This is a full-stack web application designed to parse, analyze, and visualize Google Location History data. Users can upload their LocationHistory.json file to see an interactive heatmap of their movements and get statistical insights into their travel patterns. The application also features a complete admin dashboard for aggregate data analysis.

• Secure User Authentication: Standard user registration and login system with session management.
• File Upload: Simple interface for users to upload their Google Takeout LocationHistory.json file.
• Interactive Heatmap: Displays all location data points on an interactive map using Leaflet.js, showing geographic concentrations of activity.
• Data Filtering: Users can filter the displayed data by date range (year, month, day) and time of day.
• Activity Analysis: The application calculates and displays statistics on different types of activities (e.g., walking, in vehicle, running).

• Aggregate Data Visualization: The admin dashboard provides charts and graphs (using Chart.js) that show trends across all user data.
• Statistical Breakdowns: View data distributions by year, month, day of the week, and hour of the day.
• User Data Metrics: See statistics on the number of records per user.
• Data Export: Admins can export filtered aggregate data to CSV, JSON, or XML formats.

• Backend: PHP
• Database: MySQL
• Frontend: HTML, CSS, JavaScript, jQuery, AJAX
• Mapping Library: Leaflet.js
• Charting Library: Chart.js

1. Data Upload & Parsing: The user uploads their JSON file, which is processed by a PHP script on the backend. The script parses the nested JSON structure, extracts key data points (latitude, longitude, timestamp, activity type), and stores them in the MySQL database.
2. API Endpoints: The PHP backend serves as an API, with endpoints that respond to AJAX requests from the frontend. These endpoints query the database based on user-selected filters.
3. Frontend Visualization: The frontend JavaScript receives the data from the API and dynamically updates the Leaflet.js heatmap and the Chart.js graphs, providing a seamless and interactive user experience.

For more explanation and screenshots see: Presentation (greek) Database creation at: /database export. Fake/test data can be generated with generate_random_location_dates.py