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IOT and Big Data - The Perfect Marriage

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If you have somehow missed the hype, the Internet of Things (IoT) is a fast-growing constellation of internet-connected sensors attached to a wide variety of 'things'. Sensors can take a multitude of possible measurements, Internet connections can be wired or wireless, while 'things' can literally be any object to which you can attach or embed a sensor. If you carry a smartphone, for example, you become a multi-sensor IoT 'thing', and many of your day-to-day activities can be tracked, analysed and acted upon.

Many of the conversations taking place around the IoT are incomplete without a mention of big data. Big data is characterised by “4 V’s”: volume, variety, velocity and veracity. That is, big data comes in large amounts (volume), is a mixture of structured and unstructured information (variety), arrives at (often real-time) speed (velocity) and can be different levels of uncertainty (veracity).

As organizations step into IoT, they must understand the symbiotic relationship between IoT and big data. Just like with any big-data play, merely collecting the data isn't enough. The data must be processed and analyzed to derive meaningful insights, and those insights must drive actionable steps that can improve the business.

What that means is that, without Big Data, the IoT can offer an enterprise little more than noise. But wait…! On the other hand, without IoT, the Big Data is little more than any other software lying idle. Actually you need two to Tango. That’s when you get the perfect marriage!

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IOT and Big Data - The Perfect Marriage

