Wireless Sensor Networks 2010-2020

This publication has been discontinued on July 27, 2011.

Below is the updated product.

Wireless Sensor Networks 2011-2021

Published: July, 2011

Product code: 201723

Introduction

Abstract

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.

The new IDTechEx report “Wireless Sensor Networks 2010-2020” draws lessons from the many successful installations in the last year. It looks at the complex standards scene with particular focus on WirelessHART that is key to applications in the process industries in the short and medium term and it shows how the alternative ISA 100.11a 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.

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.

• Pages: 326
• Tables: 31
• Figures: 146
• Companies: 40
• Forecasts to: 2020
• Last update: Q1 2010

Table of Contents

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

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

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

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.

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

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

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.

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

APPENDIX 1: IDTECHEX PUBLICATIONS AND CONSULTANCY

APPENDIX 2: GLOSSARY

TABLES

• 1.1. Defining features of the three generations of active RFID
• 2.1. WirelessHART Board of Directors
• 4.1. 142 WSN suppliers and developers tabulated by country, website and activity
• 4.2. Comparison of wireless sensor networks
• 4.3. Comparison of traditional Active RFID and Ambient series 3
• 5.1. Power supply options for WSN
• 5.2. Features of the Planar Energy devices batteries
• 5.3. Claimed energy storage in AAA batteries
• 5.4. Claimed energy storage in AA batteries
• 5.5. Lithium-Thionyl Chloride batteries
• 5.6. Tadiran high power series
• 5.7. The new photovoltaic options compared.
• 7.1. WSN and ZigBee node numbers million 2009, 2019, 2029 and market drivers
• 7.2. Average number of nodes per system 2009, 2019, 2029
• 7.3. Number of systems
• 7.4. WSN node price dollars 2009, 2019, 2029 and cost reduction factors
• 7.5. WSN node total value $ million 2009, 2019, 2029
• 7.6. Price-volume projections in 2009 for RF devices
• 7.7. WSN systems and software excluding nodes $ million 2009, 2019, 2029
• 7.8. Total WSN market value $ million 2009, 2019, 2029
• 8.1. BYD financials
• 8.2. Key Features of NanoEnergy minature power source

