The project uses artificial intelligence (AI) and deep learning to develop a smart police system (Smart Police) to analyze the identity of individuals and vehicles suspected of involvement in crimes. The system uses CCTV cameras to detect people with concealed weapons and track vehicles involved in crimes. The system also sends alerts to the police when a crime is detected. The Smart Police system is a collaboration between the Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, the Provincial Police Region 2, the Chachoengsao Foundation for Development, and the Smart City Office of Chachoengsao Province. The system is designed to prevent and deter crime, increase public safety and order, and build a network of cooperation between the government, the private sector, and the community. The system is currently under development, but it has the potential to be a valuable tool for law enforcement. The system could help to reduce crime and improve public safety in Chachoengsao Province and other parts of Thailand.
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คณะวิศวกรรมศาสตร์
This project aims to introduce an Automated Vertical Metal Sheet Storage System. The project is aimed at teaching how to make an Automation Vertical Metal Sheet Storage System with the integration of microcontroller devices. The project is divided into two main sections, which are the structure and control systems of the Automation Vertical Metal Sheet Storage System that will be designed and drawn through a computer program and constructed using major aluminum structures upon completion of their actual sizes outlined in the programs. Also, a Microcontroller control system using GX Works 2 program from Mitsubishi PLC has been designed for this purpose where it controls up and down movements as well as sideways movement of the pallet. It also has a weighing capability along with touch screen display for displaying information about the steel plates and controlling the Automation Vertical Metal Sheet Storage System with safety light curtain that protect users safety. These tests have shown that the machine operates normally. There are few mistakes whose rates fall within those expected by humans.
คณะศิลปศาสตร์
"Niyom Thai" represents health-centric footwear adorned with traditional Thai patterns, embodying an innovative approach to sustainable development tailored to the current needs of local communities. These shoes utilize natural materials to mitigate fatigue and integrate safety technologies, including location tracking via a mobile application and heart rate monitoring. This addresses the aspects of convenience and well-being in both daily life and travel
คณะแพทยศาสตร์
This study explores the application of deep convolutional neural networks (CNNs) for accurate pill identification, addressing the limitations of traditional human-based methods. Using a dataset of 1,250 images across 10 household remedy drugs, various CNN architectures, including YOLO models, were tested under different conditions. Results showed that natural lighting was optimal for imprinted pills, while a lightbox improved detection for plain pills. The YOLOv5-tiny model demonstrated the best detection accuracy, and efficientNet_b0 achieved the highest classification performance. While the model showed strong results, its generalization is limited by sample size and drug variability. Nonetheless, this approach holds promise for enhancing medication safety and reducing errors in outpatient care.