Sustainable food development is crucial for minimizing environmental impacts and ensuring the capacity to provide sufficient food for both present and future generations. Many eco-friendly production methods have been adopted world-wide, including organic farming, regenerative agriculture, and plant-based alternatives, aimed at reducing greenhouse gas emissions, conserving water and soil resources, and promoting biodiversity. However, despite this development in sustainable production, consumer awareness and adoption of sustainable food choices remain limited, preventing full environmental and health impacts of these practices from being realized. This paper represents the design of an AI-powered chatbot, offering nutrition guidance, promoting sustainable and healthy daily food choices, while also addressing ethical considerations such as user privacy, fairness, and transparency in its design. The chatbot integrates artificial intelligence and large language models, adapted with domain-specific data on nutrition and sustainability, to engage users in conversations about healthy eating, food waste reduction, and eco-friendly diets. Its design combines a user-friendly interface, a curated knowledge base, and personalized recommendations informed by user preferences. Early evaluations suggest that the system can increase awareness and encourage more sustainable food choices. Ethical aspects such as privacy, transparency, and fairness are embedded in its development to promote responsible use of AI. Future enhancements may include integrating image-based calorie estimation to provide personalized nutritional feedback alongside sustainability guidance.
Building similarity graph...
Analyzing shared references across papers
Loading...
Hanh Ngo Minh Truong
Andrii Kolodiazhnyi
Serhii Sokyrko
Forum for Linguistic Studies
Building similarity graph...
Analyzing shared references across papers
Loading...
Truong et al. (Fri,) studied this question.
synapsesocial.com/papers/68ff87f1c8c50a61f2bdd4e6 — DOI: https://doi.org/10.30564/fls.v7i11.10799
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: