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Data Analytics for IoT - BrightTalk Webinar

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The growth on the Internet of Things (IoT) has been astonishing.

From Home to Cities,
Wearables to Driverless Cars, Agriculture to Factories ,
more and more things are being connected and embedded with technology and generating big-data.

- When Data became really ‘Big-Data’?
- What are the characteristics/complexities of Big-Data in IoT?--
- What is the role of Analytics and How is it different in IoT context?
- What are the use-cases of IoT with Analytics in Action?
- When AI meets IoT: Frameworks, Tools, Technologies

Veröffentlicht in: Technologie
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Data Analytics for IoT - BrightTalk Webinar

  1. 1. BIG-DATA ANALYTICS FOR IOT: MAKING SENSE OF DATA FROM SENSORS Muralidhar Somisetty : CTO/Co-Founder, Innohabit Technologies © 2017: Innohabit Technologies and/or it’s affiliates. All rights reserved.
  2. 2. 2 http://cdn2.hubspot.net/hubfs/338908/images/Blog_Pictures/Humor_in_IoT.jpg Imagine Future: when things start to think ☺
  3. 3. Is Artificial Intelligence an Angel or Demon? Man To Machine: Welcome to the Era of Intelligent Systems
  4. 4. Agenda: Let’s step back to understand this evolution better… When Data became really ‘Big-Data’? What are the characteristics/complexities of Big-Data in IoT? AI in IoT : Frameworks, Tools, Technologies What are the use-cases of IoT with Analytics in Action? What is the role of Analytics and How is it different in IoT context? Conclusion
  5. 5. “Welcome to the Internet of Customers. Behind every app, every device, and every connection, is a customer. Billions of them. And each and every one is speeding towards the future.” - Salesforce.com A new wave of Internet generation: SMAC, IoT Source: Salesforce.com
  6. 6. Images: SmartInsight Data Tsunami hit the shores faster than ever…
  7. 7. Big data is defined as the collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing methods.
  8. 8. IoT is adding more fuel to Big-Data Explosion The growth on the Internet of Things (IoT) has been astonishing. From Home to Cities, Wearables to Driverless Cars, Agriculture to Factories , more and more things are being connected and embedded with technology and generating big- data.
  9. 9. Source: IoT World Forum (IBM, Cisco) IoT Reference Architecture
  10. 10. Big-Data Complexity and Characteristics in IoT
  11. 11. IoT/Analytics System Architecture
  12. 12. Data Analytics: Brain behind the IoT Systems. Image Source:: Dr. Mazlan Abbas (IoT Evangelist / Speaker)
  13. 13. ESSENSE OF DATA ANALYTICS It is the process to uncover hidden patterns, unknown correlations, trends, and any other useful business information “No one ever made a decision because of a number. They need a story. The value of data lies in the narrative of the story as to why and what to do next.” - James Richardson, Gartner Research Director Data Analytics is the science (and art!) of applying statistical techniques to large data sets to obtain actionable insights for making smart decisions.
  14. 14. Business Intelligence to Data Analytics
  15. 15. What makes IoT Analytics different? Source: Gartner BI Summit, 2016
  16. 16. Why Analytics is so critical for IoT? REAL-TIME/ FAST DATA IN MOTION PERISHABLE DATA AND ITS SHELF LIFE JUST-IN-TIME RESPONSE WITH ACTIONABLE INSIGHTS Data at the Edge of IoT networks is lightning fast and time-sensitive Making sense from endless sea of data from sensors is practically impossible without data analytics.
  17. 17. Typical IoT Scenario: Abundance of Data , Scarcity of Insights McKinsey reported on IoT analytics use cases and found that an oil rig with 30,000 sensors used only 1% of its data — that’s right, one percent.
  18. 18. The Wheel of IoT : Sensing to Making Sense Image Source:: i-scoop IOT guide
  19. 19. IoT Use-Cases: Analytics in Action DIVERSE APPLICATIONS
  20. 20. Smart Wearables (Eg., Fitbit) Smart Assistants (Eg., Home, Echo) Consumer IoT/Analytics Use-Case Scenarios Smart Cam (Eg., Dropcam, GoPro) • Lifestyle (Habit) Tracker • Emergency Care (advanced) • Behavioural Analytics • Predictive Analytics • Interactive Chatbots • Smart Home + Skills App Platform • Voice Analytics • Deep/Reinforcement Learning • Connected Cameras • Live Streaming + Social Media • Imaging/ Video Analytics • Optimization Algorithms
