Plan a walking or biking route through Berlin that minimizes exposure to known surveillance cameras.
Compare a shortest route against a camera avoiding route side by side on a map.
Run the routing pipeline locally against a small test area or the full city of Berlin.
Deploy a self hosted instance of the planner with Docker for a specific city's camera data.
| leonardoalt/kamerafrei | 0xmukesh/docusaurus-tutorial | 1tsmejp/palworld-docker-wine | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | JavaScript | JavaScript | JavaScript |
| Last pushed | — | 2021-12-27 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | general | developer | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Full Berlin data download needs a few GB of RAM and takes a while, a small test area runs in about 2 minutes.
Kamerafrei is a walk and bike route planner for Berlin that tries to steer you away from known surveillance cameras. Its name is German for camera free. It works using OpenStreetMap data that marks the locations of known surveillance cameras, the same data used by a related visualization project called Surveillance under Surveillance. The README is upfront that this only avoids cameras that are already mapped, not every camera in the city. Behind the scenes, an offline pipeline downloads Berlin's street and path network and marks every stretch of it with how many meters fall within 25 meters of a known camera. A routing algorithm then finds a path by balancing distance against camera exposure, controlled by a slider in the web interface that ranges from off to maximum avoidance. Users click a start and end point on a map, choose whether they are walking or biking, and see two routes side by side: the normal shortest path and the low camera path, with any remaining camera covered sections highlighted in red. A stats panel compares distance, time, number of cameras passed, and exposed distance between the two routes. The project is built with a Python data pipeline that fetches camera locations and builds the street network, a FastAPI backend that serves routing and camera data through a small API, and a JavaScript frontend using Leaflet for the interactive map. It can be run locally with a Makefile based setup, either on a small test area or for the whole of Berlin, and can also be deployed with Docker. Map data comes from OpenStreetMap contributors under the ODbL license, and the project credits the Surveillance under Surveillance project as its inspiration.
A Berlin walk and bike route planner that lets you avoid streets covered by known surveillance cameras, using OpenStreetMap data.
Mainly JavaScript. The stack also includes Python, FastAPI, JavaScript.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
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