KARTHIK PIPPALLA

I have built a comprehensive hotel management admin dashboard that streamlines operations such as adding, updating, and deleting rooms, customers, and bookings. To enhance efficiency, I integrated Google Cloud’s Computer Vision and Natural Language Processing (NLP) to extract text from a customer’s driver's license, automatically filling out registration forms and minimizing manual data entry. For data storage, I utilized MongoDB, ensuring a scalable and efficient database system. Additionally, I implemented a revenue tracking feature that provides real-time insights into the hotel's financial performance, helping administrators monitor earnings and make informed business decisions. This system improves overall management, reduces human error, and enhances customer onboarding by leveraging AI-driven automation.

GitHub has only the sample code , for full code link kindly email me.
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Created an AI-powered medical chatbot using Natural Language Processing (NLP) techniques. fine tuned the BERT Model with manually collected dataset from the doctors, where it can predict 200+ disease based on statment given by patient, here we used NER to identify the symptoms from the statment. predicted disease is mapped to doctor required and his availble time to shedule the appointment.

this model was qualifed for IEEE submission and model achieved 88 percent of accuracy.

Developed a web-based teaching assistant application using Node.js and MongoDB, where the applications for the teaching application will be release, update, vote, approve based on the role and level.
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Integrated TensorFlow with Raspberry Pi to classify over 200 drone types in real-time using computer vision and deep learning techniques. this was done using yolo model, where it detected with real time data.

this system was intergrated to Raspberrypi, achienved 65 percent of accuracy.