  21. 21. IOT/Analytics @ Smart Home Key Use-Cases: ▪ Home Automation ▪ Energy Optimization ▪ Safety & Security ▪ Baby/Elderly Remote Care Analytics in Action: ▪ Embedded Intelligence in Sensors/Gateways ▪ Real-Time Streaming Analytics ▪ Time Series Forecasting: Patterns, Anomaly ▪ Decision Sciences at the Edge.
  22. 22. Home Automation: Autonomous Vacuum Cleaners • Learns Home Layout and Remembers It. • Adapts to Different Surfaces or New Items • Improvises on movement pattern for efficiency • Knows when to recharge and automatically docks itself • Smart IoT Device controlled via remote Mobile App • Piezoelectric , Optical Onboard Sensors • Employs Machine Learning to Adapt and Improvise. iRobot: Advanced Machine Learning in Action
  23. 23. IoT/Analytics for Smart Cities: Increasing Quality of Public Life Telecom Renewable Energy Water ResourcesRetail Cloud Signage PrescriptiveAnalytics Telco OSS/BSS Geo-Fencing, Enterprise VAS 4G/5G IoT Applications PersonalizedShoppingExperience Smart Signages, Seamless Checkout Energy Efficiency, Operational Intelligence,PredictiveMaintenance Leakage Detection, Utilization Analytics,Predictive Maintenance Real-Time Streaming Big-Data IoT Stack Grid/Sensor Network ML/DL Models Push Notifications
  24. 24. Smart Retail: Brick is the IoT AND Mortar is Data Analytics ImageSource: Cisco IoT RetailWhite Paper Shopper Exprience Planogram Compliance Staff Optimization
  25. 25. Data Sciencein Action in SmartRetail Engagement • Footfall Demographics • Dynamic Classification • Dwell Time Analytics • Preferred Shopping Path • Sentiment Analysis Personalization • Shopper Profile • Purchase Patterns • Brand Affinity Analysis • Product/Offer Recommender Optimization • Audience Impressions • Campaign Effectiveness • Product Placement Strategies • Propensity, inference, trends, engagement, reach, ranking, comparisons, etc.
  26. 26. Industrial IoT/4.0: Connected Factories Amazon embraced IoT/ Industry 4.0 streamlining their factory, fulfilment, shipping and storage experiences. • Smart Storage Systems • Automated Order Fulfilment Centres • Supply Chain Optimization • Robotics, Drones in Action • Baseline Analytics for Machine Performance • Automated Order Fulfilment Centres • Predictive Failure Detection of Various Machines • Deep Learning Algorithms in Action Image Source: http://money.cnn.com/2016/10/06/technology/amazon-warehouse-robots/
  27. 27. AI to IA: Value of Data Analytics in Industrial IoT In the industrial space, there is a great deal of interest in using analytics to optimize asset maintenance, production operations, supply chain, product design, field service, and other areas.
  28. 28. Top Analytics Use-Cases in Industrial IoT Source: https://iot-analytics.com/product/industrial-analytics-report-201617/
  29. 29. IoT /Analytics Top Use-Cases By Sector
  30. 30. When AI meets IoT Artificial Intelligence provides us the framework and tools to go beyond trivial real-time decision and automation use cases for IoT.
  31. 31. Branches of Artificial Intelligence
  32. 32. IOT  ANALYTICS TECHNOLOGY/VENDOR CHOICES
  33. 33. 14/05/2016 STARTUP PRODUCT MANAGEMENT 33 Tools and Frameworks for Machine/Deep Learning
  34. 34. ML Algorithms Mind Map: When to choose what? Source: http://scikit-learn.org/
  35. 35. THANK YOU Thoughts/Questions Welcome muralidhars@innohabit.com@muralidhar9
  36. 36. Webinar Synopsis Big data analytics is undoubtedly one of the most exciting areas in computing today, and remains an area of fast evolution. Thanks to the data deluge from millions of sensors from IoT networks, it is humanly impossible to analyse and make sense of the data from sensors without analytics tools and processes. In this webinar, we will go over basics of big-data analytics, how analytics is different from traditional data warehouses or business intelligence systems, different tiers of data analytics etc., We will also see different use-cases of IoT from Smart Home to Transporation to Smart City context and how analytics can be applied for various use-cases for actionable insights. Webinar also briefly touches upon machine learning tools / techniques that are available as-a-service on cloud today.

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