Browse 150 industry-mentored Final Year Projects, IEEE Projects, Mini Projects and Major Projects for CSE, ECE, EEE and IT students — across IoT, AI & ML, Robotics, Embedded Systems, VLSI and Computer Vision. Every project kit from our Chennai project centre ships with source code, hardware guidance (where applicable), documentation and demo support.
150 projects found
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2024-25 • Difficulty: Beginner
Abstract — Recognises and classifies traffic signs from live camera footage using a CNN trained on the GTSRB dataset, intended as a driver-assistance alert module.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Advanced
Abstract — Classifies dermatological images into multiple skin-condition categories using a fine-tuned EfficientNet model, achieving 92% top-1 accuracy on a benchmark skin-lesion dataset.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2024-25 • Difficulty: Advanced
Abstract — Flags defective units on a production line by detecting anomalies in sensor-measured dimensional and visual features using an isolation-forest model, reducing manual QC inspection load.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Intermediate
Abstract — Classifies walking, running, sitting and falling activities from accelerometer and gyroscope wearable data using a random-forest model, aimed at elderly fall-detection applications.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2024-25 • Difficulty: Beginner
Abstract — Predicts a numeric star rating from review text alone using TF-IDF features and a gradient-boosting classifier, validated on an e-commerce review dataset.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Advanced
Abstract — Predicts equipment failure from vibration and temperature sensor time-series using a gradient-boosted survival model, giving maintenance teams a two-week failure-risk window.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Beginner
Abstract — Classifies leaf images into plant species using a fine-tuned CNN, packaged as a mobile-friendly app to help farmers and botanists identify species from a phone camera photo.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2024-25 • Difficulty: Intermediate
Abstract — Classifies speaker emotion from voice-recording features like pitch and MFCCs using an SVM and CNN ensemble, achieving 87% accuracy across six emotion categories.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Advanced
Abstract — Detects pedestrians, vehicles and traffic signs in real time from dashcam footage using a YOLOv8 model optimised for edge-device inference at over 30 FPS.
Aurobotix Systems Research Team • Domain: Machine Learning • Academic Year: 2025-26 • Difficulty: Beginner
Abstract — Trains a CNN on the MNIST dataset and a custom signature corpus to recognise handwritten digits and verify signature authenticity for document-processing workflows.
Aurobotix