Memories for the Intelligent Internet of Things

Book description

A detailed, practical review of state-of-the-art implementations of memory in IoT hardware 

As the Internet of Things (IoT) technology continues to evolve and become increasingly common across an array of specialized and consumer product applications, the demand on engineers to design new generations of flexible, low-cost, low power embedded memories into IoT hardware becomes ever greater. This book helps them meet that demand. Coauthored by a leading international expert and multiple patent holder, this book gets engineers up to speed on state-of-the-art implementations of memory in IoT hardware.  

Memories for the Intelligent Internet of Things covers an array of common and cutting-edge IoT embedded memory implementations. Ultra-low-power memories for IoT devices-including plastic and polymer circuitry for specialized applications, such as medical electronics-are described.  The authors explore microcontrollers with embedded memory used for smart control of a multitude of Internet devices. They also consider neuromorphic memories made in Ferroelectric RAM (FeRAM), Resistance RAM (ReRAM), and Magnetic RAM (MRAM) technologies to implement artificial intelligence (AI) for the collection, processing, and presentation of large quantities of data generated by IoT hardware. Throughout the focus is on memory technologies which are complementary metal oxide semiconductor (CMOS) compatible, including embedded floating gate and charge trapping EEPROM/Flash along with FeRAMS, FeFETs, MRAMs and ReRAMs.

  • Provides a timely, highly practical look at state-of-the-art IoT memory implementations for an array of product applications
  • Synthesizes basic science with original analysis of memory technologies for Internet of Things (IoT) based on the authors' extensive experience in the field
  • Focuses on practical and timely applications throughout
  • Features numerous illustrations, tables, application requirements, and photographs
  • Considers memory related security issues in IoT devices

Memories for the Intelligent Internet of Things is a valuable working resource for electrical engineers and engineering managers working in the electronics system and semiconductor industries. It is also an indispensable reference/text for graduate and advanced undergraduate students interested in the latest developments in integrated circuit devices and systems. 

Table of contents

  1. Cover
  2. Introduction to the Intelligent Internet of Things
  3. 1 Smart Cities as the Prototype of the Intelligent Internet of Things
    1. 1.1 Overview
    2. 1.2 Smart Cities
    3. 1.3 Smart Commerce as an Element of the Smart City
    4. 1.4 Smart Residences
    5. 1.5 People as Center of Smart Connected Homes
    6. 1.6 Smart Individual Transportation
    7. 1.7 Smart Transportation Networks
    8. 1.8 Smart Energy Networks
    9. 1.9 Smart Connected Buildings
    10. 1.10 Thoughts
    11. References
  4. 2 Memory Applications for the Intelligent Internet of Things
    1. 2.1 Introduction
    2. 2.2 Comparisons of the Various Nonvolatile Embedded Memories Characteristics
    3. 2.3 Circuits Using Ultralow Power MCU with Embedded Memory for Energy Harvesting
    4. 2.4 Ultralow Power Battery Operated Flash MCU
    5. 2.5 Nonvolatile MCUs Using Emerging Memory for Nonvolatile Logic
    6. 2.6 Communication Protocols for Memory Sensor Tags
    7. 2.7 Wearable Medical Devices
    8. 2.8 Low Power Battery Operated Medical Devices and Systems
    9. 2.9 Automotive Network Applications
    10. 2.10 Smart Electrical Grid and Digital Utility Smart Meters
    11. 2.11 Consumer Home Systems and Networks
    12. 2.12 Motor Control Chips with Embedded Memory
    13. 2.13 Smart Chip Cards in Advanced Applications
    14. 2.14 Analysis of Big Data Server Memory Hierarchy for Storing IoT
    15. References
  5. 3 Embedded Flash and EEPROM for Smart IoT
    1. 3.1 Introduction to eFlash and eEEPROM for Smart IoT
    2. 3.2 Single Poly Floating Gate eFlash/EEPROM Cells for IoT
    3. 3.3 eFlash Cells Using Multiple Single Polysilicon CMOS Logic Transistors
    4. 3.4 Split Gate Technology for Floating Gate Embedded Flash
    5. 3.5 Stacked Flash and Processor TSV Integration
    6. 3.6 OTP/MTP Embedded Flash Cells and Fuses
    7. 3.7 Stacked Gate Double Poly Flash
    8. 3.8 Charge Trapping eFlash
    9. 3.9 Split Gate CT eFlash Nanocrystal Storage
    10. 3.10 Novel Embedded Flash Memory
    11. References
  6. 4 Thin Film Polymer and Flexible Memories
    1. 4.1 Overview
    2. 4.2 Organic Ferroelectric Memories
    3. 4.3 Polymer Ferroelectric Tunnel Junctions
    4. 4.4 Types and Characteristics of Polymer Resistive RAMs with Flexible Substrate
    5. 4.5 Charge Trapping Nanoparticle (NP) Memory on Flexible Substrates
    6. 4.6 Transfer of Conventional Memory Chips on to Flexible Substrates
    7. References
  7. 5 Neuromorphic Computing Using Emerging NV Memory Devices
    1. 5.1 Overview of Resistive RAMs and Ferroelectric RAMs in Neuromorphic Systems
    2. 5.2 Various Resistive RAMs for use as Synapses in Neuromorphic Systems
    3. 5.3 3D Neuromorphic Memories
    4. 5.4 Modeling and Characterization of RRAMs as Synaptic Devices
    5. 5.5 Spiking Neural Nets, STDP, Potentiation, and Depression
    6. 5.6 Neural Network Systems Using Ferroelectric RAM Technology
    7. 5.7 Early Neuromorphic Computers Using Phase Change Memory
    8. 5.8 Resistive RAMs in Neuromorphic System Design and Application
    9. 5.9 Neuromorphic Memories Using Polymer and Flexible Memories
    10. References
  8. 6 Big Data Search Engines and Deep Computers
    1. 6.1 Overview of Big Data Search Engines and Deep Computers
    2. 6.2 Content Addressable Memories Made Using Various Emerging Nonvolatile Memories
    3. 6.3 Components of Large Search Engines and Artificial Neural Networks
    4. 6.4 Memory Issues in Deep Learning Systems
    5. 6.5 Deep Neural Nets for IoT
    6. References
  9. 7 Memory in Security Issues for IoT
    1. 7.1 Introduction to Memory in Security Issues for IoT
    2. 7.2 Memories Used as Physical Unclonable Functions (PUFs)
    3. 7.3 On‐Chip Memory‐Based Security Systems
    4. References
  10. Index
  11. End User License Agreement

Product information

  • Title: Memories for the Intelligent Internet of Things
  • Author(s): Betty Prince, David Prince
  • Release date: June 2018
  • Publisher(s): Wiley
  • ISBN: 9781119296355