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R.A.D.A.R. 🛰️

Real-time Analytic Detection of Available Restrooms

R.A.D.A.R. is an intelligent indoor navigation and facility management system designed to eliminate the "availability hunt" in high-density corporate environments. Developed during HackSU 2026.


🚀 Overview

In massive office complexes, finding an open restroom is often a game of chance. R.A.D.A.R. treats the office floor plan as a living network. By modeling hallways and facilities as nodes in a graph, the system calculates the most efficient path based on real-time occupancy rather than just physical proximity.

✨ Key Features

  • Smart Navigation: Uses Dijkstra’s Algorithm to calculate the shortest path to a guaranteed vacant restroom.
  • 3D Spatial Mapping: Models complex office layouts using a node-and-edge system in 3D space to account for different floors.
  • Clean Monitor: A dedicated dashboard for facility management that tracks stall usage frequency to optimize cleaning rotations.
  • Cloud-Native: Fully integrated with Azure MySQL for synchronized, low-latency data access across devices.

🛠️ Tech Stack

  • Language: Python 3.x
  • Database: MySQL (Hosted on Azure Cloud)
  • Frontend: HTML5 & CSS3
  • Core Logic: Graph Data Structures & Dijkstra’s Shortest Path

🏗️ Architecture & Logic

The building is abstracted into a mathematical graph $G = (V, E)$:

  • Nodes ($V$): Represent restrooms, hallway intersections, and office entry points.
  • Edges ($E$): Represent the physical paths between them, weighted by physical distance ($w$).
  • Dynamic Weighting: When a user inputs their location, the system queries the Azure database to identify the optimal destination based on both distance and current occupancy status.

🏁 Getting Started

Prerequisites

  • Python 3.x
  • mysql-connector-python
  • Access to an Azure SQL instance (or a local MySQL equivalent)

Installation

  1. Clone the repository:
    git clone [https://github.com/jack980180/2026_Hackathon_RADAR.git](https://github.com/jack980180/2026_Hackathon_RADAR.git)
    cd 2026_Hackathon_RADAR
  2. Install dependencies:
    pip install mysql-connector-python
  3. Database Setup: Import the provided SQL dump file into your MySQL instance to initialize the node and occupancy tables.

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