Layla, the hotel robot, is responsible for carrying guests’ luggage and guiding them to their accommodations. It is equipped with an internal map of the hotel, allowing it to navigate various locations efficiently. Additionally, it features an AI-powered system that enables interactive conversations in three major languages: Thai, English, and Chinese.
เนื่องจากปัญหาการขาดแคลนพนักงานโรงแรมในปัจจุบัน พนักงานจึงต้องทำหน้าที่หลายอย่างในเวลาเดียวกัน ทำให้ลูกค้าอาจต้องรอคิวนาน ดังนั้นเพื่อเพิ่มประสิทธิภาพการทำงานให้สะดวกและรวดเร็วยิ่งขึ้น จึงสร้างนวัตกรรมชิ้นนี้มาเพื่อช่วยลดภาระหน้าที่ของพนักงาน เช่น Bellboy, Concierge และ Receptionist เป็นต้น
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.
คณะเทคโนโลยีการเกษตร
The extreme weathers according to PM 2.5 is a global problem with out any borders. This pollutant can directly attack human health. The objective of the study was aimed to develop medicinal plant essential oil emulsions in order to use to decrease PM 2.5 based on chemical characterization of water-soluble anions and cations. A mount of 31 medicinal plant essential oil emulsions were prepared and then initially careened and tested for their efficiency in reducing PM 2.5 under test chamber by spraying method. It was found that spraying for 1 hr with kaffir lime essential oil emulsion at 0.025% concentration could reduce PM 2.5 obtained from engine exhaust pipe effectively when PM 2.5 of 24.7 µg/m3 was detected within 6 hrs, followed by kaffir lime essential oil emulsion at 0.05% and Eucalyptus essential oil emulsion at 0.05% and 0.025% concentration resulting in 27.3, 30.0 and 95.3 µg/m3, respectively. Whereas, water (blank) and control group (water and carboxymethylcellulose, CMC 0.2%) showed high revels of PM 2.5 with 126.4 and 157.3 µg/m3, respectively. This kaffir lime essential oil emulsion at 0.025% concentration showed 3-6 time decline of PM 2.5 upward 2 hrs compared with control group. Field experiment was performed at 3 Bangkok parks, namely, Suantaweewanarom, Suanbankharepirom and Suanthonbureerom. There were many factors affecting the decline of PM 2.5 caused by this essential oil emulsion, particularly, the windy as well as temperature and humidity. PM 2.5 level tended to be decreased after the beginning of spraying. In general, PM 2.5 levels appeared at those 3 parks were decreased rapidly within 1 hr as by average of 21.8 (7.7-27.3) µg/m3, Whereas, decline of only 6.4 (5.0-8.0) µg/m3 was observed in control (water). Incase of calm wind, (10-20 km/hr) this plant essential oil emulsion could even reduce PM 2.5 at 37.0-44.0 µg/m3 and reached to 13.5-16.5 µg/m3 within 3 hrs. As high level of PM 2.5 as 98.0-101.0 µg/m3 , it could reduce PM 2.5 to be an average of 23.0-26.5 µg/m3 within 3 hrs, Whereas, the use of water performed low capacity of PM 2.5 reduction found with only 31.0-40.0 µg/m3. However, windy condition (15-35 km/hr), the efficacy of this essential oil emulsion seem to be lower but tended to work better than using water alone
คณะอุตสาหกรรมอาหาร
Banana Blossom Chips is a healthy snack rich in dietary fiber, antioxidants, and plant-based protein. It is a result of combining local Thai ingredients: banana blossoms, which are high in dietary fiber and antioxidants, chickpea flour, a source of plant-based protein, and red jasmine brown rice, which has a low GI value and high antioxidants. It is processed to create crispiness and a unique shape, reduces fat, is gluten-free, and helps maintain nutritional value. Therefore, it is a new alternative for health-conscious consumers and adds value to Thai agricultural products.