DL-Integrated Chatbot with GPS

This paper presents the construction and integration of a deep learning-based chatbot with GPS functionality in order to deliver contextually appropriate and location-aware interactions. The chatbot can understand and generate content similar to that of a human by using advanced natural language processing (NLP) models, such as BERT and GPT. This improves user communication. With the use of GPS integration, the chatbot may obtain real- time location data, which allows it to tailor its responses to the user's geographical position. Our methodology included training the chatbot on many conversational datasets and fine-tuning its contextual understanding with location-specific data. In order to provide seamless communication between the chatbot and GPS, geolocation APIs were used to get accurate, efficeint and reliable location data. The system's performance was evaluated through extensive real-world testing, with a particular emphasis on the correctness and relevancy of the chatbot's responses. User input was obtained in order to assess satisfaction and pinpoint areas in need of development. Findings show that by providing precise, context-aware information, the integrated chatbot greatly enhances user experience. To further improve customer support, the chatbot also offers details about hotels, restaurants, and other well-known locations, along with precise addresses. All things considered, this work demonstrates the practical benefits of combining deep learning with geospatial technology, creating new opportunities for advanced applications in intelligent urban navigation, travel assistance, and customer support.