Result Paper on Jarvis 2.0: AI-Powered Conversational Assistant with Voice and Chatbot Interaction and Dashboard Management

Abstract

Artificial Intelligence (AI) virtual assistants have rapidly evolved, becoming integral to modern user interaction across various domains, including customer service, personal productivity, and smart environments. This literature survey investigates the develop and implementation of AI-powered voice and chatbot assistants, with a specific focus on virtual voice assistants. The study reviews key technologies such as automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech (TTS), which enable seamless human-AI interaction. It also explores the use of the MERN stack (MongoDB, Express.js, React.js, Node.js) for building scalable, real-time, and interactive assistant platforms. Particular emphasis is placed on dashboard management systems that enhance transparency, allow customization of assistant behaviour, and provide in sights into user interactions. Through a comprehensive analysis of existing systems and methodologies, this paper aims to provide a foundation for the design and development of Jarvis 2.0, an AI virtual assistant that supports both voice and text-based communication with intuitive dashboard control.