Building Enterprise IoT Applications

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

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 technologyand 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