A Context-Aware Emergency Assistance Chatbot Employing Recurrent Neural Networks for Personalized First Aid Guidance
Jivantika Gulati, Ramakrishnan Raman · 2024
A highly sophisticated chatbot designed to provide real-time assistance during emergencies and personalized guidance for administering medical treatment. This virtual assistant utilizes advanced Recurrent Neural Networks (RNN) to offer insightful responses to user inquiries on various pressing scenarios. The model has undergone training using diverse datasets and utilizes advanced deep learning techniques, including incorporation and LSTM approach elements, to provide responses that are both coherent and comprehensive. The framework is specifically intended to provide flexible interactions that may be adjusted to suit the constantly evolving nature of emergency situations. In order to provide tailored advice, the chatbot flawlessly incorporates GPS position, user context, and real-time sensor data. Ensuring customer security and facilitating effective communication are the main goals of the chatbot. In addition to meeting immediate requirements, this effort helps enhance emergency response systems driven by artificial intelligence. The ability of RNN algorithms to mimic human behavior assistance during emergencies is shown.