Exploring Real-Time Data Transfer in Slack Flow Messenger Using React and Firebase with Integrated AI Assistance

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Titel: Exploring Real-Time Data Transfer in Slack Flow Messenger Using React and Firebase with Integrated AI Assistance
Autoren: Sharma, Vinod
Quelle: Journal of Integrated Engineering Sciences; Vol. 1 No. 1 (2025): Journal of Integrated Engineering Sciences; 01-11 ; 3049-3919
Verlagsinformationen: Academic Scholars Press
Publikationsjahr: 2025
Schlagwörter: Slack, HTML, CSS, Java Script, Firebase, AI, ReactJS
Beschreibung: The application is designed to offer a smooth and seamless communication experience with a personalized touch. It focuses on fast, efficient messaging and real-time data transfer. Developed using the React framework for front-end and Firebase for back-end, the application leverages Firebase's powerful real-time database for data synchronization between client and server. This combination ensures a swift and efficient messaging experience. A standout feature is the AI-powered search assistant, trained on extensive user interaction data and continuously improving. Additional features include message threading, reactions, emoji support, and more. The user interface is designed to be clean and intuitive, facilitating easy navigation. Overall, the Slack Flow Messenger project with React and Firebase aims to deliver a fast, efficient, and personalized messaging experience.
Publikationsart: article in journal/newspaper
Dateibeschreibung: application/pdf
Sprache: English
Relation: https://journals.academicsp.com/index.php/jies/article/view/1/2; https://journals.academicsp.com/index.php/jies/article/view/1
DOI: 10.63686/jies.v1i1001
Verfügbarkeit: https://journals.academicsp.com/index.php/jies/article/view/1
https://doi.org/10.63686/jies.v1i1001
Rights: Copyright (c) 2025 Journal of Integrated Engineering Sciences (JIES) ; https://creativecommons.org/licenses/by/4.0
Dokumentencode: edsbas.36F669B5
Datenbank: BASE