FLUTTERCHAT: A Real Time Firebase Chat Application with AI Based Chat-Bot

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume :12 | Issue : 01 | Page : –
By
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S. Umamaheswari,

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S. Saranya,

  1. Professor, Department of Information Technology, C. Abdul Hakeem college of Engineering and Technology, Melvisharam, Tamil Nadu, India
  2. Assistant Professor, Department of Computer Science and Engineering, C. Abdul Hakeem college of Engineering and Technology, Melvisharam, Tamil Nadu, India

Abstract

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Recently, the development and deployment of ChatBots have gathered significant attention from both developers and researchers. ChatBots represent AI-driven conversational systems capable of understanding and responding to human language using advanced techniques like Natural Language Processing (NLP) and Neural Networks (NN). A cutting-edge real-time chat application has been crafted using Flutter and OpenAI, seamlessly integrating an AI- powered ChatBot with an innovative image generator to enrich user interaction and engagement. The Firebase Chabot Application is its ability to transcend conventional image sharing methods. Users can effortlessly transmit multiple images within a conversation, which are intelligently compiled into a single PDF file. This innovation streamlines the sharing process, ensuring that recipients receive a cohesive and organized collection of images. Moreover, the application empowers users to engage with PDF content directly within the chat interface. By integrating PDF viewing capabilities, individuals can access and review documents shared within conversations without leaving the app. This seamless integration enhances user convenience and fosters efficient collaboration, whether it involves sharing project proposals, presentations, or important documents. The recommended chatbot can be developed using technologies like Flutter, Dart, Android Studio, and Firebase. Furthermore, the implementation will utilize Machine Learning (ML) and Deep Learning (DL) techniques, including Neural Machine Translation (NMT) and Deep Reinforcement Learning (RL) models, to enhance functionality and performance.

Keywords: Real-time chat application, AI-based Chat Bot, image generator, Flutter, OpenAI, personalized responses, natural language processing

[This article belongs to Journal of Mobile Computing, Communications & Mobile Networks (jomccmn)]

How to cite this article:
S. Umamaheswari, S. Saranya. FLUTTERCHAT: A Real Time Firebase Chat Application with AI Based Chat-Bot. Journal of Mobile Computing, Communications & Mobile Networks. 2025; 12(01):-.
How to cite this URL:
S. Umamaheswari, S. Saranya. FLUTTERCHAT: A Real Time Firebase Chat Application with AI Based Chat-Bot. Journal of Mobile Computing, Communications & Mobile Networks. 2025; 12(01):-. Available from: https://journals.stmjournals.com/jomccmn/article=2025/view=0

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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 19/12/2024
Accepted 09/01/2025
Published 24/01/2025
173