# Deploy BirdNET-Go with Easypanel

URL: /templates/birdnetgo

BirdNET-Go is a real-time bird sound identification and monitoring system that uses advanced AI and machine learning to recognize bird species from audio recordings. It analyzes ambient sounds from microphones or audio files to identify and catalog bird species in your area. BirdNET-Go features automatic species detection with confidence scoring, location-based range filtering to show only birds likely in your region, real-time audio streaming, and comprehensive logging of all detected species. The application supports custom sensitivity settings, overlap detection for better accuracy, and can utilize XNNPACK acceleration for improved performance. Perfect for bird enthusiasts, ornithologists, researchers, and anyone interested in monitoring local bird populations and creating automated bird sound databases.

## Benefits

### Automated Bird Identification

AI-powered real-time identification of bird species from audio using advanced BirdNET machine learning models with high accuracy.

### Location-Aware Filtering

Configure your GPS coordinates to filter detections showing only bird species likely to be in your region, reducing false positives.

### Continuous Monitoring

24/7 automated monitoring and logging of bird species in your area. Build comprehensive databases of local bird populations over time.

## Features

### Real-Time Audio Analysis

Process live audio streams from microphones or audio files to identify bird sounds in real-time with configurable sensitivity.

### Species Confidence Scoring

Each detection includes confidence scores and threshold filtering to ensure accurate species identification.

### Geographic Range Filtering

Location-based filtering shows only birds expected in your area based on latitude/longitude coordinates.

### Audio Streaming

HLS streaming support for live audio playback and monitoring of detected bird sounds through web interface.

### Detection Logging

Comprehensive logging and database of all detected species with timestamps, confidence scores, and audio clips.

### Customizable Settings

Adjust sensitivity, detection thresholds, audio overlap, and model parameters to optimize for your environment.

## Configuration

- `appServiceName` (App Service Name, required): birdnetgo

- `appServiceImage` (App Service Image, required): ghcr.io/tphakala/birdnet-go:nightly-20260429

- `timezone` (Timezone): UTC

- `latitude` (Latitude (Optional - for location filtering)): Set during installation

- `longitude` (Longitude (Optional - for location filtering)): Set during installation

- `locale` (Locale (e.g., en-us)): en-us

## Services

- birdnetgo: app (ghcr.io/tphakala/birdnet-go:nightly-20260429)

## Resources

- [Github](https://github.com/tphakala/birdnet-go)

- [Docker Hub](https://github.com/tphakala/birdnet-go/pkgs/container/birdnet-go)

- [Template source](https://github.com/easypanel-io/templates/tree/main/templates/birdnetgo)