CALLX

March 2024
Vol-10, Issue-2
Paper ID: 22967
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Web application Video call platform Zego Cloud WebSocket API React.js Real-time communication Video calls Chat system Time management Screen sharing Customizable views External device integration No account requirement.
Abstract
In this web application project, we aim to create a highly versatile and accessible online video call platform using Zego Cloud's WebSocket API integrated with the power of React.js. Our goal is to provide a seamless and feature-rich experience for users, without imposing any restrictions or time limits. The application will empower users to connect, communicate, and collaborate in real- time with the following key features: Video Calls: Multiple users can engage in simultaneous video calls, fostering effective communication. Chat System: A real-time chat feature enables users to exchange messages, enhancing the interactive experience. Time Management: Built-in time management functionalities ensure efficient scheduling and coordination during video calls. Screen Sharing: Users can effortlessly share their screens, facilitating presentations, demonstrations, and collaborative work. Customizable Views: The application offers customizable screen layouts, including grid views and user-specific views, allowing users to tailor their experience. External Device Integration: Support for external devices like microphones and speakers enhances audio quality and user control. No Account Requirement: Users are not burdened with sign-up or login requirements, ensuring a hassle-free experience from the start. Our project seeks to combine the flexibility and power of Zego Cloud with the user-friendly and dynamic capabilities of React.js, resulting in an online video call application that is accessible, feature-rich, and intuitive. Users will enjoy a seamless video communication experience with the freedom to customize their interactions.

Author Information

# Name Institute / Affiliation
1 Neha Sharnagat Cummins College Of Engineering For Women Nagpur
2 Brahmami Chakule Cummins College Of Engineering For Women Nagpur
3 Sachi Meshram Cummins College Of Engineering For Women Nagpur
4 Shreeya Pathak Cummins College Of Engineering For Women Nagpur
5 Snehal Chandore Cummins College Of Engineering For Women Nagpur
6 Harshwardhan Kharpate Cummins College Of Engineering For Women Nagpur

How to Cite

Use the following formats to cite this article in your research.

APA Style
Sharnagat, Neha, Chakule, Brahmami, Meshram, Sachi, Pathak, Shreeya, Chandore, Snehal, & Kharpate, Harshwardhan (2024). CALLX. International Journal of Advance Research and Innovative Ideas In Education, 10(2), 1705-1710.
MLA Style
Sharnagat, Neha, et al. "CALLX." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, 2024, pp. 1705-1710.
IEEE Style
Neha Sharnagat, Brahmami Chakule, Sachi Meshram, Shreeya Pathak, Snehal Chandore, and Harshwardhan Kharpate, "CALLX," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, pp. 1705-1710, 2024.
Vancouver Style
Sharnagat Neha, Chakule Brahmami, Meshram Sachi, Pathak Shreeya, Chandore Snehal, Kharpate Harshwardhan. CALLX. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(2):1705-1710.
Harvard Style
Sharnagat, Neha, Chakule, Brahmami, Meshram, Sachi, Pathak, Shreeya, Chandore, Snehal, & Kharpate, Harshwardhan (2024) 'CALLX', International Journal of Advance Research and Innovative Ideas In Education, 10(2), pp. 1705-1710.
Chicago Style
Sharnagat, Neha, et al. "CALLX." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 1705-1710.
Turabian Style
Sharnagat, Neha, et al. "CALLX." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 1705-1710.

Export Citation

Related Research

A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
Vaibhav Ashok Bhangare et al. 2026 Computer Engineering
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
Vishakha Jadhav et al. 2026 Human Resource Management, Artificial Intelligence, Machine Learning, Payroll Systems, Cybersecurity, Business Intelligence, Robotic Process Automation, Employee Analytics, Digital Transforma
PDF Unavailable
Civic Engagement & Empowerment Platform
Supriya Dadaso Bankar et al. 2026 Computer engineering
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
Prof. Priyanka P. Kakade et al. 2026 Computer Engineering
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
Rohan Mulik et al. 2026 Computer Engineering
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
Kirti Datir et al. 2026 Computer Engineering
PDF Unavailable
Employee Performance Portal
P.Harika et al. 2026 Computer science and engineering
PDF Unavailable