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

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Predictive Engagement Models for Sustainable Environmental Interaction

Authors
Bechoo Lal1, 2, *, K. Deepthi Reddy3, M. Adhiyaman4, Debabrata Mohanty5, Deepak Gupta6, 7, G. Swarnalakshmi8
1Department of Computer Science and Engineering, KLEF- KL University, Vijayawada Campus, Guntur, Andhra Pradesh, India
2Research Scholar, Department of Computer Science and Engineering, Manipur International University, MIU Ghari, Airport Road, Imphal West, Manipur, 795140, India
3Department of Computer Science and Engineering, CVR College of Engineering, Ibrahimpatnam, Vastunagar, Mangalpalle, Telangana, India
4Assistant Professor, Department of Civil, Sona College of Technology, Salem, Tamil Nadu, India
5Senior Faculty, Pragati Group of Institution, Bhawanipatn, Saradhapur, Odisha, 766002, India
6Department of Mechanical Engineering, Graphic Era Hill University, Dehradun, 248002, Uttarakhand, India
7Department of Mechanical Engineering, Graphic Era Deemed to be University, Dehradun, 248002, Uttarakhand, India
8Assistant Professor, Department of Mech, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India
*Corresponding author. Email: drblalpersonal@gmail.com
Corresponding Author
Bechoo Lal
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_77How to use a DOI?
Keywords
SDGs; Predictive models; Environmental interaction; Machine learning; Reinforcement learning; Sustainability
Abstract

This work investigates the creation of predictive engagement models that promote sustainable interactions with the environment. Our research aims at enabling machine clients to better interpret and act on the considerations of normal citizes and apply evidence-based insights in real-time systems. In the context of the Sustainable Development Goals (SDGs), business innovation, consumer choice, and policy frameworks are explored through the research. Utilizing generational information, namely (Gen)Z based behaviors, helps the models predict and improve engagement strategies; engagement strategies for individuals, communities, and organizations. Cultural and socio-economic elements are incorporated into this research providing an in-depth model that can be modified for regional differences and real-world problems. The study seeks to inform more sustainable environmental practices, both locally and globally, that will create a custodial attitude towards sustainable and environmental best practices to ensure that benefits last much longer than the duration of the project whereby producing a sound explanatory framework embedded with relevant data.

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_77How 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  - Bechoo Lal
AU  - K. Deepthi Reddy
AU  - M. Adhiyaman
AU  - Debabrata Mohanty
AU  - Deepak Gupta
AU  - G. Swarnalakshmi
PY  - 2025
DA  - 2025/05/23
TI  - Predictive Engagement Models for Sustainable Environmental Interaction
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 907
EP  - 919
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_77
DO  - 10.2991/978-94-6463-718-2_77
ID  - Lal2025
ER  -