Final Year Project Ideas for Engineering

By: Engineer's Planet

The final year project presents engineering students the opportunity to demonstrate their understanding of what they learn in classroom to real life situations. There are numerous project ideas that may be considered as innovative; with a possibility of designing smart devices and systems, to designing energy solutions and robotics among others.

This project predicts anxiety levels using physiological data from wrist-worn devices. It employs five machine learning algorithms and k-fold cross-validation to refine anxiety assessment and treatment, aiming to enhance mental health evaluation

1. Anxiety Prediction Using Wrist-Worn Physiological Data

This project enhances brain tumor diagnosis by using the Swin Transformer V2 and YOLOv5 for improved detection and classification. Combining these models in an ensemble approach improves accuracy, precision, and real-time analysis

2. Brain Tumor Diagnosis

This project uses advanced machine learning techniques, including K-means clustering and Particle Swarm Optimization, to improve software quality assurance

3.  Enhancing Software Quality Assurance with ML-Based Fault Prediction

This project investigates gender differences in autism spectrum disorder (ASD) related to neonatal jaundice, using data from 1,054 cases. Results show boys with neonatal jaundice are more susceptible to ASD, highlighting the importance of early diagnosis and treatment.

4. Gender Differences in Autism 

This project analyzes the water quality of major Indian rivers using machine learning algorithms (J48, LMT, Naive Bayes) and WEKA tool, assessing parameters like BOD, temperature, pH, DO, and conductivity to classify water as clean or not.

5. Water quality analysis of major rivers of India

In conclusion, these final year projects leverage advanced machine learning techniques to address real-world challenges across various domains. These projects not only contribute to their respective fields but also pave the way for further research and innovation in machine learning applications, ultimately improving outcomes in health, technology, and the environment.