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Internet of Things (IoT) Intro
Anna Gerber
Anna
Maker of Things
Efficiency
IoT Applications
Manufacturing
Energy
Wearables
Healthcare (Ingestibles!)
Retail
Smart Buildings
Automotive
Connected Cities
Agriculture
Entertainment
Devices
The things
Device Hardware
Microcontrollers
● System on a Chip (SoC)-based
● Data processing & storage
● GPIO pins
● Popular development boards:
○ Arduino
○ Espressif ESP8266 & ESP32
○ Particle
○ TI LaunchPad series
Development Kits
Single-Board Computers
● Higher processing, RAM & data storage
capabilities
● Peripheral support (via USB, Bluetooth)
● Popular boards:
○ Raspberry Pi
○ Orange Pi
○ BeagleBone Black & Green
○ Qualcomm DragonBoard
Inputs / Sensors
● Temperature / Humidity
● Pressure / Force
● Smoke & Gas
● Current
● Magnetic
● Light
● Sound / Vibration
● Air & Water-flow
● Buttons / Touch
● Acceleration
● Proximity / Position etc...
● Linear actuator
● Solenoid
● Motor
● Relay
● LED
○ Matrix
○ Strip
○ Ring
○ OLED screen
● LCD screen
● Piezo / speaker
Outputs / Actuators
Network
Connecting the things
7 Application
6 Presentation
5 Session
4 Transport
3 Network
2 Data Link
1 Physical
Application
Transport
Internet
Network Access &
Physical
OSI Model TCP/IP Model
HTTPS, CoAP, MQTT,
AMQP, XMPP
UDP, TCP
IPv6, 6LoWPAN, RPL
IoT Protocols
IEEE 802.15.4
Wifi (802.11 a/b/g/n)
Ethernet (802.3)
Cellular
IoT Network Stack
The nice thing about
standards is that you have
so many to choose from
— Andrew S. Tanenbaum
IoT Protocols
Network Access & Physical Layer:
● IEEE 802.15.4 Low-Rate Wireless Personal Area
Networks (LR-WPAN) e.g. ZigBee
● Wifi (802.11 a/b/g/n)
● Ethernet (802.3)
● LP-WAN (Low Power Wide Area Network) e.g. LoRa,
SigFox
● Low Energy Bluetooth (BLE)
● Cellular: GSM, CDMA, 4G, LTE-M, NB-IoT
● RFID (Radio Frequency Identification)
● NFC (Near Field Communication)
Internet Layer:
● IPv6 (Internet Protocol version 6)
● 6LoWPAN (IPv6 Low-power wireless Personal Area
Network)
● RPL (IPv6 Routing Protocol for Low-power and lossy
networks)
Transport Layer:
● UDP (User Datagram Protocol)
● TCP (Transmission Control Protocol)
Application Layer:
● HTTP/HTTPS (Hypertext Transfer Protocol/Secure)
● CoAP (Constrained Application Protocol)
● MQTT (Message Queue Telemetry Transport)
● AMQP (Advanced Message Queuing Protocol) e.g.
