IoT

Overview

  • features
    • everything is connected
    • tying together the physical, digital and analytic worlds
  • connectivity and the “any” dimension
    • IoT allows people & things to be connected anytime at anyplace with anything and anyone using any network and any service

Evolution

Characteristics

  • dynamic changes
  • heterogeneity
  • things-related services
  • inter-connectivity
  • enormous scale

Architecture

  • sensor and identification layer
    • information generation
    • lowest abstraction layer
    • with sensors we are creating digital nervous system
    • incorporated to measure physical quantities
    • interconnects the physical and digital world
    • collects and process the real time information
    • examples
      • barcode & QR code
      • RFID
      • smartphone sensor
  • network construction layer
    • information transmission
    • robust and high performance network infrastructure
    • supports the communication requirements for latency, bandwidth or security
    • allows multiple organizations to share and use the same network independently
    • examples
      • telecommunication systems (e.g., GSM, UMTS, LTE)
      • WLAN
      • short range (e.g., bluetooth)
      • NB-IoT (Narrowband Internet of Things) & LoRa (Long Range Radio)
      • satellite systems
      • broadcast systems
      • fixed wireless access
      • SNs (Sensor Networks)
        • consist of a certain number of sensing nodes communicating in a wireless multi-hop fashion
        • SNs generally exist without IoT but IoT cannot exist without SNs
        • applications
          • environmental monitoring
          • agriculture
          • medical care
          • event detection
      • 5G
        • dramatically increase
          • speed of data transfer
          • response time
          • capacity for billions of devices to be connected
  • management layer
    • information processing
    • capturing of periodic sensory data
    • data analytics
    • streaming analytics (process real time data)
    • ensures security and privacy of data
  • integrated application layer
    • information application
    • provides a user interface for using IoT
    • different applications for various sectors like transportation, healthcare, agriculture, supply chains, government, retail, etc.

Challenges

  • lack of standardization
  • addressing issues
  • new network traffic patterns to handle
  • device level energy issues
  • security concerns
  • privacy issues

Summary

  • with billions of devices connected, vast amount of data can be generated
  • data sharing/exchange among the devices will generate new data as well
  • data analytics is necessary to analyze the data to acquire insights and trends

Big Data

Overview

  • sources
    • users
    • applications
    • systems
    • sensors
  • structure
    • unstructured
      • data that has no inherent structure and is usually stored as different types of files
      • e.g., PDFs, images
    • quasi-structured
      • textual data with erratic formats that can be formatted with effort and software tools
      • e.g., clickstream data
    • semi-structured
      • textual data files with an apparent pattern, enabling analysis
      • e.g., spreadsheets and XML files
    • structured
      • data having a defined data model, format, structure
      • e.g., database
  • tradition data vs big data
    • traditional data
      • large scale
      • highly centralized
      • structured
        • files
        • records
        • databases
      • sequential
      • indexed
      • processing transactions
    • big data
      • massive scale
      • highly distributed
      • unstructured
        • emails
        • audio/video
        • blogs, etc.
      • random
      • looking for patterns and relationships

Characteristics

  • volume
    • the vast amounts of data generated every second
  • velocity
    • the speed at which new data is generated and the speed at which data moves around
  • veracity
    • the messiness or trustworthiness of the data
  • variety
    • the different types of data can now be used
  • value
    • having access to big data is no good unless we can turn it into value

Types

  • activity data
  • conversation data
  • photo & video image data
  • sensors data from IoT devices
  • real time data
  • spatial data
  • spatiotemporal data
    • is an extension of spatial database
    • captures spatial and temporal aspects of data and deals with geometry changing over time and location of objects moving over invariant geometry

Big data and location

  • all IoT sensors have loactions
    • the most common IoT sensors in smartphones - GPS receiver
    • all posts, photos and messages are tagged with phone or IP locations in social media
  • geospatial big data analytics
    • requires new science of spatial statistics
    • GIS as a tool for spatial statistical analysis
      • aggregate data
      • join data
      • summarize data
      • calculate data
      • find hot spots

Issues

  • data privacy
  • data security
  • data discrimination
  • data accuracy
  • data existence

AI

Overview

  • relationship
    • IoT is the “senses” (connect devices and collect data)
    • big data is the “fuel” (capture, storage, analysis of data)
    • AI is the “brain” (data-based learning, analytics, automation)
  • AI & ML & DL
    • AI
      • board definition
      • building machines that learn & think like people
    • ML
      • ability to learn & improve its performance without human interaction
    • DL
      • solve any problem which requires “thought”
      • feed a lot of data
      • learn from its mistakes

Development

  • basic (weak AI)
    • specialize in a certain scope
  • advanced (strong AI)
    • think & operate like a human being
  • super advanced (Artificial Superintelligence)
    • smarter than the best human brains

The rules for success

  • computing power
  • data
  • algorithms and architecture

8 ways AI will transform our cities smarter by 2030

  • transportation
  • education
  • healthcare
  • public safety
  • home & service robots
  • employment & workplace
  • entertainment
  • low-resource communities

Additional Reading