AIOT System Architecture

An AIOT system has several key components working together. Let’s break them down:

Core Components

1. Sensors: Collect data from the environment
2. Microcontroller/Processor: Runs the device and AI
3. AI Model: Processes data and makes decisions
4. Connectivity: Communicates with other devices or cloud
5. Actuators: Takes actions based on decisions

Component Breakdown

1. Sensors

Sensors are the eyes and ears of AIOT devices. They collect data from the physical world.

Types of sensors:

• Temperature: Measures heat
• Motion: Detects movement
• Camera: Captures images and video
• Microphone: Records sound
• Light: Measures brightness
• Pressure: Detects force

Example: A smart thermostat uses temperature sensors to know how hot or cold a room is.

2. Microcontroller/Processor

This is the brain of the device. It runs the AI and controls everything.

What it does:

• Processes sensor data
• Runs AI models
• Makes decisions
• Controls actuators
• Manages connectivity

Types:

• Microcontrollers: Small, low-power (for simple devices)
• Edge processors: More powerful (for complex AI)
• GPUs: Specialized for AI processing

Example: A smart camera uses an edge processor to run face recognition AI.

3. AI Model

The AI model is the intelligence. It learns patterns and makes decisions.

What it does:

• Analyzes sensor data
• Recognizes patterns
• Makes predictions
• Decides what actions to take

Types:

• Pre-trained models: Already learned, just use them
• Custom models: Trained for specific tasks
• Lightweight models: Small enough to run on devices

Example: A fitness tracker uses a pre-trained model to recognize different types of exercises.

4. Connectivity

Connectivity lets the device communicate with other systems.

Types:

• WiFi: Fast, needs power
• Bluetooth: Short range, low power
• Cellular: Works anywhere, uses data
• LoRaWAN: Long range, low power
• Ethernet: Wired connection

What it’s used for:

• Sending alerts
• Receiving updates
• Syncing with cloud
• Communicating with other devices

Example: A smart door lock uses WiFi to send you notifications when someone enters.

5. Actuators

Actuators are the hands of the device. They perform actions.

Types:

• Motors: Move things
• Lights: Illuminate
• Speakers: Make sound
• Valves: Control flow
• Displays: Show information

Example: A smart irrigation system uses valves to turn water on and off.

How Components Work Together

Let’s see how these components interact in a smart security system:

Interactive Diagram

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Steps:

1. Motion sensor detects movement
2. Camera captures video
3. Processor runs AI face recognition
4. AI identifies person as unknown
5. Device sends alert via WiFi
6. Alarm activates

Hands-On: Identify Components

Match each component to its role in an AIOT system:

Example: Smart Home System

Let’s see how components work together in a smart home:

Components

1. Sensors: Motion sensors, door sensors, temperature sensors
2. Processor: Central hub running on edge device
3. AI Model: Learns your daily patterns
4. Connectivity: WiFi connects all devices
5. Actuators: Smart lights, thermostat, door locks

How It Works

Morning routine:

1. Motion sensor detects you waking up
2. AI recognizes this is your usual wake time
3. Processor sends commands to actuators
4. Lights turn on gradually
5. Thermostat adjusts to your preferred morning temperature
6. Coffee maker starts (if connected)

All without you doing anything—the AI learned your routine.

Edge vs Cloud Architecture

AIOT systems can process data in different places:

Edge-Only Architecture

Where: Everything runs on the device

Components:

• Sensors on device
• Processor on device
• AI model on device
• Actuators on device
• Optional: Basic connectivity for alerts

Best for: Privacy-sensitive, fast-response needs

Example: Security camera that processes video locally

Cloud-Enhanced Architecture

Where: Device does basic processing, cloud does complex analysis

Components:

• Sensors on device
• Lightweight AI on device (quick decisions)
• Connectivity to cloud
• Powerful AI in cloud (deep analysis)
• Actuators on device

Best for: Complex analysis, learning from many devices

Example: Fitness tracker that does basic step counting locally, but analyzes long-term health trends in the cloud

Hybrid Architecture

Where: Uses both edge and cloud intelligently

How it works:

• Edge handles immediate decisions
• Cloud handles complex learning
• Device gets smarter over time

Example: Smart speaker that processes voice commands locally, but uses cloud for complex questions

Key Takeaways

Remember these architecture points:

1. Five core components: Sensors, processor, AI, connectivity, actuators
2. Sensors collect: Data from the physical world
3. Processor runs: The device and AI
4. AI decides: What actions to take
5. Connectivity enables: Communication with other systems
6. Actuators perform: Physical actions
7. Edge or cloud: Can process in either place, or both

What’s Next?

In the next page, we’ll explore real-world applications of AIOT. You’ll see how these systems are used in homes, cities, factories, and more.