ResearchArticle AnIoTandMachineLearning-BasedModeltoMonitorPerishable Food towards Improving Food Safety and Quality AminaBatool , 1 SouvikGanguli , 2 HashemAliAlmashaqbeh , 3 MuhammadShafiq , 4 A. L. Vallikannu , 5 K. Sakthidasan Sankaran , 5 Samrat Ray , 6 and F. Sammy 7 1 SchoolofAutomation,BeijingInstituteofTechnology,Beijing,China 2 DepartmentofElectricalandInstrumentationEngineering,aparInstituteofEngineeringandTechnology, Patiala147004,India 3 OkanUniversity,Istanbul,Turkey 4 SchoolofArtificialIntelligence,NeijiangNormalUniversity,Neijiang,Sichuan,China 5 DepartmentofECE,HindustanInstituteofTechnologyandScience,Chennai,India 6 SunstoneEduversity,Gurugram,India 7 DepartmentofInformationTechnology,DambiDolloUniversity,DembiDolo,Welega,Ethiopia Correspondence should be addressed to F. Sammy; sammy@dadu.edu.et Received 12 March 2022; Revised 1 May 2022; Accepted 7 May 2022; Published 6 June 2022 Academic Editor: Rijwan Khan Copyright©2022AminaBatooletal.isisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Increased quantities of the same sort of item are not nearly as critical to client happiness as a high-quality product. e re- quirementsandexpectationsoftheconsumerhaveanimpactontheoverallqualityofaproductorservice.eterm“quality”may alsobedefinedasthesumtotalofallthefeaturesthatcontributetotheproductionofgoodsandservicesthataresatisfactorytothe consumer. Certain imported commodities have lately seen an improvement in quality thanks to efforts by importing nations. Additionally, it safeguards food imported from other nations by confirming that it is safe for human consumption before it is released. is article describes a technique for monitoring perishable goods that is based on the Internet of ings and machine learning. Pictures are recorded using high-resolution cameras in this suggested architecture, and then these images are sent to a cloud server using Internet of ings devices. When uploaded to a cloud server, these photos are segmented using the K-means clustering method. en, using the principal component analysis technique, features are extracted from the photos, and the images are categorized using machine learning models that have been trained. is proposed model makes use of the Internet of ings, image processing, and machine learning to monitor perishable food. 1. Introduction ings of the same type are not as important to the cus- tomer’s satisfaction as high-quality products [1]. e quality of a product is influenced by the needs and expectations of the customer. Another way to define quality is to think of it as the sum total of all the characteristics that go into gen- erating things that the customer is satisfied with [2]. Importing countries have recently improved the quality of certain imported items. Additionally, it protects food im- ported from other countries by ensuring that it is safe for consumption. Agricultural products’ external quality is the primary indicator of their immediate sensory quality. Product’s quality is generally judged by its appearance, including its color, texture, size, shape, and imperfections [3]. Food manufacturing company administrators take into consideration the product’s significance, the social setting, and the difficulties experienced by farmers in accomplishing their agricultural tasks [4]. ediscoveryoffaultspriortothesaleorexportofitems is one of the most essential parts of quality assurance [5]. When it comes to determining the quality of mangos, hu- man operators have long relied on their eyes. is is not the case anymore. ey take a long time, are tedious, and are Hindawi Journal of Food Quality Volume 2022, Article ID 6302331, 6 pages https://doi.org/10.1155/2022/6302331