  1. 1. Copyright © RIOT 2015 All Rights Reserved INTERNET OF THINGS & BIG DATA THE PERFECT MARRIAGE Dr. Mazlan Abbas CEO, REDtone IOT Sdn Bhd International Conference on Soft Computing in Data Science 2015 (SCDS2015), 2-3 Sept. 2015, Pullman, Putrajaya
  2. 2. Copyright © RIOT 2015 All Rights Reserved THE PERFECT MARRIAGE •  Introduction - Internet of Things and its Business Opportunities •  Making Sense of Data •  Encourage Adoption and Innovation of IoT •  IOT and Big Data Marriage Challenges •  Summary
  3. 3. Copyright © RIOT 2015 All Rights Reserved How Big is the IOT Market?
  4. 4. Copyright © RIOT 2015 All Rights Reserved HOW IS IT DIFFERENT FROM M2M?
 THE CURRENT ERA OF IOT
  5. 5. Copyright © RIOT 2015 All Rights Reserved CHANGE IN BUSINESS MODEL
  6. 6. Copyright © RIOT 2015 All Rights Reserved [Source: http://postscapes.com/what-exactly-is- the-internet-of-things-infographic ]
  7. 7. Copyright © RIOT 2015 All Rights Reserved 10/90 RULE The Last 100 meter connectivity The “last 100 meters” represent > 90% potential number of connections Today, the devices used in the “last 100 meters” are typically not connected. The wide-area network is to a larger extent connected e.g. through smartphones, home routers (e.g. ADSL routers) and GSM / 3G / 4G Routers. Still DisconnectedConnected World
  8. 8. Copyright © RIOT 2015 All Rights Reserved FUTURE OF COMMUNICATIONS AND PRODUCTIVITY
 BRING IOT TO THE NEXT LEVEL
  9. 9. Copyright © RIOT 2015 All Rights Reserved Improved Performance Reduced Costs Create Innovative Products New Revenue Streams Monitor Autonomous Optimize Control BUSINESS OPPORTUNITIES Capabilities Benefits
  10. 10. Copyright © RIOT 2015 All Rights Reserved Security and Privacy of data Managing vast amounts of data Fragmented industry Finding the right business model WHAT ARE THE BUSINESS CHALLENGES
  11. 11. Copyright © RIOT 2015 All Rights Reserved WHY TELCOS HAVE DIFFICULTY TO EMBRACE IOT 4 REASONS
  12. 12. Copyright © RIOT 2015 All Rights Reserved LEGACY BUSINESS IS STILL CONNECTIVITY M2M HIGH VOLUME LOW ARPU SIM-CARD BASED OLD HABITS DIE HARD LESS COMPLEX
  13. 13. Copyright © RIOT 2015 All Rights Reserved LACK OF DOMAIN EXPERTISE THINK BEYOND CONNECTIVITY SOLUTIONS, SELLING AND MANAGED SERVICES NEED GO-TO-MARKET PARTNER
  14. 14. Copyright © RIOT 2015 All Rights Reserved MINDSET BLOCK FULL OF SKEPTISM LOW SINGLE DIGIT GROWTH CONTRIBUTION
  15. 15. Copyright © RIOT 2015 All Rights Reserved STABLE BUSINESS VS. RISKY VENTURES NEED TO WORK LIKE STARTUP IOT BUSINESS IS FLUID
  16. 16. Copyright © RIOT 2015 All Rights Reserved END-TO-END IOT SERVICE PROVIDER THE END GAME
  17. 17. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e END-TO-END IOT SERVICE PROVIDER Device Provider Network Provider Platform Provider Application Provider Customer Network Platform
  18. 18. Copyright © RIOT 2015 All Rights Reserved CONNECTIVITY PLAYER PHASE-1
  19. 19. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL Device Provider Network Provider Platform Provider Application Provider Customer Network Platform Platform 1
  20. 20. Copyright © RIOT 2015 All Rights Reserved IOT ENABLER PLAYER PHASE-2
  21. 21. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL Device Provider Network Provider Platform Provider Application Provider Customer Network Platform 2
  22. 22. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL Device Provider Network Provider Platform Provider Application Provider Customer Network Platform IOT Subsidiary 3
  23. 23. Copyright © RIOT 2015 All Rights Reserved IOT SOLUTIONS PLAYER PHASE-3
  24. 24. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL Device Provider Network Provider Platform Provider Application Provider Customer Network Platform 4
  25. 25. Copyright © RIOT 2015 All Rights Reserved IOT SERVICE PROVIDER PHASE-4
  26. 26. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL Device Provider Network Provider Platform Provider Application Provider Customer Network Platform 5
  27. 27. Copyright © RIOT 2015 All Rights Reserved s m a r t c i t y smart transport s m a r t a u t o m o t i v e BUSINESS MODEL -HYBRID Device Provider Network Provider Platform Provider Application Provider Customer Network Platform 6
  28. 28. Copyright © RIOT 2015 All Rights Reserved MAKING SENSE OF SENSOR DATA … BUT WHAT DATA? THE GOLD RUSH
  29. 29. Copyright © RIOT 2015 All Rights Reserved TO OVERCOME 3 KEY CHALLENGES Only by addressing all three can organizations turn raw data into information and actionable insights. Integrating data from multiple sources Automating the collection of data Analyzing data to effectively identify actionable insights
