Created an LSTM model through RNN and nonlinear prediction of stock prices, significantly improving prediction accuracy.

Achieved an increase in prediction accuracy from ~80% to ~95% by incorporating market sentiment analysis, RSI and Bollinger Band indicators, resulting in more reliable and actionable forecasts.

Executed the model using TensorFlow and Keras, allowing for maximum accuracy and customization, reducing prediction error by ~20%.

Developed a Hydroponic Farming Model with IoT to optimize crop farming, resulting in a harvest boost of over~50%, increasing crop yield from 200kg to 300kg per cycle.

Implemented IoT automation, enhancing soil fertility by ~40% and reducing water usage by approximately ~90%, cutting water consumption from 1000 liters to 100 liters per cycle.

Leveraged IoT and Cloud solutions to accelerate the harvest cycle by ~20% for herbs, decreasing growth time from 60 days to 45 days, while also providing robust protection against pests and diseases.

Created AWS Infrastructure for Data analysis of historical and live data using AWS Glue for ETL, Redshift for Data Warehouse, S3, RDS for Data Storage.

Created RESTful API for live data using python, Airflow for orchestration of all tasks. And utilized Tableau for Data visualization.

Developed a cross-platform mobile application using React Native for hospital management with a minimal and adaptive GUI integrating: Admin, Nurse, Doctor, and Patient.

Implemented NFC technology to streamline data transfer, reducing the need for physical files by ~90%.

Utilized Google Firebase for real-time database management and OAuth 2.0 for secure user authentication and tile-based access control.