FIGURES

• 1.1. 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.
• 1.2. MicroStrain WSN node with 55 day battery life
• 1.3. WSN compared with Bluetooth and WiFi in respect of power and data rate.
• 1.4. WSN compared with other short range radio in respect of range and data rate typically available
• 1.5. Detailed view of range vs data rate
• 1.6. A basic wireless mesh network
• 1.7. WSN backhaul
• 1.8. Diagrammatic illustration of the three waves of adoption of active RFID.
• 1.9. Possible area of deployment vs system cost
• 1.10. Tolerance of faults and unauthorised repositioning vs system cost
• 1.11. Tag cost today vs system cost
• 1.12. Number of tags per interrogator vs system cost
• 1.13. Infrastructure cost vs system cost
• 1.14. RTLS progress towards the ultimate supply chain
• 2.1. WSN with conventional star network at outside edge to save power
• 2.2. More complex networks that are only partially meshed
• 2.3. Protocol structure of ZigBee
• 2.4. WirelessHART supports both new wireless field devices and also retrofit of existing HART devices with WirelessHART adapters
• 2.5. Two distinct communication paths in the WirelessHART mesh
• 2.6. DecaWave ScenSor product brief
• 3.1. RFID meets sensor network
• 3.2. Some possibilities for WSN in buildings
• 3.3. Mesh network in military applications
• 3.4. Requirements for sensor networks in health management of missiles
• 3.5. Future fundamental technology development areas for "Health Management of Munitions" in the US Navy
• 3.6. In-body WSN for healthcare
• 3.7. Environment monitoring.
• 3.8. Intelligent container
• 4.1. Geographical distribution of 141 profiled WSN practitioners
• 4.2. Ambient Wireless Infrastructure
• 4.3. Ambient SmartPoints - Making objects intelligent
• 4.4. SmartPoints communicate with the Ambient wireless infrastructure
• 4.5. Ambient wireless mesh network
• 4.6. Ambient network protocol stack
• 4.7. Ambient Studio: Managing Ambient wireless networks
• 4.8. Active RFID and RTLS compared to Ambient
• 4.9. Organisation for promoting USN
• 4.10. Research focus at Auto-ID Labs Korea
• 4.11. Related work on sensors
• 4.12. A Framework of In-situ Sensor Data Processing System for Context Awareness
• 4.13. Smart Dust components
• 4.14. Controlled environment
• 4.15. SmartMesh IA-500™
• 4.16. Smart Dust Intelligent Networking System
• 4.17. Holst Centre body area network node
• 4.18. Holst WSN piezo driven sensor
• 4.19. New logos of Intel
• 4.20. MeshScape® 5.0 "Best of Sensors" Award Winner!"
• 4.21. IAP4300 - Intelligent Access Point for MOTOMESH Duo
• 4.22. IAP6300 - Intelligent Access Point for MOTOMESH Solo
• 4.23. IAP7300 - Intelligent Access Point for MOTOMESH Quattro
• 4.24. USN in Korea
• 4.25. Concept of USN in Korea
• 4.26. Timeline of USN development in Korea
• 4.27. Marine environment data collection using USN
• 4.28. Fishery monitoring test
• 4.29. Marine environment data collection system
• 4.30. Concrete structure and sensor installation for field test.
• 4.31. Concrete curing history management
• 4.32. Microclimate in industrial greenhouses.
• 4.33. Field test of monitoring blood and anti-cancer agents
• 4.34. Development of the necessary software and hardware
• 4.35. New National Instruments WSN hardware - new NI WSN Ethernet gateway and nodes connected to existing NI CompactRIO systems.
• 4.36. SensiNet
• 4.37. ScatterWeb system diagram
• 4.38. Bridge monitoring
• 4.39. NEST node architecture
• 4.40. Essensium' s WSN product vision
• 4.41. Wavenis view of its market for wireless sensing
• 4.42. Three skill sets to be applied.
• 4.43. Integration with end customer
• 5.1. Power requirements of small devices
• 5.2. Planar Energy Devices battery
• 5.3. Volumetric vs gravimetric energy density for batteries
• 5.4. Conformable fuel cell
• 5.5. Conformable FuelCell Sticker™
• 5.6. SNCF TGV high speed train
• 5.7. Temperature monitoring on high speed trains
• 5.8. Power density vs energy density exhibited by state of the art harvesting devices
• 5.9. Thin film batteries with supercapacitors for EH in WSN
• 5.10. Field delivery of power demonstrated by Intel
• 6.1. RTLS operational options using electromagnetic emissions or, more rarely, ultrasound.
• 7.1. Number of projects by sector in the IDTechEx RFID Knowledgebase.
• 7.2. IDTechEx WSN Forecast 2010-2020 with RTLS for comparison
• 7.3. Meter reading nodes number million 2010-2020
• 7.4. Meter reading nodes unit value dollars 2010-2020
• 7.5. Meter reading nodes total value dollars 2010-2020
• 7.6. Other nodes number million 2010-2020
• 7.7. Other nodes unit value dollars 2010-2020
• 7.8. Other nodes total value dollars 2010-2020
• 7.9. Total node value billion dollars 2010-2020
• 7.10. WSN systems and software excluding nodes billion dollars 2010-2020
• 7.11. Total WSN market million dollars 2010-2020
• 7.12. WSN and ZigBee node numbers million 2009, 2019, 2029
• 7.13. Average number of nodes per system 2009, 2019, 2029
• 7.14. Number of systems 2009, 2019, 2029
• 7.15. WSN node price dollars 2009, 2019, 2029
• 7.16. WSN node total value $ million 2009, 2019, 2029
• 7.17. Price sensitivity curve for RFID
• 7.18. WSN systems and software excluding nodes $ million 2009, 2019, 2029
• 7.19. Total WSN market value $ million 2009, 2019, 2029
• 7.20. WSN adoption roadmap by Crossbow Technologies in 2006
• 7.21. Dynamics of WSN market 2009 to 2029
• 7.22. ZigBee chipset shipment market share in 2009
• 8.1. Altairnano view of some of the primary performance advantages of its lithium traction batteries
• 8.2. Celxpert notebook battery pack
• 8.3. Interchangeable notebook battery pack
• 8.4. LEV electric car by Qingyuan Motors
• 8.5. The Cymbet EnerChip™
• 8.6. Duracell NiOx batteries
• 8.7. Hummer H3 ReEV Lithium Ion SuperPolymer battery pack made by Electrovaya.
• 8.8. The world' s thinnest self standing rechargeable battery claims FET
• 8.9. Furukawa Cycle-service storage battery for Golf Cars
• 8.10. Light in Africa
• 8.11. LiTE-STAR™
• 8.12. Researchers from Planar Energy -Devices, Inc., insert a sample into the vacuum chamber of the company' s thin-film deposition system
• 8.13. Planar Energy Devices has advanced the solid-state lithium battery from NREL' s crude prototype (below) to a miniaturized, integrated device (bottom)
• 8.14. Flexible battery that charges in one minute
• 8.15. Nippon Chemi-Con ELDCs - supercapacitors
• 8.16. New Planar Energy Devices high capacity laminar battery
• 8.17. Renata Batteries
• 8.18. Flexion™
• 8.19. Toshiba e-bike battery

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