10 years battery life. Top left and right WiFi 2.45GHz. Bottom left UWB. Bottom right 2.45GHz. Center ultrasound. |
2.1. | Active vs passive RFID |
2.2. | Three generations of active RFID |
2.2. | MicroStrain WSN node with 55 day battery life |
2.3. | WSN compared with Bluetooth and WiFi in respect of power and data rate. |
2.3. | Second Generation is RTLS |
2.4. | Third Generation is WSN |
2.4. | WSN compared with other short range radio in respect of range and data rate typically available |
2.4.1. | Managing chaos and imperfection |
2.4.2. | The whole is much greater than the parts |
2.4.3. | Achilles heel - power |
2.4.4. | View from UCLA |
2.4.5. | View of Institute of Electronics, Information and Communication Engineers |
2.4.6. | View of the International Telecommunications Union |
2.4.7. | View of the Kelvin Institute |
2.4.8. | Contrast with other short range radio |
2.4.9. | A practical proposition |
2.4.10. | Wireless mesh network structure |
2.5. | Three waves of adoption |
2.5. | Detailed view of range vs data rate |
2.5.1. | WSN leads RTLS |
2.5.2. | Subsuming earlier forms of active RFID? |
2.6. | Ubiquitous Sensor Networks (USN) and TIP |
2.6. | A basic wireless mesh network |
2.7. | WSN backhaul |
2.7. | Defining features of the three generations |
2.8. | WSN paybacks |
2.8. | Diagrammatic illustration of the three waves of adoption of active RFID. |
2.9. | Possible area of deployment vs system cost |
2.9. | Supply chain of the future |
2.10. | Tolerance of faults and unauthorised repositioning vs system cost |
2.11. | Tag cost today vs system cost |
2.12. | Number of tags per interrogator vs system cost |
2.13. | Infrastructure cost vs system cost |
2.14. | RTLS progress towards the ultimate supply chain |
3. | PHYSICAL STRUCTURE, SOFTWARE AND PROTOCOLS |
3.1. | WirelessHART Board of Directors |
3.1. | WSN with conventional star network at outside edge to save power |
3.1. | Physical network structure |
3.2. | Power management |
3.2. | More complex networks that are only partially meshed |
3.2.1. | Power Management of mesh networks |
3.3. | Operating systems and signalling protocols in 2010 |
3.3. | Protocol structure of ZigBee |
3.3.1. | Standards still a problem in 2010 |
3.3.2. | WSN as part of overall physical layer standards |
3.3.3. | Why not use ZigBee IEEE 802.15.4? |
3.3.4. | Protocol structure of ZigBee |
3.3.5. | IP for Smart Objects Alliance |
3.3.6. | WirelessHART, Hart Communication Foundation |
3.3.7. | ISA100.11a |
3.3.8. | IEEE 802.15.4a to the rescue? |
3.3.9. | 6lowpan and TinyOS |
3.3.10. | Associated technologies and protocols |
3.3.11. | ISA SP100 |
3.4. | Dedicated database systems |
3.4. | WirelessHART supports both new wireless field devices and also retrofit of existing HART devices with WirelessHART adapters |
3.5. | Two distinct communication paths in the WirelessHART mesh |
3.5. | Programming language nesC / JAVA |
3.6. | Micropelt thermoelectric generation of electricity for a wireless sensor |
3.7. | DecaWave ScenSor product brief |
4. | ACTUAL AND POTENTIAL WSN APPLICATIONS |
4.1. | RFID meets sensor network |
4.1. | General |
4.2. | Precursors of WSN |
4.2. | Some possibilities for WSN in buildings |
4.3. | Mesh network in military applications |
4.3. | Intelligent buildings |
4.3.1. | WSN in buildings |
4.3.2. | Self-Powered Wireless Keycard Switch Unlocks Hotel Energy Savings |
4.4. | Military and Homeland Security |
4.4. | Requirements for sensor networks in health management of missiles |
4.5. | Future fundamental technology development areas for "Health Management of Munitions" in the US Navy |
4.5. | Oil and gas |
4.5.1. | EnerPak harvesting power management for wireless sensors |
4.6. | Healthcare |
4.6. | In-body WSN for healthcare |
4.7. | Environment monitoring. |
4.7. | Farming |
4.8. | Environment monitoring |
4.8. | Intelligent container |
4.9. | Transport and logistics |
4.10. | Aircraft |
5. | EXAMPLES OF DEVELOPERS AND THEIR PROJECTS |