  30. 30. Copyright © RIOT 2015 All Rights Reserved Wisdom Knowledge Information Data More Important Less Important Evaluated understanding Appreciation of Answers to questions. Symbols Understanding Answers to questions WHO WHY HOW WHAT WHERE WHEN VALUE IS CREATED BY MAKING SENSE OF DATA VALUE PYRAMID
  31. 31. Copyright © RIOT 2015 All Rights Reserved Wisdom Knowledge Information Data More Important Less Important N/A Empty (0), Full (1) Understanding EXAMPLE SMART PARKING Who park at this lot? What kind of vehicle? Where is the empty parking lot? When is the peak period? How to implement a tiered charging? How to find “overstayed” vehicles? Why this parking area is not fully occupied? Who Benefits? - Citizens / Parking Operators / City Council / Shops
  32. 32. Copyright © RIOT 2015 All Rights Reserved Home Health Transport OfficeWaste DATA BLENDING Creating New Compound Applications
  33. 33. Copyright © RIOT 2015 All Rights Reserved All personal items, such as mobile phones, wrist watches, spectacles, laptops, soft drinks, food items and household items, such as televisions, cameras, microwaves, washing machines, etc Private business organization has the right to take the decision whether to publish the sensors attached to those items to the cloud or not. Public infrastructure such as bridges, roads, parks, etc. All the sensors deployed by the government will be published in the cloud depending on government policies. Business entities who deploy and manage sensors by themselves by keeping ownership. They earn by publishing the sensors and sensor data they own through sensor publishers. Personal and Households Commercial Sensor Data Providers Organizations PublicPrivate [Source: “Sensing as a Service Model for Smart Cities Supported by Internet of Things”, Charith Perera et. al., Transactions on Emerging Telecommunications Technology, 2014] CHALLENGES – DATA OWNERSHIP
  34. 34. Copyright © RIOT 2015 All Rights Reserved ENCOURAGE ADOPTION AND INNOVATION OF IOT
 HOW-TO
  35. 35. Copyright © RIOT 2015 All Rights Reserved “Makers, startups and crowdsourcing efforts result in high numbers of low-revenue niche IoT applications.”
  36. 36. Copyright © RIOT 2015 All Rights Reserved WHERE ARE THE IOT DEVELOPERS? [Source: http://arc.applause.com/2015/07/27/internet-of-things-big-data-and-analytics/]
  37. 37. Copyright © RIOT 2015 All Rights Reserved SENSING-AS-A-SERVICE WHAT-IF
  38. 38. Copyright © RIOT 2015 All Rights Reserved The city would pay for access to the light sensors in order to decide when to turn on and off the street lights Gathering temperature, light, pressure, humidity and pollution. COMMERCIAL IOT SENSOR PROVIDER A university may want access to the pollution information for research purposes for a limited period The weather department would want the temperature and pressure data The street town council center would want the temperature and humidity data for planning during rough weather
  39. 39. Copyright © RIOT 2015 All Rights Reserved HARNESSING THE CREATIVITY
  40. 40. Copyright © RIOT 2015 All Rights Reserved PARTICIPATORY SENSING – “RAPID DEPLOYMENT”
  41. 41. Copyright © RIOT 2015 All Rights Reserved REDUCTION OF DATA ACQUISITION COST – “SUSTAINABLE BUSINESS MODEL”
  42. 42. Copyright © RIOT 2015 All Rights Reserved DIFFERENT BUSINESS MODELS
  43. 43. Copyright © RIOT 2015 All Rights Reserved COLLECT DATA PREVIOUSLY UNAVAILABLE – “ASSIST SCIENTIFIC OR SURVEY ACTIVITIES”
  44. 44. Copyright © RIOT 2015 All Rights Reserved CROWDSENSING GETTING INSIGHTS FROM EMPOWER THE CITIZENS TO SENSE
  45. 45. Copyright © RIOT 2015 All Rights Reserved SMARTPHONE AS YOUR “SENSING ASSISTANT” Sensors: ①  Camera – “Eyes” ②  Audio – “Ears” ③  Accelerometer – “Speed” ④  GPS – “Location” ⑤  Gyroscope – “Movement” ⑥  Compass – “Direction” ⑦  Proximity – “Closeness” ⑧  Ambient light – “Eyes” ⑨  Others… Crowdsourcing Via Crowdsensing Context ①  Spatial – Location / Speed Orientation ②  Temporal – Time / Duration ③  Environmental – Temperature / Light / Noise Level ④  User Characterization – Activity (Mobility Pattern) / Social (Friends, Interactions)
  46. 46. Copyright © RIOT 2015 All Rights Reserved MAKING CITIES BETTER USING CITIZENS Traffic NoiseEnvironment Network Coverage (WiFi/3G/4G)
  47. 47. Copyright © RIOT 2015 All Rights Reserved LET ALL CITIZENS BE OUR “EYES”
  48. 48. Copyright © RIOT 2015 All Rights Reserved Incident reporting facilities - citizens can report on issues concerning public infrastructure allowing collective collaboration to ensure an active response COLLECTIVE COLLABORATION WITH CITIZENS
