Building Smart Systems with IoT: From Sensor to Dashboard
A practical guide to IoT system architecture — from selecting sensors and microcontrollers to MQTT brokers, edge processing, time-series databases, and real-time dashboards.
Building Smart Systems with IoT: From Sensor to Dashboard
IoT systems are fundamentally different from web applications. The data flows from the physical world through hardware, communication protocols, processing layers, and finally to software. Each layer has its own failure modes, latency characteristics, and design constraints.
Here is how I think about and build end-to-end IoT systems.
The IoT Stack
A complete IoT system has five layers:
- Physical layer — sensors and actuators in the real world
- Device layer — microcontrollers and single-board computers that read sensors and run edge logic
- Communication layer — protocols that move data between devices and the backend (MQTT, HTTP, CoAP, Zigbee, Z-Wave, BLE)
- Processing layer — edge processing on the device, server-side processing, stream processing
- Application layer — databases, APIs, dashboards, alerting
Getting the split right between these layers — deciding what happens on the device vs in the cloud — is the most important IoT architecture decision.
Choosing Hardware
- Wi-Fi and Bluetooth built in
- Dual-core 240MHz processor
- 520KB SRAM
- Deep sleep power mode (critical for battery-powered nodes)
- Rich peripheral support (I2C, SPI, UART, ADC, PWM)
- Low cost (under $5)
Raspberry Pi for gateway devices and more complex edge processing. When you need to run Python, connect to multiple sensor nodes, or perform local AI inference, a Pi gives you a full Linux environment.
Arduino for very simple, low-power sensor nodes. When you need reliability and long battery life with minimal computation, Arduino's simplicity is an advantage.
Sensor Selection
Choose sensors based on your measurement requirements: