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Small description about the project like one below The integration of a chatbot within a hostel booking system, aimed at streamlining the reservation process for students and improving the overall user experience.

Tailored Chatbot for Hostel Booking System is a project designed to integrate a chatbot that leverages advanced natural language processing techniques to understand and respond to user queries to the hostel booking system. Traditional hostel booking processes are often time-consuming and involve manual searches and extensive communication with hostel staff. This project seeks to overcome these challenges by creating an easy-to-use chatbot interface that assists students in addressing inquiries.

• Implements advance neural network method.
• A framework based application for deployment purpose.
• High scalability.
• Less time complexity.
• A specific scope of Chatbot response model, using json data format.

• Operating System: Requires a 64-bit OS (Windows 10 or Ubuntu) for compatibility with deep learning frameworks.
• Development Environment: Python 3.6 or later is necessary for coding the sign language detection system.
• Deep Learning Frameworks: TensorFlow for model training, MediaPipe for hand gesture recognition.
• Image Processing Libraries: OpenCV is essential for efficient image processing and real-time hand gesture recognition.
• Version Control: Implementation of Git for collaborative development and effective code management.
• IDE: Use of VSCode as the Integrated Development Environment for coding, debugging, and version control integration.
• Additional Dependencies: Includes scikit-learn, TensorFlow (versions 2.4.1), TensorFlow GPU, OpenCV, and Mediapipe for deep learning tasks.

Detection Accuracy: 96.7% Note: These metrics can be customized based on your actual performance evaluations.

The Sign Language Detection System enhances accessibility for individuals with hearing and speech impairments, providing a valuable tool for inclusive communication. The project's integration of computer vision and deep learning showcases its potential for intuitive and interactive human-computer interaction.

This project serves as a foundation for future developments in assistive technologies and contributes to creating a more inclusive and accessible digital environment.

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2. A. A. BIN ZAINUDDIN, “Enhancing IoT Security: A Synergy of Machine Learning, Artificial Intelligence, and Blockchain”, Data Science Insights, vol. 2, no. 1, Feb. 2024.