The purpose of this invention is to develop a forest fire prevention agent that has the ability to prevent long-term forest fires, not only to suppress forest fires or prevent forest fires from spreading widely, but to prevent them from starting to catch fire from the beginning. It can prevent forest fires comprehensively and can be prevented for a long time during the peak forest fire period or the dry season, which is about 3-4 months. There are no residues or minimal residues without causing harm to the surrounding environment under the specified standards. Emphasis is placed on the use of raw materials, equipment, and chemicals that can be easily found in Thailand. This includes using the value of production costs as low as possible. This makes it suitable for use in large quantities for spraying and protecting forest areas in forest areas that are prone to fire. Estimated average for pollution caused by forest fires include particulate matter (PM), including PM2.5, PM10, carbon monoxide (CO), carbon dioxide, carbon dioxide, and carbon dioxide, Nitrogendioxide, VOC etc.
ป่าไม้เป็นทรัพยากรธรรมชาติที่มีคุณค่าต่อมนุษย์มากมาย ป่าไม้เป็นแหล่งปัจจัยพื้นฐานสี่ประการที่ทำให้มนุษย์สามารถดำรงชีวิตอยู่ได้ นอกจากนี้ป่าไม้ยังเป็นที่อยู่ของสิ่งมีชีวิตต่างๆรวมถึงสัตว์ป่าและพืชพรรณนานาชนิด ปัญหาไฟป่าเป็นอีกปัจจัยที่ส่งผลให้ทรัพยากรป่าไม้เสื่อมโทรมลงอย่างมาก ส่งผลให้ป่าไม้ไม่สามารถฟื้นตัวได้ทันตามวัฏจักรธรรมชาติ ปัจจุบันประเทศไทยได้สูญเสียพื้นที่ป่าไปเป็นจำนวนมากกว่า 1000000 ไร่ในสิบปีหลังสุด และผลกระทบจากไฟป่าทำให้เกิดปัญหาหมอกควันกระจายท้่วไปในบริเวณภาคเหนือ ภาคกลาง และตะวันออกเฉียงเหนือของประเทศ ทำให้ประชาชนจำนวนมากประสบปัญหาโรคระบบทางเดินหายใจ นวัตกรรมนี้จึงถูกสร้างขึ้นเพื่อต้องการลดปัญหาไฟป่าและปกป้องคลุมครองพื้นที่ป่าของประเทศ
คณะวิทยาศาสตร์
Otitis Media is an infection of the middle ear that can occur in individuals of all ages. Diagnosis typically involves analyzing images taken with an otoscope by specialized physicians, which relies heavily on medical experience to expedite the process. This research introduces computer vision technology to assist in the preliminary diagnosis, aiding expert decision-making. By utilizing deep learning techniques and convolutional neural networks, specifically the YOLOv8 and Inception v3 architectures, the study aims to classify the disease and its five characteristics used by physicians: color, transparency, fluid, retraction, and perforation. Additionally, image segmentation and classification methods were employed to analyze and predict the types of Otitis Media, which are categorized into four types: Otitis Media with Effusion, Acute Otitis Media with Effusion, Perforation, and Normal. Experimental results indicate that the classification model performs moderately well in directly classifying Otitis Media, with an accuracy of 65.7%, a recall of 65.7%, and a precision of 67.6%. Moreover, the model provides the best results for classifying the perforation characteristic, with an accuracy of 91.8%, a recall of 91.8%, and a precision of 92.1%. In contrast, the classification model that incorporates image segmentation techniques achieved the best overall performance, with an mAP50-95 of 79.63%, a recall of 100%, and a precision of 99.8%. However, this model has not yet been tested for classifying the different types of Otitis Media.
คณะเทคโนโลยีการเกษตร
The innovation of the vertical aquaponics system for rearing golden apple snails integrating with vegetable cultivation by using substrates to water treatment. The system aims to maximize the use of vertical space, save water, and produce safe vegetables for consumption or commercial purposes, and to support living things. The golden apple snail excretes wastes/leftover food scraps that are filtered on the substrates used for water treatment. Meanwhile, natural bacteria help change these wastes into nutrients that plants can use. Therefore, the system is environmentally friendly.
วิทยาลัยอุตสาหกรรมการบินนานาชาติ
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.