AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem

Abstract This paper presents the development and functionalities of the AI-FEED web-based platform (ai-feed.ai), designed to address food and nutrition insecurity challenges within the food charity ecosystem. AI-FEED leverages advancements in artificial intelligence (AI) and blockchain technology to facilitate improved access to nutritious food and efficient resource allocation, aiming to reduce food waste and bolster community health. The initial phase involved comprehensive interviews with various stakeholders to gather insights into the ecosystem’s unique challenges and requirements. This informed the design of four distinct modules in the AI-FEED platform, each targeting the needs of one of four stakeholder groups (food charities, donors, clients, and community leaders). Prototyping and iterative feedback processes were integral to refining these modules. The food charity module assists charities in generating educational content and predicting client needs through AI-driven tools. Based on blockchain technology, the food donor module streamlines donation processes, enhances donor engagement, and provides donor recognition. The client module provides real-time information on food charity services and offers a centralized repository for nutritional information. The platform includes a comprehensive mapping and proposal system for community leaders to strategically address local food insecurity issues. AI-FEED’s integrated platform approach allows data sharing across modules, enhancing overall functionality and impact. The paper also discusses ethical considerations, potential biases in AI systems, and the transformation of AI-FEED from a research project to a sustainable entity. The AI-FEED platform exemplifies the potential of interdisciplinary collaboration and technological innovation in addressing societal challenges, particularly in improving food security and community health.

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Publication Details

Journal
International Journal of Computational Intelligence Systems
Published
2024-10-14
DOI
https://doi.org/10.1007/s44196-024-00656-9
Citations
9
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
3.13

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article

AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem

Norma Olvera, Ioannis A. Kakadiaris, Junfeng Jiao, Susie Gronseth et al.
9 citations
International Journal of Computational Intelligence Systems
AI in Service Interactions
3.13
article

AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem

Norma Olvera, Ioannis A. Kakadiaris, Junfeng Jiao, Susie Gronseth, Marcus Sammer, Kijin Seong, Elizabeth Anderson-Fletcher, Alison Reese
article en
9 citations

Abstract

Abstract This paper presents the development and functionalities of the AI-FEED web-based platform (ai-feed.ai), designed to address food and nutrition insecurity challenges within the food charity ecosystem. AI-FEED leverages advancements in artificial intelligence (AI) and blockchain technology to facilitate improved access to nutritious food and efficient resource allocation, aiming to reduce food waste and bolster community health. The initial phase involved comprehensive interviews with various stakeholders to gather insights into the ecosystem’s unique challenges and requirements. This informed the design of four distinct modules in the AI-FEED platform, each targeting the needs of one of four stakeholder groups (food charities, donors, clients, and community leaders). Prototyping and iterative feedback processes were integral to refining these modules. The food charity module assists charities in generating educational content and predicting client needs through AI-driven tools. Based on blockchain technology, the food donor module streamlines donation processes, enhances donor engagement, and provides donor recognition. The client module provides real-time information on food charity services and offers a centralized repository for nutritional information. The platform includes a comprehensive mapping and proposal system for community leaders to strategically address local food insecurity issues. AI-FEED’s integrated platform approach allows data sharing across modules, enhancing overall functionality and impact. The paper also discusses ethical considerations, potential biases in AI systems, and the transformation of AI-FEED from a research project to a sustainable entity. The AI-FEED platform exemplifies the potential of interdisciplinary collaboration and technological innovation in addressing societal challenges, particularly in improving food security and community health.

International Journal of Computational Intelligence SystemsVol. 17(1)
Volition (United States) (US), University of Houston (US), The University of Texas at Austin (US)
National Science Foundation, Directorate for Technology, Innovation and Partnerships
Openalex Percentile: Top 7%
AI in Service Interactions
3.13
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