Course: CL2001 — Data Structures & Algorithms | Year: 2026
Institution: FAST-NUCES Islamabad
A modular C++ console-based simulation system demonstrating how multiple data structures work together in a real-world forest monitoring and decision environment.
This project models a smart forest management system where environmental data flows through multiple layers — each layer powered by a different data structure. Rather than isolated implementations, the focus is on integration and interaction between structures to simulate realistic forest scenarios.
arrays.cpp --> Environmental Data Layer
linkedlist.cpp --> Event Memory Layer
queue.cpp --> Task Scheduling Layer
tree.cpp --> Decision-Making Layer
graph.cpp --> Routing & Spread Layer
hashTable.cpp --> Fast Access Layer
monitoring.cpp --> Performance Tracking Layer
scenerio.cpp --> Scenario Simulation Layer
main.cpp --> Central Integration & Menu
- Static baseline environmental data storage
- Dynamic sensor data management
- 1D time-series tracking
- 2D forest grid representation
- Threshold-based anomaly detection
- Spatial interpolation for missing sensor values
- Singly linked list for forward event streams
- Doubly linked list for event correction and backward traversal
- Circular linked list for continuous monitoring loops
- Event history traversal (forward & backward)
- Data reconstruction and correction support
- FIFO queue for routine monitoring tasks
- Priority queue for emergency handling
- Multi-queue system: monitoring, surveillance, emergency
- Task scheduling and execution flow
- Load balancing between queue types
- Multiple specialized trees:
DecisionTree,ZoneHierarchyTree,SubZoneTree,TerrainTree,WaterTree,FireControlTree,EquipmentTree,FireClassTree,WildlifeTree,HumanActivityTree,RegionalTree,GlobalTree - Zone-based hierarchical decision-making
- Resource allocation logic
- Fire risk evaluation using weighted scoring
- Local, regional, and global decision handling
- Both adjacency matrix (
Graph) and list (GraphList) representations - BFS for fire spread simulation
- DFS for deep connectivity analysis
- Path cost calculation (distance + danger weighting)
- Dynamic path updates based on fire conditions
- Key-value storage for zone environmental data
- Fast O(1) average-case retrieval
- Collision handling (chaining)
- Cache system for frequently accessed zone data
- Execution time tracking per module
- System load analysis
- Bottleneck detection
- Performance optimization insights
Five integrated test scenarios:
- Cascading Fire Spread — graph BFS simulates fire moving across zones
- Sensor Failure & Data Reconstruction — linked list handles missing/corrupt data
- Multi-Factor Anomaly Detection — array thresholds + hash lookups combined
- System Overload Handling — priority queue reroutes tasks under high load
- Global Emergency Synchronization — all modules coordinate via main controller
- Menu-driven console interface via
main.cpp - Real-time simulation of environmental sensor data
- Fire detection and alerting using threshold logic
- Multi-structure interaction across all modules
- Scenario-based integration testing
- Modular, maintainable, single-responsibility file design
- Proper comments with time complexity annotations
g++ main.cpp array.cpp linkedlist.cpp queue.cpp graph.cpp hashTable.cpp tree.cpp monitoring.cpp scenerio.cpp -o ifamds
./ifamdsRequires a C++17-compatible compiler (g++ or clang++).
| Name | Role |
|---|---|
| Romaisa | Co-developer |
| Maham Anjum | Co-developer |
MIT License © 2026
Most DSA coursework treats each structure in isolation. IFAMDS instead asks: what happens when all of them run together? Every module feeds into the next — sensor arrays trigger linked list events, which enqueue tasks, which drive tree decisions, which route through graphs, all tracked by a hash cache and performance monitor. The result is a system that's greater than the sum of its parts.