  49. 49. Copyright © RIOT 2015 All Rights Reserved MOBILE APPLICATION LIVABILITY LOCAL AREA SERVICES PUBLIC SAFETY NATURAL DISASTER Open Data Smartphone Users Social Media Users PORTAL CITISENSE.COM CASE MANAGEMENT SYSTEM DASHBOARD EMPOWERING SMART CITIZENS
  50. 50. Copyright © RIOT 2015 All Rights Reserved
  51. 51. Copyright © RIOT 2015 All Rights Reserved WHICH CAME FIRST – THE CHICKEN OR THE EGG?
  52. 52. Copyright © RIOT 2015 All Rights Reserved SMART CITIZENS AND SENSORS CONNECTING AND AGGREGATING
  53. 53. Copyright © RIOT 2015 All Rights Reserved Smart City Environmental Monitoring Multiple Sensors Outdoor Parking Management Parking sensors Mobile Environmental Monitoring Sensors installed in public vehicles Traffic Intensity Monitoring Devices located at main entrance of city Guidance to free parking lots Panels located at intersections Smart Citizen Crowdsensing Parks and Gardens Irrigation Sensors in green zones •  Temperature •  CO •  Noise •  Car Presence •  Ferromagnetic sensors •  Temperature •  CO •  Noise •  Car Presence •  Measure main traffic parameters •  Traffic volumes •  Road occupancy •  Vehicle speed •  Queue Length •  Taking information retrieved by the deployed parking sensors in order to guide drivers towards the available free parking lots •  Moisture temperature •  Humidity •  Pluviometer (rain gauge) •  Anemometer (wind-speed) •  User generated feedback with smartphones that help to make cities better
  54. 54. Copyright © RIOT 2015 All Rights Reserved [Source: http://inrix.com]
  55. 55. Copyright © RIOT 2015 All Rights Reserved IOT AND BIG DATA MARRIAGE CHALLENGES IOT DEMAND A NEW WAY THINKING
  56. 56. Copyright © RIOT 2015 All Rights Reserved CHALLENGE #1 FLOOD MONITORING
  57. 57. Copyright © RIOT 2015 All Rights Reserved PREDICTING FLOOD 1.  What is the water level in the river? 2.  When does the river swell up? 3.  Where is the location of water rise? 4.  Where are the areas that require immediate evacuation? 5.  Who is contributing to the rise in water level? 6.  How to control the water level? 7.  How fast is the water rising? 8.  Why is the water rising?
  58. 58. Copyright © RIOT 2015 All Rights Reserved FLOOD – DIFFERENT SENSORS 1.  Water level and weather sensors 2.  Tide monitoring sensor 3.  Astronomical data 4.  GPS for rescue vehicles (Plug-n-Play OBD) 5.  GIS data 6.  Camera 7.  Social network integration
  59. 59. Copyright © RIOT 2015 All Rights Reserved FLOOD MONITORING – VALUE PROPOSITION 1.  Early warning system for floods 2.  Locating the area of violation (cause of floods) 3.  Efficient rescue planning 4.  Plan the widening of the river banks 5.  Plan deepening of the river bed 6.  Predict the conditions of flooding when coupled with a weather station, astronomical, tide and GIS.
  60. 60. Copyright © RIOT 2015 All Rights Reserved CHALLENGE #2 RIVER MONITORING
  61. 61. Copyright © RIOT 2015 All Rights Reserved MONITORING RIVER POLLUTION 1.  What are the pollutants in the river? 2.  What is the pollution level? 3.  When is the highest pollution detected? 4.  Where is the location of pollutants? 5.  Who is contributing to the rise in pollution? 6.  How to control the pollution level? 7.  How much is the pollution level? 8.  Why is the pollution rising at certain time? 9.  Why is the pollution rising at certain locations?
  62. 62. Copyright © RIOT 2015 All Rights Reserved RIVER MONITORING - SENSORS 1.  Chemical sensors 2.  Water level sensors 3.  Crowd sourced violation information (mobile device) 4.  GPS input 5.  Hydro morphology e.g. depth, width, flow 6.  Water temperature sensor 7.  In-situ (manual sampling) 8.  Weather sensors
  63. 63. Copyright © RIOT 2015 All Rights Reserved RIVER MONITORING – VALUE PROPOSITION 1.  Early warning system for water contamination 2.  Locating the area of violation 3.  Detecting and alerting violations 4.  Getting public involvement through crowd sourcing 5.  Evidence platform for violations 6.  Identify potential causes of pollution rise by correlating data with water level pattern 7.  Identify a profile of water in different months of the year. Any change in profile will trigger external sources of pollution 8.  Identify the spread of disease 9.  Ecotourism planning
  64. 64. Copyright © RIOT 2015 All Rights Reserved Tons of interesting data If you can’t take action on the data being collected, it’s likely not worth collecting, storing and analyzing. Is it actionable for my business?
  65. 65. Copyright © RIOT 2015 All Rights Reserved The Internet of Things and Big Data are two sides of the same coin, and building one without considering the other is a recipe for doom.
  66. 66. Copyright © RIOT 2015 All Rights Reserved THANK YOU @REDtoneIOTREDtoneIOT

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