Quality Assessment and Grading of Milk using Sensors and Neural Networks

J. Swarup Kumar, D. Indira, K. Srinivas, M. N. Satish Kumar
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引用次数: 4

Abstract

Every person's primary source of nutrition comes from milk. Adulterants should not be found in milk that is of high quality. In most cases, local shopkeepers and supermarket shops alike sell milk. Nevertheless, the local milk merchants utilise a slew of adulterants in their product, changing the composition of milk forever. The usage of degraded milk can lead to major health problems. The milk must therefore be tested for the presence of necessary parameters and any adulterants that have been added to it in order to ensure the quality of the milk. Here, sensors are employed to estimate several factors, such as pH, turbidity and colour. Similarly, the milk sector should be able to transmit the administration continuous data on milk quality during the production of milk bundles using the Neural Network model to help combat illegal items like poor milk quality.
基于传感器和神经网络的牛奶质量评价与分级
每个人的主要营养来源都来自牛奶。高质量的牛奶不应该掺假。在大多数情况下,当地的店主和超市都卖牛奶。然而,当地的牛奶商人在他们的产品中使用了大量的掺假物,永远改变了牛奶的成分。饮用变质的牛奶会导致严重的健康问题。因此,为了保证牛奶的质量,必须检测牛奶中是否存在必要的参数和添加的任何掺假物。在这里,传感器被用来估计几个因素,如pH值,浊度和颜色。同样,牛奶行业应该能够使用神经网络模型向管理部门传输牛奶质量的连续数据,以帮助打击劣质牛奶等非法物品。
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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