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Wireless Sensor Networks 2011-2021
The new market for Ubiquitous Sensor Networks (USN)
Updated in April 2012
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Description
Contents, Table & Figures List
Pricing
Related Content
According to IDTechEx research in the new report "Wireless Sensor Networks 2011-2021", WSN will grow rapidly from $0.45 billion in 2011 to $2 billion in 2021. These figures refer to WSN defined as wireless mesh networks, i.e. self-healing and self-organising. Wireless Sensor Networks will eventually enable the automatic monitoring of forest fires, avalanches, hurricanes, failure of country wide utility equipment, traffic, hospitals and much more over wide areas, something previously impossible. It has started already with more humble killer applications such as automating meter readings in buildings, and manufacture and process control
The WSN business is set to become a multibillion dollar activity but only if there is major progress with standards and technology. This techno-marketing report scopes over 140 manufacturers and developers and looks closely at the impediments to rollout and how to overcome them. For example, today's power sources often stand in way of the desired 20 year life so the report looks closely at how energy harvesting can help and profiles 40 relevant power source manufacturers. Ten year WSN forecasts are made based on the very latest information.
WSN Forecasts for Market Value
Source: IDTechEx
Standards
The new IDTechEx report "Wireless Sensor Networks 2011-2021" draws lessons from many successful installations in the last year. It looks at the complex standards scene with particular focus on WirelessHART that is the key to applications in the process industries in the short and medium term and it shows how the alternative ISA 11.11a has some way to go but may prove useful over a wider field of application and eventually subsume WirelessHART. It examines recent successes of the various backers of ZigBee-related solutions, who is behind the alternatives and how they see the future.
US ahead but Asia catching up
The USA dominates the development and use of WSN partly because of the heavier funding available there. US industry sits astride the computer industry thanks to companies such as Microsoft and IBM and WSN is regarded as a next wave of computing, so US industry is particularly interested to participate. Add to that the fact that the US Military, deeply interested in WSN, spends more than all other military forces combined and creating and funding start-ups is particularly easy in the USA and you can see why the US is ahead at present. IDTechEx has profiled the main players in WSN, and their location by country is shown below.
The main WSN players and their location by country
Source: IDTechEx report "Wireless Sensor Networks 2011-2021" (www.IDTechEx.com/wsn)
Power
The challenge of excessive power consumption of these nodes, that have to act as both tags and readers, is addressed. For example, progress has been good in getting the electronics to consume less electricity, by both improved signalling protocols and improved circuitry.
As for batteries, lithium thionyl chloride single-use versions have twenty year life in certain circumstances but, for many applications, energy harvesting supplying rechargeable batteries is more attractive. That said, where is the rechargeable battery guaranteed for 20 years in use? What are the most promising battery technologies coming available in the next ten years? What are the alternatives to batteries? Which of the favourite energy harvesting technologies should be used - photovoltaic, electrodynamic, thermoelectric or piezoelectric? When are they usable in combinations and what are the results so far? Which applicational sectors of WSN have the most potential and what lies in the way for each?
The new report addresses these issues and provides a wealth of analysis of WSN projects and development programmes including the creating of improved WSN components, plus profiles of many suppliers, governments, standards bodies and investors. Benchmark your success and failure and optimise your future approach based on measured evidence. It is all here.
