A novel approach to sustainable behavior enhancement through AI-driven carbon footprint assessment and real-time analytics
Document Type
Article
Source of Publication
Discover Sustainability
Publication Date
12-1-2024
Abstract
This research introduces an Artificial Intelligence-driven mobile application designed to help users calculate and reduce their Carbon Footprint (CFP). The proposed system employs an Intelligent Sustainable Behavior Tracking and Recommendation System, analyzing users' carbon emissions from daily activities and suggesting eco-friendly alternatives. It facilitates sustainability discussions through its chat community and educates users on sustainable practices via an intelligent chatbot powered by a sustainability knowledge base. To promote social engagement around sustainability, the application incorporates a competition and reward system. Additionally, it aggregates behavioral data to inform government sustainability policies and address challenges. Emphasizing individual responsibility, the proposed system stands out from other systems by offering a comprehensive solution that integrates recommendation, education, monitoring, and community engagement, contributing to the cultivation of sustainable communities. The results of a user study (n = 10) employing paired sample t-tests across the three dimensions of the Theory of Reasoned Action (TRA) revealed varying effects of using the application on attitudes, subjective norms, and behavioral intentions related to promoting sustainable human behavior. While the application did not yield significant changes in attitudes (t (9) = 1.7, p = 0.123), or behavioral intentions (t (9) = 0.6, p = 0.541), it did produce a significant increase in subjective norms (t (9) = 4.2, p = 0.002). This suggests that while attitudes towards using this application for sustainability and behavioral intentions remained relatively stable, there was a notable impact on the perception of social influence to engage in sustainable behavior through the use of the application attributed to the sustainability reward system.
DOI Link
ISSN
Publisher
Springer Science and Business Media LLC
Volume
5
Issue
1
Disciplines
Computer Sciences
Keywords
3D object detection, Augmented reality, Carbon footprint, GPS tracker, Sustainability, Theory of reasoned actions (TRA)
Scopus ID
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Jasmy, Ahmad Jasim; Ismail, Heba; and Aljneibi, Noof, "A novel approach to sustainable behavior enhancement through AI-driven carbon footprint assessment and real-time analytics" (2024). All Works. 7004.
https://zuscholars.zu.ac.ae/works/7004
Indexed in Scopus
yes
Open Access
yes
Open Access Type
Gold: This publication is openly available in an open access journal/series