RabbitMQ
● XMPP (Extensible Messaging and Presence Protocol)
… and many more
Network Topologies
Star
Tree
Bus
Mesh
Ring
Fully connected mesh
Key Challenges of IoT
Security
Securing the network, the
things and their data
Security challenges
Securing devices
Authorizing and authenticating devices
Managing device updates
Securing communication
Ensuring data security
Securing applications (web, mobile, cloud)
Detecting vulnerabilities
Detecting incidents
Managing vulnerabilities
Predicting incidents
Read more:
https://developer.ibm.com/dwblog/2017/iot-security-challenges/
IoT Security
Strategies:
● Securing devices, network architectures and upstream
applications & services (mobile / cloud)
● Authentication & Access control
● Port protection
● Encryption (message confidentiality)
● Digital signatures (message integrity)
● Event monitoring
● Activity logging
● Replay protection
● Threat assessment
● Ethical hacking / penetration
testing
Usability &
User
Experience
How people use the things and
their data
Designing for IoT
Transition from screen-based UIs (mobile / web apps) to (multiple) “invisible” interfaces
● Voice (Alexa, Google Home, Siri)
● Gestures
● Ambient interactions
● Augmented Reality
Context Awareness
Device hardware limitations
Imperfect connectivity
Accessibility
IoT at Scale
Managing complexity
Edge Architecture
20
Edge
Devices
(with Sensors & Actuators)
Gateways
Wifi, BLE, NFC, RFID, ZigBee
Cloud
Storage
Services
Rules Engine
MQTT
AMQP
CoAP
HTTP/S
Mobile Apps
Web Apps
Enterprise
Apps
HTTP/S
Web sockets
IoT Platforms
IoT Platform Capabilities
● Rapid application development
● Device management
● Data communication
● Data storage
● Authentication and Authorization services
● Rules and analytics
● Automation & Orchestration
Example Platforms
IBM Watson IoT (Bluemix)
Kaa - Open Source, model-driven
Amazon Web Services (AWS) IoT
Microsoft Azure IoT
Google Cloud IoT
Interoperability
Handling heterogeneity
Full-stack interoperability
● Hardware protocols for connecting sensors & actuators e.g. CAN, SPI, I2C
● Over the air updates for device firmware and maintaining interoperability with devices that can’t be updated
● APIs for registering / managing / decommissioning devices
● Network protocols
● Data formats
● Metadata formats
● APIs for querying / filtering / managing / integrating / analyzing data
● Deploying & orchestrating apps & services
● Platform interoperability: avoid silos & lock-in
Data Analytics
& Business
Intelligence
Making sense of and acting on
data from the things
The world’s data doubles
every two years
Data Analytics & Business Intelligence
Edge Computing
Filtering, normalization & pre-processing
Real-time / stream analytics
Data Storage & Management:
NoSQL (Cassandra, DynamoDB, CouchDB, MongoDB, HBase)
Time Series DB (InfluxDB, Riak, Prometheus, Graphite)
Data transformation & integration, tracking provenance, ensuring reliability
Distributed processing frameworks:
Hadoop
Spark
Data visualization
Machine Learning / AI:
Data mining
Pattern recognition
Predictive analytics
Actionable Insights
Learn more
Attend the Brisbane IoT Meetup
DeveloperWorks IoT learning paths
https://www.ibm.com/developerworks/learn/iot/index.html
@AnnaGerber

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IoT Intro: Applications, Devices, Networks and Challenges

  • 1. Internet of Things (IoT) Intro Anna Gerber
  • 4. IoT Applications Manufacturing Energy Wearables Healthcare (Ingestibles!) Retail Smart Buildings Automotive Connected Cities Agriculture Entertainment
  • 6. Device Hardware Microcontrollers ● System on a Chip (SoC)-based ● Data processing & storage ● GPIO pins ● Popular development boards: ○ Arduino ○ Espressif ESP8266 & ESP32 ○ Particle ○ TI LaunchPad series Development Kits Single-Board Computers ● Higher processing, RAM & data storage capabilities ● Peripheral support (via USB, Bluetooth) ● Popular boards: ○ Raspberry Pi ○ Orange Pi ○ BeagleBone Black & Green ○ Qualcomm DragonBoard
  • 7. Inputs / Sensors ● Temperature / Humidity ● Pressure / Force ● Smoke & Gas ● Current ● Magnetic ● Light ● Sound / Vibration ● Air & Water-flow ● Buttons / Touch ● Acceleration ● Proximity / Position etc... ● Linear actuator ● Solenoid ● Motor ● Relay ● LED ○ Matrix ○ Strip ○ Ring ○ OLED screen ● LCD screen ● Piezo / speaker Outputs / Actuators
