Location-Based Sensor Fusion: Technologies, Applications, and Markets

As "always-on" location in smartphones becomes a core part of retail, ambient intelligence, mobile advertising, and the quantified self, sensors have been identified as a key element in supporting high-accuracy, ubiquitous, indoor and outdoor location. Combined with GPS, Wi-Fi, Bluetooth, and other technologies it can enable consistent performance, across a range of different environments. However, sensors suffer from inherent problems that significantly limit their ability in supporting indoor location today. This report aims to identify how these problems are being overcome, who is best placed to do so, and the revenue that will be generated as a result.

The report considers the role that MEMS vendors, GNSS/Connectivity IC OEMS, and sensor/data fusion start-ups can play in enabling this market. It looks at the adoption of multi-axis sensors, the future development of sensor fusion, and how it can be combined with GNSS, connectivity and a host of other emerging data sources to enable high-accuracy data fusion, indoor location, and analytics. Forecasts are provided for motion sensors in handsets, adoption of location-based sensor fusion, and sensor fusion software revenues. A comprehensive review of important location-based sensor fusion companies is also provided.

Table of Contents

  • 1. MICRO-ELECTRO-MECHANICAL SYSTEMS
    • 1.1. Introduction
    • 1.2. Accelerometers
    • 1.3. Gyroscopes
    • 1.4. Altimeters (Pressure Sensors)
    • 1.5. Magnetometers
    • 1.6. Accelerometer + Magnetometer
    • 1.7. Accelerometer + Gyroscope
    • 1.8. - Compass + Gyro + Accelerometer
    • 1.9. Sensor Fusion Hubs
    • 1.10. Sensor Fusion Hubs versus Location-based Sensor Fusion Hubs
    • 1.11. Sensor Fusion Ecosystem
      • 1.11.1. Sensor OEM Level
      • 1.11.2. Connectivity / GPS IC Level
      • 1.11.3. Hardware-agnostic Third Parties
      • 1.11.4. Routes to Market for Start-ups
    • 1.12. How Does Sensor Fusion Improve Indoor Location
      • 1.12.1. GNSS and Pedestrian Navigation Aid
      • 1.12.2. "Filling in the Gaps"
      • 1.12.3. Machine Intelligence
      • 1.12.4. The Move to Handset-based Indoor Location / Data Fusion
      • 1.12.5. Crowdsourced RF Mapping / SLAM
      • 1.12.6. Google Tango and 3D SLAM
      • 1.12.7. Tango Can Improve Location Performance
      • 1.12.8. Current Mapping and Indoor Location Implementations of Tango
      • 1.12.9. Is the Sensor Industry Missing a Trick?
      • 1.12.10. BLE Beacons as Key Drivers for Location-based Sensor Fusion
      • 1.12.11. BLE and Sensor Fusion: A Symbiotic Relationship
      • 1.12.12. Indoor Location Improves Existing Sensor Fusion Applications
    • 1.13. Location-based Applications
      • 1.13.1. Hyperlocal Search
      • 1.13.2. Facebook Is Starting to Get Serious
      • 1.13.3. Social
      • 1.13.4. Retail / Venues
      • 1.13.5. Navigation
      • 1.13.6. Fitness, Health, and Personal Tracking
      • 1.13.7. Enterprise
      • 1.13.8. BLE Tags: A Sensor Fusion Market in of Itself
      • 1.13.9. Ambient Intelligence
      • 1.13.10. Augmented Reality
      • 1.13.11. Connected Home
      • 1.13.12. Personal Location and Asset Tracking
  • 2. LOCATION-BASED SENSOR FUSION FORECASTS
  • 3. OVERVIEW OF KEY PLAYERS
    • 3.1. MEMS Sensor Vendors
      • 3.1.1. AKM
      • 3.1.2. Analog Devices
      • 3.1.3. Bosch Sensortec
      • 3.1.4. CyweeMotion Ltd.
      • 3.1.5. Freescale Semiconductor
      • 3.1.6. Broadcom
      • 3.1.7. Fullpower Technologies
      • 3.1.8. Qualcomm
      • 3.1.9. QuickLogic
      • 3.1.10. PNI Corp.
      • 3.1.11. Hillcrest
      • 3.1.12. Indoo.rs
      • 3.1.13. InvenSense
      • 3.1.14. Kionix (ROHM)
      • 3.1.15. MEMSIC
      • 3.1.16. STMicroelectronics
      • 3.1.17. SenionLab
      • 3.1.18. Audience / Sensor Platforms

Charts

  1. MEMS Sensor Shipments in Handsets, World Market, Forecast: 2013 to 2019
  2. MEMS Combo-sensor Shipments in Handsets, World Market, Forecast: 2013 to 2019
  3. MEMS Location-based Sensor Fusion Software Installations by Vendor Type, World Market, Forecast: 2012 to 2019
  4. MEMS Location-based Sensor Fusion Software Revenue by Vendor Type, World Market, Forecast: 2012 to 2019
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Research Information

Price
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Publish Date
1Q 2015
Code
AN-1630
Research Type
Technology Analysis Report
Pages
26