Open Dronelog

Abstract

1. Introduction

A high-performance application for analyzing drone flight logs (DJI and Litchi CSV formats). Available as a Tauri v2 desktop app or a Docker-deployable web app. Built with DuckDB and React.

2. Objective

Drone Log analyzer: A high-performance universal dashboard application for organizing and analyzing DJI/Litchi flight logs privately in one place. Supports plugin for custom flight log formats. Built with Tauri v2, DuckDB, and React.

This project demonstrates how TypeScript can be applied to a real-world Data Science problem.

3. Key Features / Modules

• High-Performance Analytics: DuckDB-powered queries with automatic downsampling for large datasets. Free, open source, no subscription required.
• Smart Deduplication: Prevents duplicate imports based on drone serial, battery serial, and start time.
• Interactive Flight Maps: 3D terrain, map-type selection (Satellite, Topographic, OpenStreetMap), flight replay with speed control (0.5x-16x), live telemetry overlay, and RC joystick visualization.
• Local-First Storage: All data in a local DuckDB database. No cloud upload required (except DJI key fetch during first import).
• Smart Tags: Auto-tagging (Night Flight, High Speed, Low Battery, etc.) and offline reverse geocoding for location tags. Manual tags and bulk operations supported.on.
• Filters & Search: Date range (calendar + typed YYYY-MM-DD start/end quick entry), drone/battery/controller/color filters, duration/altitude/distance sliders, tag filter, map area filter, and filter inversion.
• Overview Dashboard: Aggregate stats, activity heatmap, pie charts by drone/battery/duration, time-of-day radial chart, cluster map with optional heatmap layer, and top-flight highlights.
• Maintenance Tracking: Configurable thresholds with color-coded progress bars and date-based maintenance recording.
• Exports: CSV, JSON, GPX, KML, and Summary CSV export. FlyCard generator for shareable 1080x1080 social media images.
• Manual Flight Entry: Record flights without log files with optional coordinates and metadata.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm / yarn / pnpm
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/arpanghosh8453/open-dronelog.git
cd open-dronelog

1. Zero setup – just open the link in your browser
2. Perfect for evaluation – see if the tool fits your needs before installing
3. Single flight visualization – upload and analyze one flight log at a time
4. All core features – view telemetry charts, 3D flight path replay, and flight statistics
5. No data persistence – your data is processed locally in the browser and not stored on any server
6. Import a Flight Log: Click "Browse Files" or drag-and-drop a drone log file
7. Select a Flight: Click on a flight in the sidebar
8. Analyze Data: View telemetry charts and the 3D flight path on the map

docker pull ghcr.io/arpanghosh8453/open-dronelog:latest

docker run -d \
  -p 8080:80 \
  -v drone-data:/data/drone-logbook \
  --name open-dronelog \
  ghcr.io/arpanghosh8453/open-dronelog:latest

git clone https://github.com/arpanghosh8453/open-dronelog
cd open-dronelog
docker compose up -d

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by arpanghosh8453 and published on GitHub under the GNU Affero General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.