Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

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Edge AI Solutions for Real-Time Engagement in Remote Work Environments

Authors
Sireesha Pendem1, *, Hara Krishna Reddy Koppolu2, R. Sathees Kumar3, Sumit Pokhriyal4, 5, S. Shanmugapriya6, B. Sheeba7
1Associate Professor, Department of Electronics and Communication Engineering, CMR Technical Campus, Kandlakoya Village, Medchal, Hyderabad, Telangana, India
2Data Engineering Lead, CSG Systems International, Englewood, USA
3Assistant Professor, Department of English, Sona College of Technology, Salem, Tamil Nadu, India
4Assistant Professor, Department of Physics, Graphic Era Hill University, Dehradun, India
5Adjunct Professor, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
6Assistant Professor, Department of Artificial Intelligence and Data Science, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
7Assistant Professor, Department of Physics, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India
*Corresponding author. Email: sirisha5716@gmail.com
Corresponding Author
Sireesha Pendem
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_40How to use a DOI?
Keywords
Edge AI; remote work; real-time engagement; intelligent collaboration; low-latency processing; privacy-preserving AI; automated decision-making; cloud-edge integration; AI-driven productivity; scalable AI solutions
Abstract

The surge in adoption of remote working has turbocharged the demand for effective, intelligent and real-time engagement solutions. Edge Artificial Intelligence (Edge AI) is one of these disruptive technologies that are revolutionizing remote collaboration, with its expectations of seamless, real-time, low-latency dynamic and secure computing resources. This article discusses different ways in which Edge ai can be used in real-time remote interaction - intelligent workload partitioning, minimizing latency, privacy in AI models and prompt collaboration. In this paper, we examine the integration of Edge AI with cloud computing technology, real-time communication tools, and automated decision-making systems to increase productivity, team engagement, and resource efficiency. Moreover, the paper also includes key challenges such as computational constraints, security risks, and scalability challenges in Edge AI deployment. A brief segmentation of existing models highlights a gap in research on Edge AI to improve user experiences in remote work, through the proposition of an Edge AI framework.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_40How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sireesha Pendem
AU  - Hara Krishna Reddy Koppolu
AU  - R. Sathees Kumar
AU  - Sumit Pokhriyal
AU  - S. Shanmugapriya
AU  - B. Sheeba
PY  - 2025
DA  - 2025/05/23
TI  - Edge AI Solutions for Real-Time Engagement in Remote Work Environments
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 464
EP  - 476
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_40
DO  - 10.2991/978-94-6463-718-2_40
ID  - Pendem2025
ER  -