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1. | EXECUTIVE SUMMARY AND CONCLUSIONS |
1.1. | Definitions and scope |
1.2. | A natural next stage |
1.3. | IoT infrastructure |
1.4. | IoT contrasted with IoP |
1.5. | IoT value chain and bias vs IoP |
1.6. | Potential applications examples |
1.6.1. | Losing privacy, committing crime, solving crime |
1.7. | Examples of IoT opportunities and suppliers |
1.8. | Hype and nonsense |
1.9. | The bigger vision |
1.10. | But wider deployment means compromises and new challenges |
1.11. | Some megatrends favour IoT: others do not |
1.12. | Impediments to IoT |
1.13. | System and software issues |
1.13.1. | Severe security breaches continue |
1.13.2. | Choosing a low power WAN |
1.13.3. | Sensor fusion |
1.13.4. | Artificial intelligence: deep learning |
1.13.5. | Lower power ICs, more frugal node activation |
1.14. | Hardware |
1.14.1. | IoT nodes: basics |
1.14.2. | System on a Chip (SoC) |
1.14.3. | Microcontroller units (MCUs) |
1.14.4. | Anatomy of a generic device |
1.14.5. | Compute power |
1.14.6. | How are microcontrollers used? |
1.14.7. | Capabilities, limitations, application |
1.14.8. | Beyond microcontrollers |
1.14.9. | Single Board Computer SBC |
1.14.10. | Internet of Things nodes |
1.14.11. | New IoT formats: RFMOD's BeanIoT |
1.14.12. | IoT node with up to ten sensors and battery power: cost structure excluding batteries |
1.14.13. | Energy harvesting EH choice |
1.14.14. | 1Wi-Fi harvesting |
1.15. | Investment in IoT development 2014-2020 |
1.16. | Industry standards ferment and SIGfox, NBIOT etc contention |
1.17. | Market forecasts 2017-2027 |
1.17.1. | Internet of Things forecasts 2017-2027 - numbers (billions) |
1.17.2. | Internet of Things forecasts 2017-2027 - unit price (US$) |
1.17.3. | Internet of Things forecasts 2017-2027 - node market value ex-factory (US$ billions) |
1.17.4. | IoT systems globally 2017-2027 (US$ billions) |
1.17.5. | Allied market forecasts and data |
1.17.6. | EV and 48V mild hybrid global forecasts number K 2017-2027 |
1.17.7. | IDTechEx EV and 48V mild hybrid global forecasts $ billion 2017-2027 |
1.17.8. | On-road Level 4/5 autonomous vehicles forecasts |
1.17.9. | Ten-year market forecasts for all agricultural robots and drones segmented by type and/or function |
1.17.10. | Ten-year market forecasts for agricultural robots and drones segmented by type and/or function |
1.17.11. | Market for IoT wearable devices: medical |
2. | INTRODUCTION |
2.1. | What is IoT? |
2.2. | Example of possible applications: wearable IoT |
2.3. | The IoT dream |
2.4. | Many rename existing things without IP addresses as IoT: this is unhelpful |
2.5. | Heroic forecasts retained despite a quiet 2016 |
2.6. | Why is IoT gaining attention? |
2.6.1. | Primary driver |
2.6.2. | New technology |
2.6.3. | Oil and gas |
2.6.4. | Manufacturing etc. Bosch view |
2.6.5. | Utilities |
2.6.6. | Transportation |
2.6.7. | Automotive |
2.6.8. | Retail |
2.6.9. | Local government |
2.6.10. | Smart home |
2.6.11. | Bottom line |
2.7. | Automotive IoT in more detail |
2.7.1. | Introduction |
2.7.2. | Sensors: IoT potential for insight, safety, performance |
2.7.3. | Automobiles mapping pollution |
2.7.4. | Automobile and smart home |
2.7.5. | Cars as an IoT subscription service |
2.7.6. | Some trends resulting |
2.7.7. | Recent Acquisitions and mergers in automotive IoT |
2.8. | Impediments |
2.9. | Disagreements and uncertainty |
2.10. | System and node operational improvements |
2.10.1. | Overview of advances proceeding |
2.10.2. | Lower power ICs and different design approach facilitate low power EH adoption |
2.10.3. | Node to Node or Big Data? |
3. | CORE MICROCONTROLLER UNIT MCU TECHNOLOGIES |
3.1. | Manufacture |
3.2. | Optimising power consumption |
3.3. | Low power battery backup |
3.4. | MCU architectures |
3.5. | MCU components: memory |
3.6. | MCU components: IO |
3.7. | MCU co-processors: DSPs |
3.8. | MCU co-processors: FPGAs |
3.9. | MCU co-processors: PLDs and CPLDs |
3.10. | MCU software: Operating Systems |
3.11. | MCU software: programming languages |
3.12. | Case study: Texas Instruments MSP430G2333 |
4. | ADJACENT SYSTEM AND SENSOR TECHNOLOGIES |
4.1. | Sensors |
4.1.1. | Inertial measurement units (IMUs) |
4.1.2. | Global Positioning System (GPS) |
4.1.3. | Depth cameras |
4.2. | Communications |
5. | HARDWARE PLAYERS |
5.1. | Renesas Electronics |
5.2. | NXP+Freescale |
5.3. | Microchip+Atmel |
5.4. | Atmel |
5.5. | ST Microelectronics |
5.6. | Infineon Technologies |
5.7. | Texas Instruments (TI) |
5.8. | Cypress/Spansion |
5.9. | Samsung |
5.10. | Intel |
5.11. | Digispark |
5.12. | Arduino/Genuino |
5.13. | Apple |
5.14. | |
5.15. | Amazon |
5.16. | Raspberry Pi Foundation |
5.17. | Beagleboard |
5.18. | Some more MCU prototyping boards... |
5.19. | And many more SBCs... |
6. | SYSTEM AND HARDWARE TRENDS |
6.1. | Benchmarking Clarifies the Future of Internet of Things |
6.2. | Wide Area network choice - LoRaWAN and LoRa Alliance |
6.3. | eRIC |
6.4. | MCU architecture trends: ARM |
6.5. | Open source hardware and systems |
6.6. | Moore's Law |
6.7. | Prices equilibrating |
6.8. | Other MCU trends |
7. | APPENDIX: REPORT FROM THE IBM-ENOCEAN ALLIANCE MEETING |
Slides | 171 |
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Forecasts to | 2027 |