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| 1. | EXECUTIVE SUMMARY AND CONCLUSIONS |
| 1.1. | IDTechEx WSN Forecast 2010-2022 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 2012, 2022, 2032 and market drivers |
| 1.3. | Average number of nodes per system 2012, 2022, 2032 |
| 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. | WSN node price dollars 2012, 2022, 2032 and cost reduction factors |
| 1.5. | WSN node total value $ million 2012, 2022, 2032 |
| 1.5. | Node price trends. |
| 1.5. | Price and volume of IT devices |
| 1.6. | Meter reading nodes number million 2010-2022 |
| 1.6. | IDTechEx forecast for 2032 |
| 1.6. | WSN systems and software excluding nodes $ million 2012, 2022, 2032 |
| 1.7. | Total WSN market value $ million 2012, 2022, 2032 |
| 1.7. | Three generations of active RFID |
| 1.7. | Meter reading nodes unit value dollars 2010-2022 |
| 1.8. | Meter reading nodes total value dollars 2010-2022 |
| 1.8. | Why the USA is ahead |
| 1.8. | Comparison of the three generations of active RFID |
| 1.9. | Overall Wireless Sensor Systems (WSS) market |
| 1.9. | Power for tags |
| 1.9. | Other nodes number million 2010-2022 |
| 1.10. | Other nodes unit value dollars 2010-2022 |
| 1.10. | Trend towards multiple energy harvesting |
| 1.11. | Other nodes total value dollars 2010-2022 |
| 1.12. | Total node value billion dollars 2010-2022 |
| 1.13. | WSN systems and software excluding nodes billion dollars 2010-2022 |
| 1.14. | Total WSN market million dollars 2010-2022 |
| 1.15. | WSN and ZigBee node numbers million 2012, 2022, 2032 |
| 1.16. | Average number of nodes per system 2012, 2022, 2032 |
| 1.17. | WSN node price dollars 2012, 2022, 2032 |
| 1.18. | WSN node total value $ million 2012, 2022, 2032 |
| 1.19. | WSN systems and software excluding nodes $ million 2012, 2022, 2032 |
| 1.20. | Total WSN market value $ million 2012, 2022, 2032 |
| 1.21. | WSN value chain |
| 1.22. | 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 2010-2022 |
| 8.1. | WSN and ZigBee node numbers million 2012, 2022, 2032 and market drivers |
| 8.1. | Background |
| 8.1. | Number of projects by sector in the IDTechEx RFID Knowledgebase |
| 8.2. | IDTechEx WSN Forecast 2010-2022 with RTLS for comparison |
| 8.2. | History and forecasts |
| 8.2. | Average number of nodes per system 2012, 2022, 2032 |
| 8.2.1. | IDTechEx forecasts 2010-2022 |
| 8.2.2. | IDTechEx forecast for 2032 |
| 8.2.3. | Market and technology roadmap to 2032 |
| 8.2.4. | The overall markets for ZigBee and wireless sensing. |
| 8.3. | Meter reading nodes number million 2010-2022 |
| 8.3. | WSN node price dollars 2012, 2022, 2032 and cost reduction factors |
| 8.4. | WSN node total value $ million 2012, 2022, 2032 |
| 8.4. | Meter reading nodes unit value dollars 2010-2022 |
| 8.5. | Meter reading nodes total value dollars 2010-2022 |
| 8.5. | Price-volume projections in 2009 for RF devices |
| 8.6. | WSN systems and software excluding nodes $ million 2012, 2022, 2032 |
| 8.6. | Other nodes number million 2010-2022 |
| 8.7. | Other nodes unit value dollars 2010-2022 |
| 8.7. | Total WSN market value $ million 2012, 2022, 2032 |
| 8.8. | Other nodes total value dollars 2010-2022 |
| 8.9. | Total node value billion dollars 2010-2022 |
| 8.10. | WSN systems and software excluding nodes billion dollars 2010-2022 |
| 8.11. | Total WSN market million dollars 2010-2022 |
| 8.12. | WSN and ZigBee node numbers million 2012, 2022, 2032 |
| 8.13. | Average number of nodes per system 2012, 2022, 2032 |
| 8.14. | WSN node price dollars 2012, 2022, 2032 |
| 8.15. | WSN node total value $ million 2012, 2022, 2032 |
| 8.16. | Price sensitivity curve for RFID |
| 8.17. | WSN systems and software excluding nodes $ million 2012, 2022, 2032 |
| 8.18. | Total WSN market value $ million 2012, 2022, 2032 |
| 8.19. | WSN adoption roadmap by Crossbow Technologies in 2006 |
| 8.20. | Dynamics of WSN market 2010 to 2030 |
| 8.21. | ZigBee chipset shipment market share in 2009 |
| 9. | 42 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 |
| 9.20. | Microsemi's ISM RF IC |
| 9.21. | Z-Star WSN Evaluation Kit Using ZL7025 |
| 9.21. | LGChem |
| 9.22. | MIT |
| 9.22. | Wireless ECG sensor nod |
| 9.23. | ULP Wireless Accelerometer Reference Design |
| 9.23. | National Renewable |
| 9.24. | NEC |
| 9.24. | ISM band radio in energy harvesting applications |
| 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 |
| 9.42. | Zarlink Semiconductor |
| APPENDIX 1: IDTECHEX PUBLICATIONS AND CONSULTANCY | |
| APPENDIX 2: GLOSSARY | |
| TABLES | |
| FIGURES |
Report Statistics
| Pages | 340 |
|---|---|
| Tables | 30 |
| Figures | 148 |
| Companies | 42 |
| Forecasts to | 2022 |
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