  • 9. 7 Application 6 Presentation 5 Session 4 Transport 3 Network 2 Data Link 1 Physical Application Transport Internet Network Access & Physical OSI Model TCP/IP Model HTTPS, CoAP, MQTT, AMQP, XMPP UDP, TCP IPv6, 6LoWPAN, RPL IoT Protocols IEEE 802.15.4 Wifi (802.11 a/b/g/n) Ethernet (802.3) Cellular IoT Network Stack
  • 10. The nice thing about standards is that you have so many to choose from — Andrew S. Tanenbaum
  • 11. IoT Protocols Network Access & Physical Layer: ● IEEE 802.15.4 Low-Rate Wireless Personal Area Networks (LR-WPAN) e.g. ZigBee ● Wifi (802.11 a/b/g/n) ● Ethernet (802.3) ● LP-WAN (Low Power Wide Area Network) e.g. LoRa, SigFox ● Low Energy Bluetooth (BLE) ● Cellular: GSM, CDMA, 4G, LTE-M, NB-IoT ● RFID (Radio Frequency Identification) ● NFC (Near Field Communication) Internet Layer: ● IPv6 (Internet Protocol version 6) ● 6LoWPAN (IPv6 Low-power wireless Personal Area Network) ● RPL (IPv6 Routing Protocol for Low-power and lossy networks) Transport Layer: ● UDP (User Datagram Protocol) ● TCP (Transmission Control Protocol) Application Layer: ● HTTP/HTTPS (Hypertext Transfer Protocol/Secure) ● CoAP (Constrained Application Protocol) ● MQTT (Message Queue Telemetry Transport) ● AMQP (Advanced Message Queuing Protocol) e.g. RabbitMQ ● XMPP (Extensible Messaging and Presence Protocol) … and many more
  • 14. Security Securing the network, the things and their data
  • 15. Security challenges Securing devices Authorizing and authenticating devices Managing device updates Securing communication Ensuring data security Securing applications (web, mobile, cloud) Detecting vulnerabilities Detecting incidents Managing vulnerabilities Predicting incidents Read more: https://developer.ibm.com/dwblog/2017/iot-security-challenges/
  • 16. IoT Security Strategies: ● Securing devices, network architectures and upstream applications & services (mobile / cloud) ● Authentication & Access control ● Port protection ● Encryption (message confidentiality) ● Digital signatures (message integrity) ● Event monitoring ● Activity logging ● Replay protection ● Threat assessment ● Ethical hacking / penetration testing
  • 17. Usability & User Experience How people use the things and their data
  • 18. Designing for IoT Transition from screen-based UIs (mobile / web apps) to (multiple) “invisible” interfaces ● Voice (Alexa, Google Home, Siri) ● Gestures ● Ambient interactions ● Augmented Reality Context Awareness Device hardware limitations Imperfect connectivity Accessibility
  • 19. IoT at Scale Managing complexity
  • 20. Edge Architecture 20 Edge Devices (with Sensors & Actuators) Gateways Wifi, BLE, NFC, RFID, ZigBee Cloud Storage Services Rules Engine MQTT AMQP CoAP HTTP/S Mobile Apps Web Apps Enterprise Apps HTTP/S Web sockets
  • 21. IoT Platforms IoT Platform Capabilities ● Rapid application development ● Device management ● Data communication ● Data storage ● Authentication and Authorization services ● Rules and analytics ● Automation & Orchestration Example Platforms IBM Watson IoT (Bluemix) Kaa - Open Source, model-driven Amazon Web Services (AWS) IoT Microsoft Azure IoT Google Cloud IoT
  • 23. Full-stack interoperability ● Hardware protocols for connecting sensors & actuators e.g. CAN, SPI, I2C ● Over the air updates for device firmware and maintaining interoperability with devices that can’t be updated ● APIs for registering / managing / decommissioning devices ● Network protocols ● Data formats ● Metadata formats ● APIs for querying / filtering / managing / integrating / analyzing data ● Deploying & orchestrating apps & services ● Platform interoperability: avoid silos & lock-in
  • 24. Data Analytics & Business Intelligence Making sense of and acting on data from the things
  • 25. The world’s data doubles every two years
  • 26. Data Analytics & Business Intelligence Edge Computing Filtering, normalization & pre-processing Real-time / stream analytics Data Storage & Management: NoSQL (Cassandra, DynamoDB, CouchDB, MongoDB, HBase) Time Series DB (InfluxDB, Riak, Prometheus, Graphite) Data transformation & integration, tracking provenance, ensuring reliability Distributed processing frameworks: Hadoop Spark Data visualization Machine Learning / AI: Data mining Pattern recognition Predictive analytics Actionable Insights
  • 27. Learn more Attend the Brisbane IoT Meetup DeveloperWorks IoT learning paths https://www.ibm.com/developerworks/learn/iot/index.html