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Featured Assignments
Smart Traffic Management System Using IoT and Real-Time Data Analysis
IoT & Data AnalyticsClient Requirements
The student wanted to build a smart traffic management system that could detect congestion and optimize signal timings based on live data. The aim was to simulate real-world traffic intersections using IoT sensors and data analytics, with a functional dashboard showing traffic patterns and predictions.
Challenges Faced
We ensured proper use of simulated sensor data streams, but faced complications while handling real-time data synchronization and algorithmic adjustment of traffic light cycles. Designing the logic for adaptive signal control based on density heatmaps needed multiple refinements for realism and performance.
Our Solution
We implemented simulated IoT nodes feeding live vehicle density data into a backend via MQTT protocol. Python and Flask were used to build the analytics engine, and a web dashboard (built with React and Chart.js) displayed live intersection statuses, congestion hotspots, and signal timing adjustments.
Results Achieved
The final product successfully mimicked a smart intersection that could adjust signal timing dynamically. The dashboard offered insightful analytics and visualizations, marking a high-level interdisciplinary FYP.
Client Review
Assignment FYP.401 was a game-changer. I honestly didn’t expect the traffic simulation to look this real. The dashboard, data flow, and decision-making logic were all handled with amazing precision. Everything was properly visualized, and my experience working with them was absolutely smooth and productive.
AI-Based Career Recommendation System Using Machine Learning
Machine Learning & Career TechClient Requirements
The student wanted to develop an AI-powered career recommendation system based on user academic data, interests, and skill assessments. They were hoping to implement classification techniques in machine learning to suggest personalized career paths for students, with insights and confidence scores.
Challenges Faced
We ensured the data preprocessing was robust, but handling imbalanced training data and noisy inputs posed issues during model training. Selecting the right ML model and fine-tuning hyperparameters to get accurate predictions needed multiple rounds of evaluation.
Our Solution
We collected a dataset of user profiles and labeled career outcomes, applied preprocessing and feature engineering, and trained multiple models (Random Forest, SVM, and KNN). After evaluation, the best-performing model was deployed via a Flask API connected to a responsive web form with suggestions, graphs, and confidence metrics.
Results Achieved
A functional, user-friendly system that took profile inputs and provided ranked career recommendations along with confidence scores and rationale behind each result. The system was demo-ready for real academic settings.
Client Review
The career recommender system they delivered was smarter than I’d hoped for. It gave accurate suggestions, and the logic behind each choice was well explained. The design, API work, and predictive engine were properly done — working with them on FYP.402 was a highly satisfying experience!
Blockchain-Based Academic Certificate Verification Platform
Blockchain in EducationClient Requirements
The student wanted to explore blockchain in education by building a certificate verification system where institutions could issue certificates stored securely on-chain. Employers or universities could verify authenticity via a unique hash or QR.
Challenges Faced
We ensured smart contract logic was sound, but faced challenges in choosing the right blockchain (public vs. private) and handling gas fees, wallet integration, and UI trust indicators. Interfacing frontend with blockchain events needed additional security validations.
Our Solution
We built a Solidity smart contract for issuing and validating certificates and deployed it on the Polygon testnet to minimize costs. The React-based frontend integrated Metamask for issuer verification and displayed transaction hashes and verification statuses on a clean dashboard.
Results Achieved
A decentralized certificate management system that allowed issuance, verification, and tracking of academic credentials with tamper-proof security — ideal for tech-forward universities.
Client Review
Assignment FYP.403 turned out to be cutting-edge. I loved how the verification worked via blockchain — no room for fake credentials. The UI was clean, Metamask worked flawlessly, and everything was properly deployed. My experience with them was absolutely brilliant.
AI-Powered Medical Symptoms Checker Web App
AI in HealthcareClient Requirements
The student wanted to develop a healthcare assistant web app where users could input symptoms and receive potential diagnoses, severity levels, and recommendations. The student emphasized using NLP and machine learning, with ethical data handling and medical reliability.
Challenges Faced
We ensured the symptom checker maintained medical accuracy, but integrating text-based NLP classification using a relatively small dataset posed some challenges. Ensuring no harmful misclassification and providing disclaimers added extra care to logic design.
Our Solution
We used a curated dataset of symptoms and diagnoses, trained a Multinomial Naive Bayes model using TF-IDF features, and deployed it behind a Python/Flask API. The frontend included dropdown symptom selection and free-text input with autocomplete. We added disclaimers and confidence-based suggestions with colored indicators.
Results Achieved
The system provided users with likely medical outcomes and appropriate advice using AI — without replacing medical professionals. It passed all usability checks and featured a strong UI/UX experience.
Client Review
I was seriously impressed with how well Assignment FYP.404 worked. The symptom checker responded intelligently, gave suggestions backed by data, and the interface was professional and reliable. Working with them was beyond great — they really brought my project vision to life.