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