Huda, A. S. NazmulAntara, Raihana Shams IslamShams, Sharif MohdFaruk, Md. Fardaus HasanShihab, Nahid AhmedIslam, Md. RakibulSadi, SakibSrabonti, Tasnuva Meherin2025-01-222025-01-2220242024-10ID 20321024ID 20321016ID 20321030ID 20321052ID 20121067http://hdl.handle.net/10361/25254Cataloged from PDF version of final year design project.Includes bibliographical references (pages 102-104).This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2024.Ensuring the safety and quality of meat production has a huge impact on preventing foodborne illness, which is also connected to the betterment of public health. Meat being highly decomposable is bound to be contaminated by such bacteria as E. coli, Salmonella and Listeria, which is responsible for serious health hazards. This paper mainly focuses on the development of a system with advanced technology that can provide an accurate meat quality detection. As a result, all this spoilage identification has been integrated by real time monitoring technologies like machine learning, sensors and microcontrollers. Besides, these technologies aim to detect spoilage indicators such as volatile organic compounds (VOCs), harmful bacteria and environmental factors. Furthermore, this can help for more identification, grading and contamination of meat processing. Ultimately, through detecting the spoilage of meat products, this project will not only help to ensure public health but will also have a great impact on the meat supply industry, society and the environment.137 pagesenBrac University project reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Meat spoilageSpoilage identificationGas sensorsImage processingMachine learning.Project Report