Role: Strategic Technical Consultant
Course: MCA Semester I (UPES Online)
Status: Completed (December 2025)
This repository contains the technical solutions for the SmartCity Data Innovation Lab case study. The goal was to optimize public services (Traffic, Emergency Response, Utilities) using algorithmic solutions and data structures.
| Module | Task | Technology Stack | Key Concepts |
|---|---|---|---|
| Q1 | Traffic Data Analysis | Python (Pandas) | ETL, Data Cleaning, Vectorization |
| Q2 | Citizen Feedback DB | SQL (SQLite) | Schema Design, Primary Keys |
| Q3 | Emergency Routing | Python | Dijkstra’s Algorithm (Graph Theory) |
| Q4 | Utility Billing System | C++ | OOP, Inheritance, Polymorphism |
| Q5 | Emergency Call Priority | C++, Python, C | Max-Heap (Priority Queue) |
cd src/Q1_Traffic_Analysis
python traffic_analysis.py
cd src/Q3_Emergency_Routing python dijkstra_route.py
g++ src/Q5_Call_Priority/priority_queue.cpp -o priority_queue ./priority_queue
The complete consulting report with theoretical justifications and output screenshots is available in the reports/ directory.