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https://github.com/acamarata/fajr-watch.git
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b62a361c9a
Complete project structure for an automated Fajr/Isha observation appliance: Hardware: - BOM for 3 build tiers ($270, $465, $1000) - 20-unit bulk order spec (~$9,900 for fleet) - Solar power, weatherproof enclosure, GPS timing Software: - Detection engine: multi-channel color analysis + temporal derivative tracking on horizon ROI, no fixed brightness threshold - Capture scheduler: computes twilight windows from coordinates, captures every 10s during window, runs detection, uploads results - Solar position via PyEphem for depression angle at each frame - Upload sync: hourly cron to central server + CSV export for offline Provisioning: - first-boot.sh: one-shot setup script installs all deps, configures systemd service, sets up WiFi from station.yaml on boot partition - Flash SD card, edit station.yaml, plug in, forget Docs: - Volunteer host guide: 10-minute installation, plug-and-play - Hardware BOM with sourcing links
97 lines
2.8 KiB
YAML
97 lines
2.8 KiB
YAML
# fajr-watch station configuration
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# Copy this file to station.yaml and fill in your values.
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# On the Pi SD card, place station.yaml in /boot/fajr-watch/station.yaml
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station:
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# Unique station identifier (lowercase, hyphens ok)
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id: "my-station-01"
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# GPS coordinates (decimal degrees)
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# South latitudes and west longitudes are negative
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lat: 41.95
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lng: -80.55
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# Elevation above sea level in metres
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elevation_m: 175
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# Horizon type at camera location
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# Options: ocean, lake, flat, hills, mountain
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horizon: "lake"
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# Light pollution environment
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# Options: dark (Bortle 1-2), rural (3-4), suburban (5-6), urban (7-9)
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environment: "suburban"
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# Your name (for data attribution)
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host: "Your Name"
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# Contact email (not published, used for station health alerts)
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contact: "you@example.com"
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camera:
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# Camera model connected to the Pi
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# Options: zwo_asi224, zwo_asi462, zwo_asi662, pi_hq, pi_cam3, pi_cam3_wide
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type: "zwo_asi224"
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# Lens focal length in mm (for FOV calculation)
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lens_mm: 1.8
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# Which horizon the camera points at
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# Options: east (Fajr only), west (Isha only), allsky (both)
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orientation: "allsky"
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# Azimuth offset in degrees (0 = camera north is true north)
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# Measured clockwise. If your camera's "up" points 30 degrees east of north,
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# set this to 30.
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azimuth_offset: 0
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network:
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# WiFi credentials (WPA2)
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wifi_ssid: ""
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wifi_password: ""
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# Optional: additional WiFi networks (tried in order)
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# wifi_networks:
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# - ssid: "BackupNetwork"
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# password: "password2"
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# Data upload endpoint
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upload_url: "https://api.fajr.watch/v1/upload"
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# Upload API key (provided when you register your station)
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api_key: ""
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capture:
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# Seconds between frames during twilight window
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interval_s: 10
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# How many degrees before/after the expected twilight to start/stop capturing
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# Larger margin = more data but more storage. 5 degrees is ~20-30 min extra.
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twilight_margin_deg: 5
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# Capture RAW images (recommended for scientific quality)
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# Set to false for JPEG-only (smaller files, less accurate)
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raw_format: true
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# Maximum exposure time in seconds
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# ZWO cameras support up to 1000s. Pi cameras typically max at 30-60s.
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max_exposure_s: 30
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# Target mean brightness for auto-exposure (0-255 for 8-bit)
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# Lower = darker frames that preserve faint gradients
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target_brightness: 80
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processing:
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# Run detection on-device (true) or upload raw frames for server processing (false)
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detect_on_device: true
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# Minimum confidence score to accept a detection (0.0 - 1.0)
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min_confidence: 0.5
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# Keep raw frames after processing
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# true = keep all frames (uses more storage, useful for debugging)
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# false = keep only the 10 frames around each detection event
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keep_raw_frames: false
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# Maximum days of local data to retain before cleanup
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retention_days: 30
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