Smart Agriculture has rapidly developed in recent years, particularly with the integration of robotics and automation technologies to improve production efficiency and reduce costs, thereby enhancing the quality of current agricultural practices. A key innovation in this area is the rail-based robotic arm, designed to enhance work efficiency using a rail system with high precision and effectiveness. The application of this robotic arm covers various processes, such as planting, sorting, maintenance, harvesting, and resource management, allowing continuous operation and reducing human labor in repetitive and high-risk tasks. Studies have shown that the use of rail-based robotic arms in agriculture can significantly improve work efficiency, reduce production costs, and effectively mitigate environmental impact. By using robots in agricultural processes, it is possible to reduce contamination, lower the risk of crop damage, and make agriculture more sustainable. Additionally, it can increase accuracy in operations on limited spaces or farms with diverse crops. From these findings, it can be concluded that adopting rail-based robotic arm technology in agriculture not only enhances long-term production efficiency but also promotes sustainable agriculture and maximizes resource use, meeting future agricultural demands
ประเทศไทยเป็นประเทศเกษตรกรรม การที่จะนำเทคโนโลยีเข้ามาช่วยพัฒนาระบบการเกษตรกรรม ให้มีความทันสมัย มีประสิทธิภาพ เพื่อช่วยยกระดับอุตสาหกรรมการเกษตรของไทยนั้น เป็นสิ่งที่มีความสำคัญมาก เราจึงได้พัฒนา “เเขนกลระบบรางเพื่อการเกษตรอัฉริยะ” โดยเทคโนโลยีนี้ช่วยลดการใช้แรงงานคน เพิ่มความแม่นยำในการทำงาน และสามารถทำงานได้ตลอดเวลาไม่หยุดพัก นอกจากนี้ยังช่วยลดต้นทุนการผลิตและเพิ่มผลผลิต ทำให้เกษตรกรสามารถแข่งขันในตลาดโลกได้ดียิ่งขึ้น และช่วยพัฒนาความยั่งยืนในภาคการเกษตรของประเทศไทย
คณะวิศวกรรมศาสตร์
The presented project topic is Garbage Sorting Systems. The purpose is to study the operation and develop a waste sorting system that can automatically detect the type of waste using a proximity sensor to separate the types of metal and non-metal waste, as well as an ultrasonic sensor to check the amount of waste in the bin. If the amount of waste exceeds the specified amount, the system will send a notification to the communication device connected to the system, such as a smartphone or computer. The operation of the system is designed to increase the efficiency of waste management, reduce the burden of manual waste sorting, and promote recycling. This system can be applied in various places, such as educational institutions or public places, to help reduce the amount of waste that is not properly separated and increase the opportunity to reuse waste.
คณะเทคโนโลยีการเกษตร
This study examines the effects of chemical mutagens, ethyl methane sulfonate (EMS) and colchicine in inducing mutations in Chrysanthemum spp. through tissue culture techniques. In vitro cultures of Chrysanthemum were treated with various concentrations of EMS and colchicine to assess their impact on shoot regeneration and mutation frequency. Results indicated that EMS significantly increased phenotypic variability, leading to enhanced flower color and size, while colchicine treatment effectively induced polyploidy, resulting in plants with greater flower size and overall vigor. Morphological assessments, along with genetic analyses using molecular markers, confirmed the mutations associated with these treatments. The integration of chemical mutagenesis with tissue culture presents a promising approach for developing novel Chrysanthemum varieties with improved ornamental traits.
คณะวิศวกรรมศาสตร์
This project aims to develop a conceptual prototype of a weapon aiming system that simulates an anti-aircraft gun. Utilizing an optical camera, the system detects moving objects and calculates their trajectories in real time. The results are then used to control a motorized laser pointer with two degrees of freedom (DoF) of rotation, enabling it to aim at the predicted position of the target. Our system is built on the Raspberry Pi platform, employing machine vision software. The object motion tracking functionality was developed using the OpenCV library, based on color detection algorithms. Experimental results indicate that the system successfully detects the movement of a tennis ball at a rate of 30 frames per second (fps). The current phase involves designing and integratively testing the mechanical system for precise laser pointer position control. This project exemplifies the integration of knowledge in electronics (computer programming) and mechanical engineering (motor control).