Sensor based intelligent digital nose to detect spoilage of food using machine learning /
Title
Sensor based intelligent digital nose to detect spoilage of food using machine learning /
Subject
Communication
Description
Patent Number: 202141042368, Applicant:Dr.S.Balamurugan.
Detecting the spoilage of food is a challenging ang important task to be carried out in food processing industry. The food contamination may cause variety of diseases to human mankind including- diarrhoea, dysentery, and sometime may even to death of the individual. Proposed is an intelligent electronic nose, which is capable of diagnosing the food decay based on the foul smell evolved from the food material. The digital nose is composed of an array of metallic-oxide sensors which are capable of detecting the odours from the foods stored roughly more than a week. The sensor arrays are capable of detecting the odours and classifying the same into categories- pungent, alcoholic, fishy, cheesy, fermented, musty and bitter.
Detecting the spoilage of food is a challenging ang important task to be carried out in food processing industry. The food contamination may cause variety of diseases to human mankind including- diarrhoea, dysentery, and sometime may even to death of the individual. Proposed is an intelligent electronic nose, which is capable of diagnosing the food decay based on the foul smell evolved from the food material. The digital nose is composed of an array of metallic-oxide sensors which are capable of detecting the odours from the foods stored roughly more than a week. The sensor arrays are capable of detecting the odours and classifying the same into categories- pungent, alcoholic, fishy, cheesy, fermented, musty and bitter.
Creator
N, Arul Kumar.
Publisher
Intellectual Property India
Date
2021
Language
English
Type
Patent
Collection
Citation
N, Arul Kumar., “Sensor based intelligent digital nose to detect spoilage of food using machine learning /,” CHRIST (Deemed To Be University) Institutional Repository, accessed December 23, 2024, https://archives.christuniversity.in/items/show/2491.