BirdsOS

BirdsOS is a Flask-based application for controlling and monitoring bird feeder hardware, with support for camera feeds and GPIO control. It includes development-friendly mock implementations for testing without physical hardware.

Features

Camera System

• Live video streaming with configurable resolution
• Recording capabilities with frame buffering
• Camera settings management
• Mock implementation for development with test pattern generation

GPIO Control

• Hardware abstraction layer with Raspberry Pi detection
• Pin state monitoring and control
• Mock implementation for development and testing
• Interactive GPIO simulator interface

Web Interface

• Main dashboard for system monitoring
• Camera simulator with live feed display
• GPIO simulator for hardware interaction
• RESTful API endpoints for system control

Setup

1. Clone the repository:

git clone <repository-url>
cd birdbox

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

python app.py

The application will be available at:

• Main Dashboard: http://localhost:5000
• Camera Simulator: http://localhost:5000/camera
• GPIO Simulator: http://localhost:5000/gpio

API Endpoints

Camera Control

• GET /video_feed - Stream live video feed
• POST /api/camera/record/start - Start recording
• POST /api/camera/record/stop - Stop recording
• POST /api/camera/settings - Update camera settings
• GET /api/camera/recordings - List recorded videos

GPIO Control

• GET /api/gpio/status - Get current pin states
• POST /api/gpio/trigger - Trigger input pin state change

System Status

• GET /status - Get system operational status

Development

The system includes mock implementations for both camera and GPIO functionality, allowing development and testing without physical hardware. When running on a Raspberry Pi, it automatically switches to using real hardware interfaces.

Mock Implementations

• Camera mock generates test patterns with timestamps
• GPIO mock simulates pin state management
• Both provide realistic behavior for testing

Current Status

Implemented

• Core application structure
• Camera streaming and recording framework
• GPIO state management
• Web interface and simulators
• Hardware abstraction layer

In Progress

• Motor control system
• Recording storage implementation
• Full status monitoring
• Enhanced simulator features

Contributing

Contributions are welcome! Please feel free to submit pull requests or open issues for bugs and feature requests.

License

[License information to be added]

BirdBox - Training Wild Birds to Clean the Environment

The BirdBox project is an innovative approach to environmental cleanup that trains wild birds to collect litter in exchange for food. This project combines environmental conservation with animal intelligence, creating a sustainable way to help clean our environment while engaging with local wildlife.

Overview

The BirdBox is a device designed to train wild crows to pick up litter and deposit it into a designated container in exchange for food rewards. This project leverages the natural intelligence and adaptability of corvids (crows and ravens) to create a mutually beneficial relationship between humans and birds while addressing environmental pollution.

How It Works

The system works on a simple principle: when a bird deposits litter into the collection area, it triggers sensors that activate a food dispenser, rewarding the bird with a treat. Over time, birds learn to associate cleaning up litter with receiving food rewards, creating a sustainable cycle of environmental cleanup.

Project Goals

• Create a sustainable solution for environmental cleanup
• Engage wild birds in a meaningful way that benefits both wildlife and humans
• Raise awareness about environmental issues and animal intelligence
• Demonstrate how technology can be used to create innovative solutions for environmental challenges

Community Impact

This project not only helps clean the environment but also:

• Creates awareness about environmental pollution
• Demonstrates the intelligence of wild birds
• Provides a unique way for communities to engage with local wildlife
• Offers an educational opportunity to learn about animal behavior and environmental conservation

Contributing

This is an open-source project, and we welcome contributions from the community. Whether you're interested in hardware improvements, software development, or documentation, your input is valuable to the project's success.

License

This project is licensed under the Creative Commons - Attribution - Non-Commercial license.

Spezifikation: Motordurchmesser: 6 mm Motorlänge: 12 mm Kabellänge: 65 mm Gewicht: 2 g Spannungsbereich: 3,0 V -3,7 V Testdaten: Spannung: 3,0 V Strom: 160 mA Spannung: 3,7 V Strom: 220 mA

Camera Case

The Camera Case was used from https://www.thingiverse.com/thing:2317664 and modified, to make it attachable to the backboard.

Installation

Automated Setup (Raspberry Pi)

The project includes an automated setup script designed for Raspberry Pi (optimized for Pi 3B). The script handles all necessary installation steps, including:

• System dependencies
• Python environment
• Hardware configuration
• Service setup
• Storage management

Prerequisites

• Raspberry Pi (3B recommended) with Raspberry Pi OS
• Internet connection
• GitHub account (for SSH key setup)
• At least 32GB SD card (Class 10 recommended)

Installation Steps

1. Download the Setup Script

   curl -O https://raw.githubusercontent.com/DeniseBryson/birdbox/AIgen2/setup.sh
   chmod +x setup.sh

   or upload via scp:

   scp "setup.sh" birds@<ip-address>:/home/birds/

2. Run the Setup Script

   ./setup.sh

   The script will:

   • Check if running on a Raspberry Pi
   • Set up SSH keys if needed
   • Install all dependencies
   • Configure camera and GPIO interfaces
   • Set up the Python environment
   • Create necessary directories
   • Configure storage based on available space
   • Run tests to verify the installation
   • Set up the system service

3. Post-Installation

   • The service will start automatically
   • Access the web interface at http://localhost:5000
   • Check the service status with sudo systemctl status birdbox

Configuration

The script creates a .env file with default settings optimized for Raspberry Pi 3B:

• Camera: 640x480 @ 20fps
• Storage: 75% of available SD card space
• GPIO: BCM mode
• Logging: Daily rotation, 14 days retention

Troubleshooting

• If tests fail during installation, you can choose to:
  1. Exit and fix the issues
  2. Continue with the installation (not recommended)
• Check logs in ~/birdbox/storage/logs/
• Monitor system temperature with vcgencmd measure_temp
• Monitor resources with htop

Manual Installation

For non-Raspberry Pi systems or manual installation, please refer to the Manual Installation Guide.