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Data Analytics for IoT

Data Analytics for IoT - specifically Industrial IoT,

Data Analytics for IoT

  1. 1. ANALYTICS FOR IOT: MAKING SENSE OF DATA FROM SENSORS Muralidhar Somisetty, CTO, Innohabit TechnologiesFeb 17, 2017 IIoT Course @ IISc CCE
  2. 2. Our Vision & Mission: “Innovation as Habit” We Innovate by building Compelling Products. We Build Other’s Innovations with our Technical Competencies and Cutting-Edge Solutions. We Offer Business Services by setting up and operating businesses. We Trigger Innovations through Start-up Mentoring programs. Making Ideas Actionable A Contextual Intelligence Platform with Machine Learning Analytics to offer solutions for IoT, Retail and Enterprises. A SaaS Product for Product Leaders. India’s First Product Management Software in the market. (Cisco) Predictive Network Health Analytics (Cisco) Smart Waste Management with IoT/Analytics. Muralidhar Somisetty Technologist, Entrepreneur, Product Evangelist, Mentor and Certified Yoga Instructor. Current (Work): CTO, Innohabit Technologies. Member, IEEE Computer Society, Bangalore. Past (Work) : Senior Engineering and Product Management Leader at Cisco Systems, India. Education: B.Tech,ECE (NIT @ Warangal) & M.S Computer Science (University of Illinois @ Urbana Champaign) Experience: Telecom, OSS, SaaS, Network Analytics, Machine Learning(ML) & Internet-of-Things (IoT).
  3. 3. Our Company Vision and Mission We Build Amazing Products Innovative We Setup Businesses Build, Operate and Transfer We Build Your Innovations Partner for Solutions We Trigger Innovations Mentoring Innovators “Innovation is our Habit”
  4. 4. IMAGINE: WHAT IF THINGS START TO THINK
  5. 5. 5 http://cdn2.hubspot.net/hubfs/338908/images/Blog_Pictures/Humor_in_IoT.jpg
  6. 6. What is Human Perception of Intelligent Things? Internet of ThingsDigital Human Artificial Intelligence A Boon? A Threat? An Opportunity?
  7. 7. Is Artificial Intelligence an Angel or Demon?
  8. 8. Ethical AI : Effort on to make AI an Angel. Source: OpenAI.com
  9. 9. Let us step back and go through the journey …. What is Big-Data? What is Data Analytics? How BI, Analytics & AI are related to each other? What is the Value of Analytics in Industrial IoT? What is the role of Analytics in IoT?
  10. 10. “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 toward the future.” Salesforce.com
  11. 11. BIG-DATA Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. Social MediaMobile Internet of Things / Sensors Video and Media Web Cloud
  12. 12. Volume (Scale) 13 Earthscope: 67 terabytes of data From 0.8 zettabytes to 35.2 Zettabytes of data LHC: 15 petabytes of data Imagine the volume of data from 104 satellites launched by ISRO…
  13. 13. HOW BIG-DATA IS DIFFERENT FROM TRADITIONAL DATABASE? • Structured /Relational Data • Cost goes up with data size/growth • Well defined models & schemas • ERP, CRM, SCM, BI, App data Traditional data management Big Data • Unstructured data • Scaling at low costs • Flexibility and complex analytics • Distributed processing
  14. 14. WHAT IS DATA ANALYTICS? Data Analytics is the science (and art!) of applying statistical techniques to large data sets to obtain actionable insights for making smart decisions. It is the process to uncover hidden patterns, unknown correlations, trends, and any other useful business information It is Business Intelligence on steroids.
  15. 15. How BI, Analytics, Data Science are related?
  16. 16. Value (Tiers) of Data Analytics
  17. 17. “It is the intelligence of machines and the branch of computer science that aims to create it. It is the study and design of intelligent agents, where an intelligent agent is a system that perceives it environment and takes actions to maximize the chances of success.”
  18. 18. Branches of Artificial Intelligence
  19. 19. Machine Learning A subfield of computer science (CS) and artificial intelligence (AI) that deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions.”
  20. 20. 14/05/2016 Startup Product Management 23 Man Vs Machine
  21. 21. BIG-DATA VENDOR LANDSCAPE Structured Commercial Open source Unstructured (RDBMS) (NoSQL DB)
  22. 22. IOT  ANALYTICS TECHNOLOGY/VENDOR CHOICES
  23. 23. CRM Retaile r System s Data Sources Data Integration Data Storage Data Analytics Data Visualization/ Insights POS Data NFC Tags IoT Sensor sBrand Partners Bluetooth Beacons Wi-Fi Public Data Customers Data Connectors ETL JobsAPIs Streaming Data Queues NoSQL Big-Data Traditional Data warehouse (Like Oracle, Teradata) Streaming, Analytics Engine Machine LearningAnalytical Models Deep Learning Visualization Tools Dwell-Time Analysis FootFall Demographics Campaign Effectiveness A Typical Big-Data Analytics Technology Stack
  24. 24. UNDER-THE-HOOD OF BIG-DATA ANALYTICS
  25. 25. ML Algorithms Mind Map: When to choose what? Source: http://scikit-learn.org/
  26. 26. 14/05/2016 Startup Product Management 30 Tools and Frameworks for Machine/Deep Learning
  27. 27. Analytics in IoT DIVERSE APPLICATIONS
  28. 28. Source: IoT World Forum (IBM, Cisco) IOT Reference Model
  29. 29. Analogy between Human Body and Cognitive IoT
  30. 30. Why is Analytics important in IoT context? Making sense from endless sea of data from sensors is humanly impossible.  (Automate) Decision Making  Operations Efficiency  Preventive Maintenance  Supply Chain Optimization  Competitive Edge  OPEX Savings  …  …
  31. 31. 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.
  32. 32. 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. Machine Learning in Action
  33. 33. Smart Retail: Brick is the IoT AND Mortar is Data Analytics Source: Cisco IoT Retal White Paper
  34. 34. Autonomous Cars • Computer Vision / Neural Networks • Deep Learning in Action Smart Transportation
  35. 35. Analytics for Industrial IoT
  36. 36. Source: McKinsey Industry 4.0
  37. 37. 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.
  38. 38. Top Analytics Applications in Industrial IoT Top-3 Source: https://iot-analytics.com/product/industrial-analytics-report-201617/
  39. 39. Benefits of Analytics Adoption in Industrial IoT Top-3 Source: https://iot-analytics.com/product/industrial-analytics-report-201617/
  40. 40. “The cars are going around the track with thousands of sensors and every time it goes past the pit wall they download a load of data, and the race engineers tell the driver how to drive in response to that data. That’s what we’ve got to do to our factories, we need to have that pit wall somewhere to make sure that your machinery, your systems are working better than the next guy’s.” - Ken Young, Manufacturing Technology Centre, UK
  41. 41. THANK YOU Thoughts/Questions Welcome muralidhars@innohabit.com@muralidhar9

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