The development of a fruit spoilage detection system originates from the need to reduce agricultural product losses, a global issue affecting both the agricultural and food distribution industries. Spoiled fruit can negatively impact product quality and result in significant economic losses. The primary goal of this system is to assist in screening and removing unsuitable fruit from the supply chain, thereby preserving product quality and meeting consumer demands for fresh produce. The system was designed to simulate the sorting process by utilizing images as a key factor in detecting spoiled fruit. Experimental results demonstrated high efficiency and rapid prediction capabilities, highlighting the system’s potential for practical applications.
ระบบตรวจจับผลไม้เน่ามีที่มาจากความต้องการในการลดการสูญเสียผลผลิตทางการเกษตร ซึ่งเป็นปัญหาที่เกิดขึ้นทั่วโลกโดยเฉพาะในอุตสาหกรรมการเกษตรและการจัดจําหน่ายอาหาร ผลไม้ที่เน่าเสียจะส่งผลกระทบต่อคุณภาพของผลิตภัณฑ์และสามารถก่อให้เกิดความสูญเสียทางเศรษฐกิจได้อย่างมาก การพัฒนาระบบตรวจจับผลไม้เน่าจึงมีเป้าหมายเพื่อช่วยในการคัดกรองและแยกผลไม้ที่ไม่เหมาะสมออกจากกระบวนการจัดส่ง เพื่อรักษาคุณภาพของสินค้าและตอบสนองต่อความต้องการของผู้บริโภคที่ต้องการผลไม้สดใหม่
คณะวิศวกรรมศาสตร์
Currently, lithium batteries are widely used in electronic devices and electric vehicles, making the estimation of their State of Health (SOH) crucial. Accurate SOH estimation helps extend battery lifespan, reduce maintenance costs, and prevent safety issues such as overheating or explosions. This project aims to study and analyze mathematical models of batteries and develop SOH estimation techniques using Neural Networks to enhance accuracy and evaluation speed. The experiment involved collecting charge and discharge data from three lithium battery cells under controlled temperature conditions while maintaining a constant current. The current, voltage, and time data were recorded and analyzed to determine the battery capacity for each cycle. These data were then used to train a Neural Network model. The results demonstrated an effective method for predicting battery health status. The outcomes of this project can contribute to the development of a Battery Management System (BMS) that improves battery efficiency and longevity. Additionally, it provides a foundation for applying artificial intelligence techniques in the energy sector effectively.
คณะอุตสาหกรรมอาหาร
This research investigates active packaging films made from polyvinyl alcohol (PVA) and nanocellulose fibers (NFC), incorporating silver nanoparticles (AgNPs) synthesized from Terminalia chebula extract, which possesses antibacterial and antifungal properties. The developed films were tested for their mechanical properties, microbial inhibition, and biodegradability. The results showed that the addition of AgNPs from Terminalia chebula enhanced product protection and effectively extended the shelf life of strawberries while being environmentally friendly.
คณะวิทยาศาสตร์
Nowadays, automobiles are the most widely used form of transportation. This increases the risk of accidents. Therefore, car users prefer to get insurance to reduce the risk in the event of an accident. As for the insurance company, the company will be responsible for damages according to the conditions of the policy. One of the duties of a company's claims department is to procure spare parts to control costs. However, in the case of compensation, there may be erroneous operations, such as ordering the wrong parts or ordering more than necessary. Currently, insurance companies do not have a very efficient management system. This research aims to develop a system for managing and storing automobile parts for insurance companies. The system is designed to be able to track the status of spare parts from storage to disbursement. It uses barcode technology to increase accuracy and reduce errors in data recording. Such a system will help insurance companies manage spare parts systematically, reduce unnecessary costs, and increase efficiency in providing services.