5.1. | 142 WSN suppliers and developers tabulated by country, website and activity, including suppliers of wireless sensors not yet meshed. |
5.1. | Geographical distribution of WSN practitioners and users |
5.1. | Geographical distribution of 141 profiled WSN practitioners |
5.2. | Ambient Wireless Infrastructure |
5.2. | Profiles of 142 WSN suppliers and developers |
5.2. | Comparison of wireless sensor networks |
5.3. | Comparison of traditional Active RFID and Ambient series 3000 |
5.3. | Ambient Systems |
5.3. | Ambient SmartPoints - Making objects intelligent |
5.3.1. | Introduction |
5.3.2. | How Ambient Product Series 3000 works |
5.3.3. | The power of local intelligence: Dynamic Event Reporting |
5.3.4. | How SmartPoints communicate with the Ambient wireless infrastructure |
5.3.5. | Ambient Wireless Infrastructure - The power of wireless mesh networks |
5.3.6. | Ambient network protocol stack |
5.3.7. | Rapid Reader for high-volume data communication |
5.3.8. | Ambient Studio: Managing Ambient wireless networks |
5.3.9. | Comparing Ambient to wireless sensor networks (including ZigBee) |
5.3.10. | Comparing Ambient to active RFID and Real Time Locating Systems |
5.4. | Arch Rock |
5.4. | SmartPoints communicate with the Ambient wireless infrastructure |
5.5. | Ambient wireless mesh network |
5.5. | Auto-ID Labs Korea/ ITRI |
5.6. | Berkeley WEBS |
5.6. | Ambient network protocol stack |
5.6.1. | Epic |
5.6.2. | SPOT - Scalable Power Observation Tool |
5.7. | Chungbuk National University Korea |
5.7. | Ambient Studio: Managing Ambient wireless networks |
5.8. | Active RFID and RTLS compared to Ambient |
5.8. | Dust Networks |
5.8.1. | Smart Dust components |
5.8.2. | Examples of benefits |
5.8.3. | KV Pharmaceuticals |
5.8.4. | Milford Power |
5.8.5. | Fisher BioServices |
5.8.6. | PPG |
5.8.7. | Wheeling Pittsburgh Steel |
5.8.8. | SmartMesh Standards |
5.8.9. | US DOE project |
5.9. | Crossbow Technology |
5.9. | Organisation for promoting USN |
5.10. | Research focus at Auto-ID Labs Korea |
5.10. | Emerson Process Management |
5.10.1. | Grane offshore oil platform |
5.11. | GE Global Research |
5.11. | Related work on sensors |
5.12. | A Framework of In-situ Sensor Data Processing System for Context Awareness |
5.12. | Holst Research Centre IMEC - Cornell University |
5.12.1. | Body area networks for healthcare |
5.13. | Intel |
5.13. | Smart Dust components |
5.14. | Controlled environment |
5.14. | Kelvin Institute |
5.15. | Laboratory for Assisted Cognition Environments LACE |
5.15. | SmartMesh IA-500™ |
5.16. | Smart Dust Intelligent Networking System |
5.16. | Millennial Net |
5.17. | Motorola |
5.17. | Holst Centre body area network node |
5.18. | Holst WSN piezo driven sensor |
5.18. | National Information Society Agency |
5.18.1. | The vision for Korea |
5.18.2. | First trials |
5.18.3. | Seawater - oxygen, temperature |
5.18.4. | Setting concrete - temperature, humidity |
5.18.5. | Greenhouse microclimate - temperature, humidity |
5.18.6. | Hospital - blood temperature, drug temp and humidity |
5.18.7. | Recent trials |
5.18.8. | Program of future work |
5.19. | National Instruments WSN platform |
5.19. | New logos of Intel |
5.20. | Alternative flooding approaches |
5.20. | Newtrax Technologies |
5.20.1. | Canadian military |
5.20.2. | Decentralised architecture |
5.20.3. | Inexpensive and expendable sensors |
5.21. | TelepathX |
5.21. | D3R |
5.22. | IAP4300 - Intelligent Access Point for MOTOMESH Duo |
5.22. | University of California Los Angeles CENS |
5.23. | University of Virginia NEST |
5.23. | IAP6300 - Intelligent Access Point for MOTOMESH Solo |
5.23.1. | NEST: Network of embedded systems |
5.23.2. | Technical overview |
5.23.3. | Programming paradigm |
5.23.4. | Feedback control resource management |
5.23.5. | Aggregate QoS management and local routing |
5.23.6. | Event/landmark addressable communication |
5.23.7. | Team formation |
5.23.8. | Microcell management |
5.23.9. | Local services |
5.23.10. | Information caching |
5.23.11. | Clock synchronization and group membership |
