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.

ISSN

2662-9984

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

85212495461

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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