IoT services for Telecom Service Providers Training Course

Session 1: Business Overview of Why IoT is So Important

• 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
• Smart City
• Energy and cost optimization
• Connected Car and parking
• IoT healthcare
• Business Rule Generation for IoT
• 3 layered architecture of Big Data — Physical (Sensors), Communication, and Data Intelligence

• Connectivity only service – providing SIM inside device, providing special data service for connected device
• Third Party vertical IoT integration - In this approach, the operator partners with a provider of IoT/M2M solutions (solutions that typically comprise hardware and software), reselling the solution, often under its own brand to its own customers. Example applications in this category are fleet management or ePOS systems. Illustrations include Masternaut’s partnerships with Telefonica, Swisscom and KPN. In each case, the Masternaut application and device is sold and supported by the telecoms operator, which uses its own brand.
• Selling internal product : The third approach is for an operator to sell its own solution in selected vertical markets, either developed internally or gained through acquisition and to control the service end to end. Vodafone and Verizon have followed this approach through acquisition (of Cobra and Hughes Telematics respectively) and a number of operators have also developed small, often bespoke, products internally.
• Providing broad menu of M2M services : an operator could concentrate on what common elements it can provide for multiple vertical markets. These could include traditional operator strengths, such as connectivity, but also reach into different areas, such as hosting, support and application enablement.

• 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 the 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.
• Different Kind of Calibration Techniques — manual, automation, infield, primary and secondary calibration — and their implication in IoT
• Powering options for sensors — battery, solar, Witricity, Mobile and PoE
• Hands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.

Demo : Logging data from a temperature sensor

• What is a sensor network? What is ad-hoc network?
• Wireless vs. Wireline network
• WiFi- 802.11 families: N to S — application of 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 of BLE. 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
• Capacity and throughput calculation
• Application issues in wireless protocols — power consumption, reliability, PER, QoS, LOS
• Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN, NB-IoT etc.
• Hands on training with sensor network

Demo : Device control using BLE

• Protocol stack of Mobile app for IoT
• Mobile to server integration –what are the factors to look out
• What are the intelligent layer that can be introduced at Mobile app level ?
• Microsoft Azure IoT
• Amazon AWS-IoT
• Web Interfaces for Mobile Apps ( REST/WebSockets)
• IoT Application layer protocols (MQTT/CoAP)
• Security for IoT middleware- Keys, Token and random password generation for authentication of the gateway devices.

Demo : Mobile app for tracking IoT enabled trash cans/ AWS IoT demo using a MEMS sensor for ambient and motion tracking

• Introduction to Machine learning
• Learning classification techniques
• Bayesian Prediction-preparing training file
• Support Vector Machine
• Predicting failure of the machines -vibrational analysis
• Current signature analysis
• Time series data and prediction
• IoT data visualization
• Security alarms

Demo : Using KNN Algorithm for regression analysis

SVM based classification for image and video analysisDemo :

• low cost of connectivity modules and data transmission
• low energy consumption
• Wide area coverage
• Efficient scalability
• Diversity
• Providing IoT connectivity rural /remote areas -LPWAN, LoRATM
• New 3GPP standard
• Case studies

• Orthogonal multiplex access in 1-4G-why Orthogonal TDM is not good for IoT service connectivity
• Non-orthogonal multiplex access for IoT services-why does it work better for IoT services
• Unified framework for connectivity in Smart City environment & 5G
• Non-orthogonal access to Massive MIMO, Cloud radio access network, full duplexing

• Why security is absolutely essential for IoT
• Mechanism of security breach in IOT layer
• Privacy enhancing technologies
• Fundamental of network security
• Encryption and cryptography implementation for IoT data
• Security standard for available platform
• European legislation for security in IoT platform
• Secure booting
• Device authentication
• Firewalling and IPS
• Updates and patches

• Telematics
• Mobile commerce
• Asset Tracking & Management
• 4G LTE+IOT
• Things Space for IoT Development / Providing IoT platform SAAS /IAAS/PAAS service

• Energy Metering – Smart meters
• Home automation / Temp control/ Security
• Smart Watch
• Smart Health
• Smart Camera

Demo : Smart METER

• 4V- Volume, velocity, variety and veracity of Big Data
• Why Big Data is important in IoT
• Big Data vs legacy data in IoT
• Hadoop for IoT-when and why?
• Storage technique for image, Geospatial and video data
• Distributed database- Cassandra as example
• Parallel computing basics for IoT

Demo : Apache Spark