Developing an AI-Powered Chatbot for CO2 Emissions Estimations Utilizing Botpress Framework
Aizpurietis, Janis (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024053018799
https://urn.fi/URN:NBN:fi:amk-2024053018799
Tiivistelmä
In today's world, there is a need for tools and methodologies to measure greenhouse gas emissions resulting from both individual and business activities. In response to this necessity, the author of this thesis is developing an AI-based chatbot designed to assist individuals and small to medium-sized businesses in calculating their carbon dioxide (CO2) emissions based on their annual electricity consumption.
This thesis constructs upon an idea perceived during a hackathon event, where the author and his team received recognition for developing one of the best solutions to help small and medium-sized companies in Environmental, Social, and Governance (ESG) reporting. The central objective is to research a technological solution for this established business concept, focusing on the development of an AI-based chatbot to enable CO2 calculations for businesses with an easy and user-friendly approach.
Despite increasing pressure for businesses worldwide to report their emissions, many remain unaware of their carbon footprint and lack the expertise to conduct accurate calculations. While European regulations currently encourage voluntary emissions reporting, mandatory reporting is expected for most businesses in the near future.
Recognizing the complexity and time-consuming nature of emission calculations, the author explores the potential of an AI chatbot tool to streamline this process for individuals and companies. This thesis concentrates specifically on annual electricity-related CO2 emissions, proposing a chatbot solution tailored to help individuals and small and medium-sized enterprises in emission reporting.
Keeping scalability and accuracy in mind, the author recognizes Botpress as the optimal platform for developing such a solution. In the end, the author provides a comprehensive overview of the chatbot solution, detailing its functionality, implementation process, and potential impact on simplifying CO2 emissions calculations for individuals and businesses alike.
This thesis constructs upon an idea perceived during a hackathon event, where the author and his team received recognition for developing one of the best solutions to help small and medium-sized companies in Environmental, Social, and Governance (ESG) reporting. The central objective is to research a technological solution for this established business concept, focusing on the development of an AI-based chatbot to enable CO2 calculations for businesses with an easy and user-friendly approach.
Despite increasing pressure for businesses worldwide to report their emissions, many remain unaware of their carbon footprint and lack the expertise to conduct accurate calculations. While European regulations currently encourage voluntary emissions reporting, mandatory reporting is expected for most businesses in the near future.
Recognizing the complexity and time-consuming nature of emission calculations, the author explores the potential of an AI chatbot tool to streamline this process for individuals and companies. This thesis concentrates specifically on annual electricity-related CO2 emissions, proposing a chatbot solution tailored to help individuals and small and medium-sized enterprises in emission reporting.
Keeping scalability and accuracy in mind, the author recognizes Botpress as the optimal platform for developing such a solution. In the end, the author provides a comprehensive overview of the chatbot solution, detailing its functionality, implementation process, and potential impact on simplifying CO2 emissions calculations for individuals and businesses alike.