5.23.12. | Distributed control and location services |
5.23.13. | Testing tools and monitoring services |
5.23.14. | Software release: VigilNet |
5.24. | Wavenis and Essensium |
5.24. | IAP7300 - Intelligent Access Point for MOTOMESH Quattro |
5.24.1. | Essensium's WSN product vision |
5.24.2. | Fusion of WSN, conventional RFID, RTLS and low power System on Chip integration |
5.24.3. | Concurrent skill sets to be applied |
5.24.4. | Integration with end customer. |
5.25. | USN in Korea |
5.26. | Concept of USN in Korea |
5.27. | Timeline of USN development in Korea |
5.28. | Marine environment data collection using USN |
5.29. | Fishery monitoring test |
5.30. | Marine environment data collection system |
5.31. | Concrete structure and sensor installation for field test. |
5.32. | Concrete curing history management |
5.33. | Microclimate in industrial greenhouses. |
5.34. | Field test of monitoring blood and anti-cancer agents |
5.35. | Development of the necessary software and hardware |
5.36. | New National Instruments WSN hardware - new NI WSN Ethernet gateway and nodes connected to existing NI CompactRIO systems. |
5.37. | NEST node architecture |
5.38. | Essensium's WSN product vision |
5.39. | Wavenis view of its market for wireless sensing |
5.40. | Three skill sets to be applied. |
5.41. | Integration with end customer |
6. | POWER FOR TAGS |
6.1. | Power supply options for WSN |
6.1. | Power requirements of small devices |
6.1. | Batteries |
6.1.1. | Customised and AAA / AA batteries |
6.1.2. | Planar Energy Devices |
6.1.3. | AlwaysReady Smart NanoBattery |
6.1.4. | Energy storage of batteries in standard and laminar formats |
6.1.5. | Future options for highest energy density |
6.2. | Features of the Planar Energy devices batteries |
6.2. | Laminar fuel cells |
6.2. | Planar Energy Devices battery |
6.2.1. | Bendable fuel cells: on-chip fuel cell on a flexible polymer substrate |
6.3. | Claimed energy storage in AAA batteries |
6.3. | Volumetric vs gravimetric energy density for batteries |
6.3. | Energy Harvesting |
6.3.1. | Energy harvesting with rechargeable batteries |
6.3.2. | Energy harvesting WSN at SNCF France |
6.3.3. | Photovoltaics |
6.3.4. | Battery free energy harvesting |
6.3.5. | Thermoelectrics in inaccessible places |
6.3.6. | Other options |
6.3.7. | Wireless sensor network powered by trees |
6.4. | Claimed energy storage in AA batteries |
6.4. | Field delivery of power |
6.4. | Conformable fuel cell |
6.5. | Conformable FuelCell StickerTM |
6.5. | Lithium-Thionyl Chloride batteries |
6.6. | Tadiran high power series |
6.6. | SNCF TGV high speed train |
6.7. | Temperature monitoring on high speed trains |
6.7. | The new photovoltaic options compared |
6.8. | Power density vs energy density exhibited by state of the art harvesting devices |
6.9. | Thin film batteries with supercapacitors for EH in WSN |
6.10. | Field delivery of power demonstrated by Intel |
7. | IMPEDIMENTS TO ROLLOUT OF WSN |
7.1. | Concerns about privacy and radiation |
7.1. | RTLS operational options using electromagnetic emissions or, more rarely, ultrasound |
7.2. | Reluctance |
7.3. | Competing standards and proprietary systems |
7.4. | Lack of education |
7.5. | Technology improvement and cost reduction needed |
7.5.1. | Error prone |
7.5.2. | Scalability |
7.5.3. | Sensors |
7.5.4. | Locating Position |
7.5.5. | Spectrum congestion and handling huge amounts of data |
7.5.6. | Optimal routing, global directories, service discovery |
7.6. | Niche markets lead to first success |
8. | MARKETS 2010-2020 |
8.1. | WSN and ZigBee node numbers million 2010, 2020, 2030 and market drivers |
8.1. | Background |
8.1. | Number of projects by sector in the IDTechEx RFID Knowledgebase |
8.2. | IDTechEx WSN Forecast 2010-2020 with RTLS for comparison |
8.2. | Assessments |
8.2. | Average number of nodes per system 2010, 2020, 2030 |
8.3. | Number of systems 2010, 2020, 2030 |
8.3. | History and forecasts. |
8.3. | Meter reading nodes number million 2010-2020 |
8.3.1. | IDTechEx forecasts 2010-2020 |
