1st Edition

Building Enterprise IoT Applications

By Chandrasekar Vuppalapati Copyright 2020
    452 Pages 308 B/W Illustrations
    by CRC Press

    452 Pages 308 B/W Illustrations
    by CRC Press

    McKinsey Global Institute predicts Internet of Things (IoT) could generate up to $11.1 trillion a year in economic value by 2025. Gartner Research Company expects 20 billion inter-connected devices by 2020 and, as per Gartner, the IoT will have a significant impact on the economy by transforming many enterprises into digital businesses and facilitating new business models, improving efficiency and increasing employee and customer engagement. It’s clear from above and our research that the IoT is a game changer and will have huge positive impact in foreseeable future.



    In order to harvest the benefits of IoT revolution, the traditional software development paradigms must be fully upgraded. The mission of our book, is to prepare current and future software engineering teams with the skills and tools to fully utilize IoT capabilities. The book introduces essential IoT concepts from the perspectives of full-scale software development with the emphasis on creating niche blue ocean products. It also:







    • Outlines a fundamental full stack architecture for IoT






    • Describes various development technologies in each IoT layer






    • Explains IoT solution development from Product management perspective






    • Extensively covers security and applicable threat models as part of IoT stack






    The book provides details of several IoT reference architectures with emphasis on data integration, edge analytics, cluster architectures and closed loop responses.

    Table of Contents:

    SECTION I – THE INTERNET OF THINGS (IOT)

    Introduction

    Industry 4.0

    The Man and the Machine – Robots may guide collaboration with Humans

    The Five Forces that shape Industry Competition and Smart Connected Objects

    Digital Twin

    Enterprise IoT Platforms

    Human Touch – artificial intelligence infused Mobile Companion

    The CRISP-PM Process

    References

    SECTION II - END TO END ARCHITECTURES

    Foundation Architectures

    IoT Platform

    IoT Platform Types

    Connectivity Platform

    Use Case: Artik Connectivity Platform

    Technical Case Study: Using IoT to detect water leakages with Powel

    IoT & KDD

    5Vs and IoT

    Intel IoT Data Flow Diagram

    CAP Theorem

    IoT Streams and Reference Architecture

    Data at Rest

    SECTION III - HARDWARE

    Hardware Design

    Arduino IDE Installation

    Arduino Uno Pinout Diagram and Guide

    Tinyduino Humidity Sensor (SI7021)

    Embedded System Architecture

    Hanumayamma Dairy IoT Sensor

    SECTION IV – DATA

    IoT Data Sources

    Enterprise IoT Data Sources

    Physical Asset Perspective – "Things that Spin"

    Industrial IoT Data Sources

    Sensors

    Use Case: Investment in IoT is investment in our future generations’ Safety & Security

    Industrial Use Case: Connected Bus and Mass Transportation

    Sensors Performance and Characteristic definitions

    Case study

    Type of Sensors

    Basic Sensors

    Motion Sensors

    Accelerometer App

    Accelerometer Play App – a precursor to Digital Twin Apps

    Magnetometer App

    The Role of Sensors in Healthcare & Wellness

    Use Case: A SYSTEM TO DETECT MENTAL STRESS USING MACHINE LEARNING AND MOBILE DEVELOPMENT

    Health Fitness IoT App

    Step Counter Value

    Android Batch Step Sensor Sample

    Full Sensor & Data List

    Core Motion Framework in iOS

    Core Motion iOS Code

    Pedometer App

    Reservoir Use Case

    Audio Sensors

    Video Sensors

    Image Texture Data

    IRES Image Retina Data

    Geospatial Data

    References

    IoT Data Collectors

    Use Case: Note to my great-great Grand Kids: I am Sorry

    Data Collector Algorithms

    Audio Signal Data

    Image Texture Extraction – Histograms

    References

    Data Storage

    Data in Motion: Data representations

    Files in C

    EPROM Data Storage

    Android Data Storage

    SQLite

    SQLite and Embedded C App

    SQL Storage

    iOS Data Storage

    Tensors as Storage

    References

    SECTION V: DATA SCIENCE

    Machine Learning at the Edge

    Use Case: Intelligent Dispenser for Long Tail Venues

    Supervised Learning Techniques useful for small form factor devices

    Clustering

    Use Case: Smart City – Intelligent Dispenser

    Sliding Window

    Model Equation – Regression Analysis

    Kalman Filter

    K-Means Clustering

    Use Case: Sensor Signal and Data Interference & Machine Learning

    Fuzzy Logic (FL)

    Reinforcement Learning (RL)

    Neural Networks

    Voice Detection (Neural Networks)

    Tensor Flow execution on embedded Microcontroller Units (MCUs)

    Edge to Cloud Amalgamation – Traffic Light Sensors as law enforcement devices

    Hotels and Entertainment and Dynamic Pricing (Harmonious dancing for calculating

    the best price – both for industry and Patrons – a Win-Win)

    References

    SECTION VI: CONNECTIVITY

    Connectivity

    5G Network

    Use Case: Low Power Wide Area (LPWA) and Cellular IoT

    REST

    CoAP (Constrained Application Protocol)

    Bluetooth Low Energy (BLE)

    iOS App – IoT made easy - Sensor Tag

    Android

    Hanumayamma Dairy IoT Design

    Use Case: Dairy Application – Cow Necklace

    MQTT

    IoT and Hardware Clocks

    MQTT Signals

    MQTT Client

    MQTT Wireshark Captures

    ECG or Electrocardiogram Sesnors

    References

    SECTION VII – CLOUD COMPUTING

    Middleware

    Message Architectures

    Apache Kafka

    Installation of Kafka

    Apache Spark

    References

    IoT Data Analytics Platform

    Data Processing Architecture

    Data Acquisition Systems

    Insight Value Chain

    References

    Future

    Dedication

    Acknowledgement

    Appendix

    Biography

    Chandra is a Software IT Executive with diverse experience in Software Technologies, Enterprise Software Architectures, Cloud Computing, Big Data Business Analytics, Internet Of Things (IoT), and Software Product & Program Management. Chandra held engineering and Product leadership roles at GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies, a Bell Laboratories Company. Chandra teaches Software Engineering, Mobile Computing, Cloud Technologies, and Web & Data Mining for Masters program in San Jose State University. Additionally, Chandra held market research, strategy and technology architecture advisory roles in Cisco Systems, Lam Research and performed Principal Investigator role for Valley School of Nursing where he connected Nursing Educators & Students with Virtual Reality technologies. Chandra has functioned as Chair in numerous technology and advanced computing conferences such as: IEEE Oxford, UK, IEEE Big Data Services 2017, San Francisco USA and Future of Information and Communication Conference 2018, Singapore. Chandra graduated from San Jose State University Masters Program, specializing Software Engineering, and completed his Master of Business Administration from Santa Clara University, Santa Clara, California, USA