bhavvi bhavana

Developed a full-stack web application for data mapping and visualization, enabling users to generate visual insights through dynamic charting. Implemented an ASP.NET Core MVC backend with SQL Server for data storage and utilized Chart.js for interactive and responsive charting experiences. The tool supported real-time table testing, chart rendering, and export options for results.

Designed an AI-powered smart helmet for real-time safety monitoring in coal mines, incorporating Arduino, gas and temperature sensors, and a distress signal system. The backend was built with ASP.NET Core and a Blazor UI, connecting sensor data to Azure Functions for cloud processing and emergency alerting. This system improved miner safety by detecting harmful gases with 96% accuracy and reduced

Built a web application that translates natural language queries into executable SQL using LLM integration, specifically the DeepSeek model via Ollama API. Developed with ASP.NET Core MVC, C#, and SQL Server, it included schema-parsing logic and a modular service layer. The application empowered non-technical users to explore relational data intuitively without writing SQL.

Developed a reporting application converting user prompts in natural language to executable SQL queries by integrating the OpenAI GPT model. Built using ASP.NET Core with C# and SQL Server, it featured a Blazor UI for user-friendly query entry and formatted result display. The system included secure query execution with validation and AI prompt chaining for schema-awareness and error-correction.

Built an advanced SQL query tool powered by Azure OpenAI, designed to assist users with writing, debugging, and explaining SQL through a chat-based Blazor interface. It integrated database schema analysis and tokenized AI prompts for better SQL understanding. The tool allowed users to visualize results dynamically as tables or pie charts using Chart.js and achieved 92% accuracy in AI-generated que

Developed an intelligent driver safety system using Arduino and alcohol sensors to detect intoxication and prevent engine ignition. The application utilized ASP.NET Core with a Blazor frontend and SQL Server for data storage, integrating Azure IoT Hub and Azure Functions for real-time sensor data streaming. It achieved 94% accuracy in alcohol detection and a 15% reduction in unauthorized vehicle u

Grade: 8.32 CGPA

Completed a Bachelor of Technology in Computer Science Engineering. Achieved a CGPA of 8.32.

Grade: 9.5 CGPA

Completed intermediate education at Sri Vikas Junior College. Achieved a CGPA of 9.5.