PULICHINTHA NAVANEETH REDDY

Developed and deployed an automated incident detection system, integrating Python, OpenCV, and TensorFlow for real-time analysis and alert generation.

Designed a robust database management system to store and retrieve incident data, improving data accessibility and analytical capabilities.

Implemented advanced AI/ML models (Scikit-learn, Faster R-CNN) to accurately identify and flag suspicious activities, enhancing security response times.

Designed and implemented a predictive maintenance system using IoT sensors and ML algorithms (NumPy, Pandas) to detect pre-dislodgement conditions.

Integrated PI camera technology to provide visual confirmation and enhance the accuracy of dislodgement prediction, minimizing downtime.

Developed a Power BI dashboard for real-time monitoring of conveyor belt health, enabling proactive intervention and operational optimization.

Constructed an unsupervised deep learning pipeline for anomaly detection, processing AVIRIS and Hyperion datasets to identify critical targets.

Implemented advanced preprocessing techniques including radiometric correction, denoising, and pan-sharpening to enhance spectral clarity and data quality.

Utilized autoencoders and spectral analysis to extract precise target features and signatures, significantly improving detection accuracy in complex datasets.