8.3.2. | IDTechEx forecast for 2030 |
8.3.3. | Market and technology roadmap to 2030 |
8.3.4. | The overall markets for ZigBee and wireless sensing. |
8.4. | Meter reading nodes unit value dollars 2010-2020 |
8.4. | WSN node price dollars 2010, 2020, 2030 and cost reduction factors |
8.5. | WSN node total value $ million 2010, 2020, 2030 |
8.5. | Meter reading nodes total value dollars 2010-2020 |
8.6. | Other nodes number million 2010-2020 |
8.6. | Price-volume projections in 2009 for RF devices |
8.7. | WSN systems and software excluding nodes $ million 2010, 2020, 2030 |
8.7. | Other nodes unit value dollars 2010-2020 |
8.8. | Other nodes total value dollars 2010-2020 |
8.8. | Total WSN market value $ million 2010, 2020, 2030 |
8.9. | Total node value billion dollars 2010-2020 |
8.10. | WSN systems and software excluding nodes billion dollars 2010-2020 |
8.11. | Total WSN market million dollars 2010-2020 |
8.12. | WSN and ZigBee node numbers million 2010, 2020, 2030 |
8.13. | Average number of nodes per system 2010, 2020, 2030 |
8.14. | Number of systems 2010, 2020, 2030 |
8.15. | WSN node price dollars 2010, 2020, 2030 |
8.16. | WSN node total value $ million 2010, 2020, 2030 |
8.17. | Price sensitivity curve for RFID |
8.18. | WSN systems and software excluding nodes $ million 2010, 2020, 2030 |
8.19. | Total WSN market value $ million 2010, 2020, 2030 |
8.20. | WSN adoption roadmap by Crossbow Technologies in 2006 |
8.21. | Dynamics of WSN market 2010 to 2030 |
8.22. | ZigBee chipset shipment market share in 2009 |
9. | 41 PROFILES OF RELEVANT POWER SOURCE SUPPLIERS AND DEVELOPERS |
9.1. | BYD financials |
9.1. | Altairnano view of some of the primary performance advantages of its lithium traction batteries |
9.1. | A123 Systems |
9.2. | Advanced Battery Technologies |
9.2. | Celxpert notebook battery pack |
9.2. | Key Features of NanoEnergy miniature power source |
9.3. | Interchangeable notebook battery pack |
9.3. | Altairnano |
9.4. | BASF - Sion |
9.4. | LEV electric car by Qingyuan Motors |
9.4.1. | BASF licenses Argonne Lab's cathode material |
9.5. | The Cymbet EnerChip™ |
9.5. | BYD |
9.5.1. | Volkswagen |
9.5.2. | Car superlatives |
9.5.3. | Plans for the USA |
9.6. | CapXX |
9.6. | Duracell NiOx batteries |
9.7. | Hummer H3 ReEV Lithium Ion SuperPolymer battery pack made by Electrovaya |
9.7. | Celxpert |
9.8. | China BAK |
9.8. | The world's thinnest self standing rechargeable battery claims FET |
9.9. | Furukawa Cycle-service storage battery for Golf Cars |
9.9. | Cymbet |
9.10. | Duracell |
9.10. | Light in Africa |
9.11. | LiTESTAR™ |
9.11. | Electrovaya |
9.12. | Enerize USA and Fife Batteries UK |
9.12. | Researchers from Planar Energy -Devices, Inc., insert a sample into the vacuum chamber of the company's thin-film deposition system |
9.13. | Planar Energy Devices has advanced the solid-state lithium battery from NREL's crude prototype (below) to a miniaturized, integrated device (bottom) |
9.13. | Front Edge |
9.14. | Furukawa |
9.14. | Flexible battery that charges in one minute |
9.15. | Nippon Chemi-Con ELDCs - supercapacitors |
9.15. | Harvard |
9.16. | Hitachi Maxell |
9.16. | New Planar Energy Devices high capacity laminar battery |
9.17. | Renata Batteries |
9.17. | Holst |
9.18. | IBM |
9.18. | Flexion ™ |
9.19. | Toshiba e-bike battery |
9.19. | Infinite Power Solutions |
9.20. | Kokam America |
9.21. | LGChem |
9.22. | MIT |
9.23. | National Renewable |
9.24. | NEC |
9.25. | Nippon Chemi-Con Japan |
9.26. | Oak Ridge |
9.27. | Panasonic (formerly Matsushita, now owns Sanyo) |
9.28. | PolyPlus Battery |
9.29. | Planar |
9.30. | Renata |
9.31. | ReVolt |
9.32. | Saft |
9.33. | Sandia |
9.34. | Solicore |
9.35. | Superlattice |
9.36. | Tadiran |
9.37. | Tech Univ Berlin |
9.38. | Toshiba |
9.39. | Sony |
9.40. | Univ Calif |
9.41. | Virtual Extension |
APPENDIX 1: IDTECHEX PUBLICATIONS AND CONSULTANCY | |
APPENDIX 2: GLOSSARY | |
TABLES | |
FIGURES |
Pages | 338 |
---|---|
Tables | 32 |
Figures | 145 |
Companies | 41 |
Forecasts to | 2020 |