GeoHealth: Efficient Hospital Search and Management System

Objective

The GeoHealth project is a comprehensive hospital management system designed to efficiently manage and search hospital data using advanced data structures like R-Tree, Trie, Heap, and Stack. It supports features such as location-based hospital searches, prefix-based search queries, priority-based hospital ratings, and search history tracking, providing a user-friendly and efficient solution for emergency and non-emergency scenarios.

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Features

1. Hospital Management:

   • Add, delete, and retrieve hospital information.
   • Prioritize high-rated hospitals for emergencies.

2. Location-Based Searches:

   • Utilize R-Tree for efficient spatial indexing of hospital locations.
   • Perform range and nearest neighbor queries.

3. Name-Based Searches:

   • Use Trie for prefix-based search, enabling autocomplete and efficient retrieval of hospital names and addresses.

4. Hospital Ratings:

   • Maintain hospital ratings with a MaxHeap to quickly access the highest-rated hospital.

5. Search History:

   • Track user searches using a Stack to provide quick access to recent searches.

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Data Structures and Their Applications

1. R-Tree:

   • Efficiently indexes spatial data for location-based hospital searches.
   • Operations:
     • Insertion: O(log n)
     • Deletion: O(log n)
     • Search: O(log n + k) (nearest neighbors)

2. MaxHeap:

   • Maintains and prioritizes hospitals based on ratings.
   • Operations:
     • Insertion: O(log n)
     • Maximum Retrieval: O(1)

3. Trie:

   • Facilitates fast prefix-based lookups for hospital names and addresses.
   • Operations:
     • Insertion/Search/Deletion: O(m) (where m is the length of the key)

4. Stack:

   • Tracks user search history for quick reference.
   • Operations:
     • Push/Pop/Peek: O(1)
     • View History: O(n)

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R-Tree Structure Example

Root (Internal Node) [Bounding Box: (40.7242, -74.0049) - (40.758896, -73.9176)]
|-- Internal Node 1 [Bounding Box: (40.7242, -74.0049) - (40.7373, -73.9352)]
|   |-- Leaf Node 1
|   |   |-- City Hospital (40.73061, -73.935242)
|   |   |-- St. Peter's Hospital (40.7306, -73.9352)
|   |-- Leaf Node 2
|       |-- Metro (40.730610, -73.935242)
|       |-- Sunshine Medical Clinic (40.730610, -73.935242)
|-- Internal Node 2 [Bounding Box: (40.7357, -74.0031) - (40.758896, -73.9744)]
|   |-- Leaf Node 3
|   |   |-- Northside Hospital (40.7357, -73.9918)
|   |   |-- Westside Hospital (40.7373, -74.0031)

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Challenges

1. Sensor Accuracy: Handling inconsistencies in geographical data with optimized algorithms.
2. Efficient Retrieval: Balancing memory usage and speed for large datasets.
3. User Experience: Designing intuitive and fast systems for real-world applications.

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Future Enhancements

• Add support for real-time updates and notifications.
• Integrate GPS for outdoor navigation.
• Implement machine learning algorithms for predictive analytics and smarter decision-making.

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How to Run

1. Clone the repository:

   git clone https://github.com/YourUsername/GeoHealth.git

2. Navigate to the project folder:

   cd GeoHealth

3. Compile and run the code:

   g++ main.cpp -o geohealth
   ./geohealth

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