Design and Implementation of an Intelligent System based on ML and IOT for Ordinary to Smart Refrigerator Conversion

dc.contributor.guideChawla, Paras
dc.coverage.spatial
dc.creator.researcherJain, Pulkit
dc.date.accessioned2022-12-09T05:38:57Z
dc.date.available2022-12-09T05:38:57Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered
dc.description.abstractMachine Learning has evolved with a variety of algorithms to enable state of the art computer vision applications. In particular the need for automating the process of real time food item identification, there is a huge surge of research so as to make smarter refrigerators. According to a survey by the Food and Agriculture Organization of the United Nations (FAO), it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and large amount of food is wasted from homes and restaurants itself. Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage. But a major issue is high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator. To address these issues, the current work proposes an automated identification algorithm for computer vision in smart refrigerators using VGG-16, InceptionV3 and Mobile Net CNN architectures. newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/423309
dc.languageEnglish
dc.publisher.institutionDept of Electronics and Communication Engineering
dc.publisher.placeMohali
dc.publisher.universityChandigarh University
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.titleDesign and Implementation of an Intelligent System based on ML and IOT for Ordinary to Smart Refrigerator Conversion
dc.title.alternative
dc.type.degreePh.D.

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