Ingredient
Raspberry Pi
Also known as: RPi, Raspberry Pi 5, Raspberry Pi 4
ARM-based single-board computer — full Linux on a credit-card-sized board. Runs Debian-derived Raspberry Pi OS, Ubuntu, or any ARM64 Linux distribution; capable of hosting web services, running ROS2 nodes, processing camera feeds, training small ML models, and acting as the always-on brain of a farm-automation system. The right ingredient when you need a real OS, network services, a filesystem, or compute that exceeds what an MCU can deliver. Models: Pi 5 (4-core ARM Cortex-A76, up to 16 GB RAM, ~$80), Pi 4 (4-core A72, up to 8 GB, ~$45), Pi Zero 2 W ($15, low-power applications), Compute Module (industrial-form-factor, for embedded production).
Inputs / outputs
- GPIO: 40-pin header — 28 GPIO, 3.3V logic; multiple I²C, SPI, UART; PWM via software or DMA.
- USB: 4× USB-A (Pi 4/5: 2× USB 3.0, 2× USB 2.0).
- Network: Gigabit Ethernet + WiFi 5/6, BLE.
- Display/camera: HDMI, dedicated CSI camera ribbon connector, DSI display connector.
- Storage: microSD primary; Pi 5 supports NVMe SSDs via a HAT.
- Power: 5V/3A USB-C (Pi 5 wants 5V/5A under load); ~5–10 W typical.
Solves / unlocks
- Always-on farm-automation hub (web dashboard, scheduler, MQTT broker)
- Computer vision at the edge (camera + OpenCV/YOLO nano)
- ROS2 control node for small robots and stationary actuator-arrays
- Local LLM inference (Pi 5 + 8 GB can run small quantized models like Phi-3 mini)
- [[home-assistant|Home Assistant]] or OpenHAB self-hosted automation server
- [[node-red|Node-RED]] visual flow orchestration
Constraints
- No real-time guarantees — Linux scheduling is not deterministic; pair with an MCU for tight timing loops.
- Microsd reliability — frequent writes destroy SD cards; use SSD or read-only root for production.
- GPIO weakness — single GPIO can sink/source ~16 mA; never drive motors or solenoids directly.
Source
- Hardware: https://www.raspberrypi.com/products/
- OS: https://www.raspberrypi.com/software/ (Debian-based, free)
- pinout reference: https://pinout.xyz/
- Linux kernel: mainline ARM64
See also
Auto-generated from this entry’s typed relations: frontmatter, grouped by relation type so the editorial signal isn’t flattened.
- Parallels: [[nvidia-jetson]] · [[beaglebone-black]]
- Member of: [[ingredient]]
- Combines with: [[ros2]] · [[opencv]] · [[node-red]] · [[home-assistant]] · [[mqtt]] · [[rgbd-camera]]
What links here, and how
Inbound connections from across the wiki, grouped by lens and by relationship. These appear automatically — every entity page declares what it links to, and that data populates here on the targets.
Practical
parallels
- BeagleBone Black BBB competes for industrial-control roles where its real-time PRUs matter; RPi wins on cost and ecosystem
- NVIDIA Jetson Jetson is the GPU-accelerated step up from RPi when ML/CV is the bottleneck
contains
- Farm-tech toolkit compute / Linux SBC; the always-on farm hub
combines with
- FarmBot Genesis FarmBot OS runs on a Pi inside the FarmBot's electronics box
- Home Assistant Home Assistant OS images directly to a Pi SD card; the standard self-hosted automation stack
- iNaturalist API Pi 5 + camera + iNaturalist CV API = field species ID without needing local model
- LiDAR rangefinder RPLiDAR A1 + RPi 4 = entry-level autonomous-rover perception stack
- Modbus / RS-485 USB-RS485 adapters or HAT; Python pymodbus is mature
- MQTT Mosquitto MQTT broker runs trivially on Pi as a service
- Node-RED Node-RED runs as a service on the Pi; visual orchestration of farm IoT
- OpenCV Pi 5 with Camera Module 3 = real-time OpenCV pipelines for crop monitoring
- PlantVillage dataset Pi 5 with quantized model (TFLite) = lightweight in-field disease screening
- RGB-D camera RPi 5 can stream RealSense, but heavy processing should move to Jetson
- ROS 2 ROS2 runs on Pi 4/5 with Ubuntu ARM64; standard low-cost ROS2 control node
- Servo motor needs hardware PWM HAT for jitter-free control (PCA9685 is standard)
- YOLO (object detection) Pi 5 with YOLOv8-nano + TFLite delegate: real-time at ~10 FPS for low-frame-rate work
combines
- Recipe: orchard disease-prediction station the always-on hub
- Recipe: closed-loop greenhouse climate controller the always-on hub running Home Assistant
- Recipe: off-grid soil-moisture mesh the always-on farm hub running Mosquitto, Home Assistant, and (for LoRaWAN) the network server
19 inbound links · 9 outbound