Optimizing Food Utilization: A Smart Inventory Management and AI-Predictive Analytics in Reducing Food Waste

Food waste remains a critical global challenge that contributes significantly to environmental degradation, economic loss, and resource wastage. This essay delves into the innovative integration of technology in the battle against food waste within households and restaurants. We propose a comprehensive solution leveraging innovative inventory management applications and artificial intelligence (AI) systems to tackle this pervasive issue [1]. The smart inventory apps aim to assist households and culinary establishments in tracking food expiration dates and managing groceries efficiently, while AI predictive analytics are employed to forecast restaurant demand, thereby optimizing food supply orders and reducing excess. This article underscores the potential of digital tools in fostering sustainable food consumption practices by exploring current food waste statistics, examining existing technological interventions, and providing a detailed proposal for our integrated tech-based solution. Furthermore, we discuss our approach's implementation framework, potential challenges, and future prospects, providing a holistic view of how technology can be a pivotal ally in minimizing food waste [2]. By aligning technological advancements with sustainable practices, this study illuminates a path toward reducing food waste’s environmental footprint, bolstering food security, and achieving economic efficiency

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-27
DOI
https://doi.org/10.5281/zenodo.14227539
Citations
1
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
0.35
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article

Optimizing Food Utilization: A Smart Inventory Management and AI-Predictive Analytics in Reducing Food Waste

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Food Waste Reduction and Sustainability
0.35
article

Optimizing Food Utilization: A Smart Inventory Management and AI-Predictive Analytics in Reducing Food Waste

article en
1 citations

Abstract

Food waste remains a critical global challenge that contributes significantly to environmental degradation, economic loss, and resource wastage. This essay delves into the innovative integration of technology in the battle against food waste within households and restaurants. We propose a comprehensive solution leveraging innovative inventory management applications and artificial intelligence (AI) systems to tackle this pervasive issue [1]. The smart inventory apps aim to assist households and culinary establishments in tracking food expiration dates and managing groceries efficiently, while AI predictive analytics are employed to forecast restaurant demand, thereby optimizing food supply orders and reducing excess. This article underscores the potential of digital tools in fostering sustainable food consumption practices by exploring current food waste statistics, examining existing technological interventions, and providing a detailed proposal for our integrated tech-based solution. Furthermore, we discuss our approach's implementation framework, potential challenges, and future prospects, providing a holistic view of how technology can be a pivotal ally in minimizing food waste [2]. By aligning technological advancements with sustainable practices, this study illuminates a path toward reducing food waste’s environmental footprint, bolstering food security, and achieving economic efficiency

Zenodo (CERN European Organization for Nuclear Research)
Indian Institute of Technology Kharagpur (IN)
Zero hunger, Responsible consumption and production
Openalex Percentile: Top 32%
Food Waste Reduction and Sustainability
0.35
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Optimizing Food Utilization: A Smart Inventory Management and AI-Predictive Analytics in Reducing Food Waste · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS