PATENTS & PUBLICATIONS

As the inventor of the patented “Traffic Control System” under VIT-AP University, India, I have developed an innovative solution to address the challenges of urban traffic management. This system intelligently analyzes real-time data on traffic conditions, vehicle types, and weather conditions to optimize traffic signal timings, ensuring efficient traffic flow and reduced waiting times. Unlike traditional systems, it adapts to changing traffic patterns and responds to varying demands in different periods. The system also prioritizes various factors such as emergency vehicles and weather conditions, offering a more responsive and effective solution to traffic congestion. This invention is a testament to my commitment to leveraging technology for societal benefits, particularly in enhancing transportation efficiency and reducing urban congestion.

This research paper introduces a significant advancement in aquaculture systems, proposing a deep learning model for real-time detection of dead fish, an indicator of pond imbalance. The model, leveraging the YoloV5 architecture, has been trained on thousands of images and achieves an accuracy of 88%. By automating the detection process, the system allows for immediate mitigation measures, enhancing the health and efficiency of aquaculture facilities. This work represents a substantial contribution to the field of “smart fish farming”, promoting sustainable development through increased resource efficiency.

In this research, I’ve developed an innovative approach to fabricate high-performance perovskite solar cells using artificial intelligence algorithms. I’ve applied machine learning regression algorithms to predict band-gap for efficient and stable PSCs, achieving up to 99.3% accuracy for heat of formation and 90.5% for bandgap prediction. This work represents a significant step towards overcoming the challenges in the field and paves the way for future research in lead-free perovskites.