NUST Institutional Repository

Smart Cold Storage System

Show simple item record

dc.contributor.author PROJECT SUPERVISOR Dr. Abdur Rehman Mazhar, Nouman Rafiq Asjad Ikram Ahsan Sher Umais Khan
dc.date.accessioned 2025-03-07T10:38:45Z
dc.date.available 2025-03-07T10:38:45Z
dc.date.issued 2024
dc.identifier.other DE-MECH-42
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/50796
dc.description PROJECT SUPERVISOR Dr. Abdur Rehman Mazhar en_US
dc.description.abstract In an era of environmental awareness and innovative technology, our final year project represents a significant breakthrough in the field of cold storage solutions. We present a smart, eco-friendly cold storage with modern technologies like Object Detection and Adaptive Temperature Control to increase the storage time and minimize the temperature changes so the fruits and vegetables can be stored and remain fresh for a longer amount of time. We included Object Detection for accurate object identification and intelligent temperature control which will further improve the performance of our system and reduce its carbon footprint. Our cold storage not only reduces carbon emissions but also optimizes energy usage, making it a sustainable and cost-effective option. The Object Detection component of the system uses computer vision to recognize objects within the cold storage and dynamically changes the temperature to ensure optimal preservation based on the kind and number of contents. It will also give us information related to the product (for example the apple is stale or fresh). The AI model was first trained to identify the different objects through number of experiments then the model was tested through different experiments. The whole information will be displayed on the internet so we can access the data of the cold storage any time anywhere. The temperature and state of the fruits will also be displayed on the LCD. Finally, the whole setup will be installed inside the storage for its accurate working. This project combines sustainability, energy efficiency, and artificial intelligence to promise a breakthrough in cold storage technology that will help a variety of industries, including agriculture, food preservation, and healthcare. The smart temperature management system is a key component that distinguishes our project. Traditional cold storage systems sometimes suffer from inefficiencies as a result of continuous temperature settings that do not account for the unique needs of various goods. Our system's dynamic temperature changes ensure that each variety of fruit or vegetable is stored optimally, preventing spoiling and increasing shelf life. This personalized technique not only enhances the quality of stored product, but it also saves energy because the technology avoids excessive chilling. Furthermore, the integration of real-time monitoring and data access via the internet gives consumers unparalleled control and supervision over their storage units. This function is especially useful for large scale enterprises like commercial farms and food delivery centers, where keeping produce fresh is important. The future of cold storage is here, and it's smart, green, and powered by cutting-edge artificial intelligence technology. Our systematic approach has the potential to alter the cold storage industry by increasing efficiency, lowering environmental impact, and making advanced storage solutions more accessible to a diverse range of consumers. By integrating innovative technology with eco-friendly methods, we want to create a new standard for cold storage systems globally. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.title Smart Cold Storage System en_US
dc.type Project Report en_US


Files in this item

This item appears in the following Collection(s)

  • BS [123]

Show simple item record

Search DSpace


Advanced Search

Browse

My Account