Sustain Track - Interactive and Accessible Carbon Footprint Analyzer

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Main Author: Monika Yadav, Dolly Mauraya, Risha Ritika, Deepanshi Nigam, Neha Kulshreshtha
Format: Recurso digital
Published: Zenodo 2025
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author Monika Yadav, Dolly Mauraya, Risha Ritika, Deepanshi Nigam, Neha Kulshreshtha
author_facet Monika Yadav, Dolly Mauraya, Risha Ritika, Deepanshi Nigam, Neha Kulshreshtha
contents <p>Keeping an eye on our carbon footprints is important if we want to tackle climate change effectively. Traditional methods for<br>tracking carbon emissions often fall short. They just don’t grab people’s attention or keep them engaged. So, this paper dives<br>into a new approach: a fun and user-friendly system for monitoring carbon footprints, featuring a chatbot interface. Yes,<br>chatbots, these nifty tools can help folks track and cut down on their emissions, thanks to some cool artificial intelligence (AI).<br>With machine learning at play, users can get real-time insights, personalized feedback, and even automated analysis of their data. It’s all about using chatbot technology to encourage more sustainable behaviours. The developed study is an evolution of current behavioral intervention frameworks and carbon assessment methodologies. components of the proposed system are One-On-One conversations, AI recommendations, and real-time tracking of user data about lifestyle choices concerning energy, transport, and food. The chatbot-based tracking increases awareness about the carbon footprint and further encourages physical activity levels, as the study concludes. Retention, as well as a more sustained targeted behavior change. Chatbot technology also has the potential for consumers and companies to drive action as part of global decarbonization solutions, raising levels of narrative experience and participation in carbon counting. </p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_15382978
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Sustain Track - Interactive and Accessible Carbon Footprint Analyzer
Monika Yadav, Dolly Mauraya, Risha Ritika, Deepanshi Nigam, Neha Kulshreshtha
<p>Keeping an eye on our carbon footprints is important if we want to tackle climate change effectively. Traditional methods for<br>tracking carbon emissions often fall short. They just don’t grab people’s attention or keep them engaged. So, this paper dives<br>into a new approach: a fun and user-friendly system for monitoring carbon footprints, featuring a chatbot interface. Yes,<br>chatbots, these nifty tools can help folks track and cut down on their emissions, thanks to some cool artificial intelligence (AI).<br>With machine learning at play, users can get real-time insights, personalized feedback, and even automated analysis of their data. It’s all about using chatbot technology to encourage more sustainable behaviours. The developed study is an evolution of current behavioral intervention frameworks and carbon assessment methodologies. components of the proposed system are One-On-One conversations, AI recommendations, and real-time tracking of user data about lifestyle choices concerning energy, transport, and food. The chatbot-based tracking increases awareness about the carbon footprint and further encourages physical activity levels, as the study concludes. Retention, as well as a more sustained targeted behavior change. Chatbot technology also has the potential for consumers and companies to drive action as part of global decarbonization solutions, raising levels of narrative experience and participation in carbon counting. </p>
title Sustain Track - Interactive and Accessible Carbon Footprint Analyzer
url https://doi.org/10.5281/zenodo.15382978