Minimization of Food Waste in Retail Sector using Time-Series Analysis and Object Detection Algorithm

Harsh Agarwal, Bhavya Ahir, Pramod J. Bide, Somil Jain, Harshit Barot
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Abstract

One-third of the total food produced gets wasted according to the Food And Agriculture Association of the United Nations. This wastage accounts for 1.3 billion tonnes and the scarcity of food is one of the major concerns globally. This paper presents comprehensive research on various factors that lead to the wastage of food in the retail sector. And a robust methodology is proposed which aims at reducing the waste to as minimal as possible in this sector. A method is proposed which integrates the inventory prediction and forecasting technique with smart dustbins which uses state of the art object detection technique to analyze the waste that gets thrown into bins in order to provide with insights to help optimize the use of raw materials that are used in preparing food and further redistribution and valorization of unpredictable waste. Thus producing minimal food waste.
基于时间序列分析和目标检测算法的零售业食品浪费最小化
根据联合国粮食和农业协会的数据,三分之一的粮食被浪费了。这种浪费占13亿吨,粮食短缺是全球关注的主要问题之一。本文对导致零售部门食品浪费的各种因素进行了全面的研究。并提出了一种强有力的方法,旨在将该部门的浪费减少到尽可能少。提出了一种将库存预测和预测技术与智能垃圾箱相结合的方法,智能垃圾箱使用最先进的对象检测技术来分析扔进垃圾箱的废物,以提供见解,帮助优化用于准备食物的原材料的使用,并进一步重新分配和评估不可预测的废物。从而产生最少的食物浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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