In July 2026, when the number of connected IoT devices worldwide exceeded 18 billion (according to IoT Analytics), integrating microcontrollers with AI agents became particularly relevant. The Raspberry Pi Pico is an inexpensive microcontroller based on the RP2040, used for collecting data from temperature, humidity, and motion sensors, as well as controlling actuators. The problem is that without an AI agent, these devices operate in isolation: you get raw data but cannot analyze it in real time or automatically respond to events. Integration with ASI Biont solves this problem — the AI agent itself writes code for data exchange via UART/COM port, analyzes sensor readings, and sends commands back to the Pico. In this article, we will explore how to set up such a connection in 10 minutes without programming, what automation scenarios this unlocks, and why it is more advantageous than traditional approaches.
Why Connect Raspberry Pi Pico to an AI Agent?
The Raspberry Pi Pico is a microcontroller that can read data from analog and digital sensors, control relays, LEDs, and stepper motors. However, its built-in memory (264 KB SRAM) and processor (133 MHz) do not allow running complex machine learning algorithms or analyzing time series. Typically, developers write code in MicroPython or C++ that sends data to a server and then manually configure processing logic. This requires time and skills.
Connecting the Pico to the ASI Biont AI agent via UART changes the approach. The AI agent takes over analysis: it can detect anomalies (e.g., a temperature spike above 40°C), predict trends (rising humidity before rain), and make decisions (turn on ventilation). Moreover, the user does not need to write code — just provide the service API key in the chat with the AI, and the agent will generate the integration for the UART protocol, which is supported on the Pico via built-in UART0 (GP0/GP1) or UART1 (GP4/GP5).
How Does ASI Biont Connect to Raspberry Pi Pico?
ASI Biont is an AI agent that can connect to any service via API. For the Raspberry Pi Pico, it uses the UART/COM port: the AI agent generates MicroPython code that is uploaded to the Pico and configures the serial interface. All interaction occurs through chat — you specify which sensor is connected (e.g., DHT22 for temperature and humidity or PIR sensor for motion), and the AI creates the sketch itself.
The connection process looks like this:
1. You register at asibiont.com and obtain an API key.
2. In the chat with the AI agent, you write: "Connect Raspberry Pi Pico with DHT22 sensor via UART."
3. The AI requests the API key (if not provided earlier) and generates MicroPython code that configures UART0 at 115200 baud, reads data from the sensor, and sends it to the ASI Biont server.
4. You upload this code to the Pico via USB (using Thonny or another IDE), and data exchange begins.
No control panels or "add integration" buttons — everything is done through dialogue. The only thing required from the user is to physically connect the sensor to the Pico (e.g., DHT22 to GP2) and provide the API key. The AI writes the integration itself, taking into account the specifics of the UART protocol: stop bits, parity, buffering.
What Automation Tasks Does This Integration Enable?
Integrating the Pico with ASI Biont unlocks three key automation scenarios:
1. Environmental Monitoring with Predictive Analytics
Temperature and humidity sensors (DHT22, BME280) send data every 5 seconds. The AI agent analyzes trends: if humidity rises above 70% within an hour, it can warn about mold risk or turn on a dehumidifier. In production workshops, this prevents material spoilage.
2. Perimeter Security with Intelligent False Alarm Filtering
PIR motion sensors often give false signals due to animals or branches. The AI agent on ASI Biont can distinguish human movement (by pattern: speed, duration) from random interference using simple ML models loaded on the server. This reduces false alarms by 80% (according to smart home tests).
3. Scheduled and Event-Based Actuator Control
Relays connected to the Pico can turn on lights, ventilation, or pumps. The AI agent receives a command from the user (e.g., "turn on the light if motion is detected after 18:00") and generates code that checks conditions on the Pico and closes contacts. Everything works in real time: the delay from event to command is less than 200 ms.
Practical Example: Greenhouse Automation
Consider a real case. You have a greenhouse with a Raspberry Pi Pico, a DHT22 temperature/humidity sensor, and a relay for irrigation control. The task: maintain temperature 22–28°C and humidity 60–80%, automatically turning on irrigation when humidity drops below 55%.
Step 1: Hardware Preparation
- Raspberry Pi Pico (cost ~$4)
- DHT22 sensor (connected to GP2, power 3.3V)
- Relay module (connected to GP3, controls the pump)
- USB cable for connection to computer
Step 2: Integration via ASI Biont
You open the chat with the AI agent at asibiont.com and write: "Configure Pico with DHT22 on GP2 and relay on GP3. Send temperature and humidity data every 10 seconds. If humidity < 55%, turn on the relay for 30 seconds." The AI generates MicroPython code that:
- Initializes UART0 at 115200 baud
- Reads DHT22 and sends a JSON string: {"temp": 24.5, "hum": 62.3}
- Receives commands from the server: {"relay": "on"} or {"relay": "off"}
Step 3: Upload and Test
The code is uploaded to the Pico via Thonny. After reboot, the Pico starts sending data. The AI agent on the server checks conditions and sends commands. If humidity drops to 54%, the relay turns on for 30 seconds, then turns off. Everything works without human intervention.
Results:
- Setup time: 15 minutes (instead of 2–3 hours with manual coding)
- Savings on cloud servers: data is processed on the ASI Biont server, no need to buy a separate VPS
- Flexibility: to change logic (e.g., turn on irrigation when temperature >35°C), just write in the chat — the AI updates the code on the Pico remotely
Why Is This Beneficial?
Time savings. According to an IoT developer survey (2025, Hackster.io), 68% of time is spent writing and debugging code for data exchange between microcontroller and server. ASI Biont automatically generates this code, including error handling (e.g., retransmission on UART failure).
Lower entry barrier. To connect the Pico, you don't need to know TCP/IP, MQTT, or HTTP protocols — all communication goes via UART, which is supported at the hardware level. The AI agent selects the correct settings (baud rate, data bits) based on documentation.
Scalability. You can connect not just one but a dozen Picos — each will send data to the same API key. The AI agent distributes load and aggregates data, for example, building a heat map from multiple sensors.
Security. All data is transmitted over an encrypted connection (TLS 1.3), and the API key is stored only with the user. The AI agent does not request access to your local network — only to the open UART port.
How to Get Started?
- Connect the sensor to the Raspberry Pi Pico according to the schematic (e.g., DHT22 to GP2, VCC to 3.3V, GND to GND).
- Go to asibiont.com and create an API key in your personal account.
- In the chat, write: "Connect Pico with temperature sensor on UART." Provide the API key.
- Copy the generated code and upload it to the Pico via USB.
- Check the data — it will appear in the ASI Biont dashboard within 10 seconds.
Conclusion
Integrating the Raspberry Pi Pico with the ASI Biont AI agent via UART is a practical way to automate monitoring and control in a smart home or production environment without complex programming. You get ready-made code, predictive analytics, and remote control, spending 10 minutes on setup. Industrial protocols like UART remain the standard for microcontrollers, and the AI agent makes them accessible to any user.
Try the integration right now at asibiont.com — connect your first sensor and see how AI manages devices in real time.
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