Deepfake Image and Video Screening Tool
Convolutional neural network analyzing facial artifact inconsistencies, optical flow anomalies, and spectral noise in videos.
Project Overview
Detects AI-synthesized face swaps and GAN-generated media. Analyzes frame-level landmark consistency, eye blinking patterns, and frequency domain noise artifacts to output confidence score reports. ### Practical Student Engineering Solution Fully functional hardware demonstration prototype equipped with dedicated microcontrollers, precision sensors, actuators, and an interactive cloud/mobile telemetry dashboard. ### Key Learning Outcomes - Embedded C / MicroPython firmware architecture and sensor interfacing - IoT telemetry protocols (MQTT / HTTP / BLE / LoRaWAN) - Power regulation, hardware debugging, and PCB design principles - Comprehensive technical documentation aligned with IEEE academic standards
Modern commercial and industrial infrastructure requires automated, real-time sensing and telemetry. Conventional manual monitoring suffers from high latency, human error, and lack of predictive fault visibility for Deepfake Image and Video Screening Tool.
A turnkey engineering prototype integrating high-precision sensor modules, dedicated microcontroller unit, and cloud telemetry protocols to automate measurement, trigger alert thresholds, and provide remote dashboard control.