BUSINESS OVERVIEW

• Case Studies from Nest, CISCO and top industries

• IoT adaptation rate in North American & and how they are aligning their future business model and operation around IoT

• Broad Scale Application Area

• Smart house and smart city

• Industrial Internet

• Smart Cars

• Wearables

• Home healthcare

• Business Rule generation for IoT

• 3 layered architecture of Big Data –Physical (Sensors), Communication and Data Intelligence

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INTRODUCTION OF IOT

• Basic function and architecture of a sensor –Sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor network- All basics about the sensors

• Development of sensor electronics- IoT vs legacy and open source vs traditional PCB design style

• Development of Sensor communication protocols –history to modern days. Legacy protocols like Modbus, relay, HART to modern day Zigbee, Zwave, X10,Bluetooth, ANT etc..

• Business driver for sensor deployment- FDA/EPA regulation, Fraud/tempering detection, supervision, Quality control and process management

• Different Kind of Calibration Techniques-manual, automation, infield, primary and secondary calibration –their implication in IoT

• Powering options for sensors-Battery, solar, Witricity. Mobile and PoE

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SENSOR NETWORK AND WIRELESS PROTOCOL

• What is a sensor network? What is Ad-hoc network ?

• Wireless vs. Wireline network

• WiFi- 802.11 families: N to S- application of each standards and common vendors.

• Zigbee and Zwave-advantage of low power mesh networking. Long distance Zigbee. Introduction to different Zigbee chips:

• Bluetooth/BLE: Low power vs high power, speed of detection, class ofBLE. Introduction of Bluetooth vendors & their review :

• Creating network with Wireless protocols such as Piconet by BLE

• Protocol stacks and packet structure for BLE and Zigbee

• Other long distance RF communication link

• LOS vs NLOS links

• Sensor network packet architecture

• Capacity and throughput calculation

• Application issues in wireless protocols- power consumption, reliability, PER, QoS, LOS

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REVIEW OF ELECTRONICS PLATFORM

• PCB vs FPGA vs ASIC design-how to take decision

• Prototyping electronics vs Production electronics

• QA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and

• Basic introduction of multi-layer PCB design and its workflow when needed?

• Electronics reliability-basic concept of FIT and early mortality rate

• Environmental and reliability testing-basic concepts

• Basic Open source platforms: Adruino, Rasberry Pi, Beaglebone, RedBack, Diamond Back

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CONCEIVING A NEW IOT PRODUCT

• State of the present art and review of existing technology in the marketplace

• Suggestion for new features and technologies based on market analysis and patent issues

• Detailed technical specs for new products- System, software, hardware, mechanical, installation etc.

• Packaging and documentation requirements

• Servicing and customer support requirements

• High level design (HLD) for understanding of product concept

• Release plan for phase wise introduction of the new features

• Skill set for the development team and proposed project plan -cost & duration

• Target manufacturing price

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INTRODUCTION TO MOBILE APP PLATFORM IOT

• Protocol stack of Mobile app for IoT

• Fundamentals of WAP ( Wireless application protocols)

• Mobile to server integration –what are the factors to look out

• What are the intelligent layer that can be introduced at Mobile app level ?

• iBeacon in IoS

• Global vs Local ID-GUID concept for secured IoT network

• IoT-Middleware case study-1 Axeda

• IoT Middleware case study-2 Xively

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MACHINE LEARNING FOR INTELLIGENT IOT

• Introduction to Machine learning

• Learning classification techniques

• Bayesian Prediction-preparing training file

• Support Vector Machine

• Image and video analytic for IoT

• Fraud and alert analytic through IoT

• Bio –metric ID integration with IoT

• Real Time Analytic/Stream Analytic

• Scalability issues of IoT and machine learning

• What are the architectural implementation of Machine learning for IoT

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ANALYTIC ENGINE FOR IOT

• Insight analytic

• Visualization analytic

• Structured predictive analytic

• Unstructured predictive analytic

• Recommendation Engine

• Pattern detection

• Rule/Scenario discovery –failure, fraud, optimization

• Root cause discovery

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IAAS/PAAS/SAAS

• Iaas : Information as a service-evolving models

• Mechanism of security breach in IOT layer for Iaas

• Middleware for Iaas business implementation in healthcare, homeautomation and farming

• Iaas case study for vehicular information for Auto-insurance and Agriculture

• Paas: Platform as a service in IoT. Case studies of some of the IoT middleware

• Saas : Software/System as service for IoT business models

• European legislation for security in IoT platform

• Firewalling and IPS

• Updates and patches

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DATABASE & PLATFORM IMPLEMENTATION

• SQL vs NoSQL-Which one is good for your IoT application

• Open sourced vs. Licensed Database

• Available M2M cloud platform

• Basic functionality of IoT cloud platform

• Real Time Analytic

• Batch Analytic

• Data storage

• Data filtering

• Rule engine

• Process mapping

• Caching of Data for IoT rule implementation

• Lossless data compression /Data encoding : Huffman and Progressive filtering

• Xively/ Omeg/Ayla/Libellium/CISCO M2M platform /AT &T M2M platform/ Google M2M platform

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COMMON IOT SYSTEMS

• Home automation

• Energy optimization in Home

• Automotive-OBD /Iaas/Paas for Insurance and Car parking

• IoT-Lock

• Smart Smoke alarm

• BAC ( Blood alcohol monitoring ) for drug abusers under probation

• Pet cam for Pet lovers

• Wearable IOT

• Mobile parking ticketing system

• Indoor location tracking in Retail store

• Home health care

• Smart Sports Watch

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BIG DATA FOR IOT

• 4V- Volume, velocity, variety and veracity of Big Data

• Why Big Data is important in IoT

• Big Data vs legacy data in IoT

• Fundamental of Map reduced system (MR)

• Hadoop and HDFS

• Kafka for data messaging and brokerage

• Storm/Bolt/Spout-fundamentals of real time analytic system

• Storage technique for image, Geospatial and video data

• Distributed database like Cassandra and HDFS

• Parallel computing basics for IoT