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
Introduction of IoT: All about Sensors – Electronics
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 sensorsDevelopment of sensor electronics — IoT vs legacy, and open source vs traditional PCB design styleDevelopment of sensor communication protocols — history to modern days. Legacy protocols likeModbus, 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 managementDifferent Kind of Calibration Techniques — manual, automation, infield, primary and secondary calibration — and their implication in IoTPowering options for sensors — battery, solar, Witricity, Mobile and PoEHands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.
Fundamental of M2M communication — Sensor Network and Wireless protocol
What is a sensor network? What is ad-hoc network?Wireless vs. Wireline networkWiFi- 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 BLEProtocol stacks and packet structure for BLE and ZigbeeOther long distance RF communication linkLOS vs NLOS linksCapacity and throughput calculationApplication issues in wireless protocols — power consumption, reliability, PER, QoS, LOSHands on training with sensor network1. PICO NET- BLE Base network2. Zigbee network-master/slave communication3. Data Hubs : MC and single computer ( like Beaglebone ) based datahub
Review of Electronics Platform, production and cost projection
PCB vs FPGA vs ASIC design-how to take decisionPrototyping electronics vs Production electronicsQA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and when needed?Basic introduction of multi-layer PCB design and its workflowElectronics reliability-basic concept of FIT and early mortality rateEnvironmental and reliability testing-basic conceptsBasic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?RedBack, Diamond Back
Conceiving a new IoT product- Product requirement document for IoT
State of the present art and review of existing technology in the market placeSuggestion for new features and technologies based on market analysis and patent issuesDetailed technical specs for new products- System, software, hardware, mechanical, installation etc.Packaging and documentation requirementsServicing and customer support requirementsHigh level design (HLD) for understanding of product conceptRelease plan for phase wise introduction of the new featuresSkill set for the development team and proposed project plan -cost & durationTarget manufacturing price
Introduction to Mobile app platform for IoT
Protocol stack of Mobile app for IoTMobile to server integration –what are the factors to look outWhat are the intelligent layer that can be introduced at Mobile app level ?iBeacon in IoSWindow AzureLinkafy Mobile platform for IoTAxedaXively
Machine learning for intelligent IoT
Introduction to Machine learningLearning classification techniquesBayesian Prediction-preparing training fileSupport Vector MachineImage and video analytic for IoTFraud and alert analytic through IoTBio –metric ID integration with IoTReal Time Analytic/Stream AnalyticScalability issues of IoT and machine learningWhat are the architectural implementation of Machine learning for IoT
Analytic Engine for IoT
Insight analyticVisualization analyticStructured predictive analyticUnstructured predictive analyticRecommendation EnginePattern detectionRule/Scenario discovery — failure, fraud, optimizationRoot cause discovery
