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Python Developer: Build Real-Time Geofence Alert Script via WebSockets (AISStream / Telegram)

Budget: $250.0 FIXED / ⭐ 0.00 (0) United States

python, automation, python-script, api-integration, websockets, json, telegram-api, linux

I am looking for an experienced Python developer to build a lightweight, automated tracking script that acts as a digital tripwire for specific mobile assets entering defined geographic zones. The script will monitor a live maritime telemetry feed, apply specific size and type filters, and send instant structured alerts to a private Telegram channel. To protect our operational privacy, the exact coordinates and token keys will be kept in an environment file, which we will configure during deployment. Technical Requirements Data Sourcing (WebSockets/API): Connect to a live, continuous AIS data stream (such as the free AISStream.io WebSocket API or similar budget-friendly providers). Geofencing Engine: Monitor two specific geographic bounding boxes (GPS coordinate pairs provided upon hire). Data Parsing & Filtering: Parse the incoming JSON payloads in real-time. The script must only trigger an alert if the asset meets two strict criteria: Asset Type: Matches specific classification codes (e.g., AIS Code 37 / Pleasure Craft). Asset Scale: Dimension attribute (length) is greater than or equal to 24 meters. De-duplication / State Management: Implement an in-memory cache or lightweight state tracking system. When an asset enters a bounding box, it should only fire one initial alert rather than spamming notifications on every data packet update while inside the zone. Notification Layer: Format the output into a clean, scannable Markdown-styled message and push it to a Telegram Bot API. The message needs to display the asset's Name, Length (converted from meters to feet), Speed, and Destination string. Deliverables A clean, well-commented, production-ready Python script. A .env file structure for all API tokens, bot credentials, and bounding box coordinates to keep them entirely separate from the codebase. 30 minutes of deployment assistance/hand-off to help us launch the script on a basic Linux cloud server (DigitalOcean Droplet or AWS Lightsail instance).
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