Discover the ultimate innovations of the future developed by Thai researchers! Meet the latest technology from KMITL that will transform our way of life and industry.
คณะวิทยาศาสตร์
With the urgent need for rapid screening of Aflatoxin B1 (AFB1) due to its association with increased liver cirrhosis and hepatocellular carcinoma cases from contaminated agricultural foods, we propose a novel electrochemical aptasensor. This aptasensor is based on trimetallic nanoparticles AuPt-Ru supported by reduced graphene oxide (AuPt-Ru/RGO) modified on a low-cost and disposable goldleaf electrode (GLEAuPt-Ru/RGO) for detection of AFB1. The trimetallic nanoparticle AuPt-Ru was synthesized using an ultrasonic-driven chemical reduction method. The synthesized AuPt-Ru exhibited a waxberry-like appearance, with AuPt core-shell structure and ruthenium dispersed over the particles. The average particle size was 57.35 ± 8.24 nm. The AuPt-Ru was integrated into RGO sheets (inner diameter of 0.5 to 1.6 µm) in order to enhance electron transfer efficiency and increase the specific immobilizing surface area of the thiol-5’-terminated modified aptamer (Apt) to target AFB1. With a large electrochemical surface area and low electrochemical impedance, GLEAuPt-Ru/RGO displays ultra-high sensitivity for AFB1 detection. Differential pulse voltammetry (DPV) measurements revealed a linear range for AFB1 detection range from 0.3 to 30.0 pg mL-1 (R2 = 0.9972), with a limit of detection (LOD, S/N = 3) and a limit of quantification (LOQ, S/N = 10) of 0.009 pg mL-1 and 0.031 pg mL-1, respectively. The developed aptasensor also demonstrated excellent accuracy in real agricultural products, including dried red chili, garlic, peanut, pepper, and Thai jasmine rice, achieving recovery rates between 94.6 and 107.9%. The fabricated aptamer-based GLEAuPt-Ru/RGO performance is comparable to that of a modified commercial electrode, which has great potential application prospects for detecting AFB1 in agricultural products.
คณะอุตสาหกรรมอาหาร
This study aimed to develop a formula and production process for snacks made from germinated brown rice flour and banana flour using the extrusion process. The results indicated that both germinated brown rice flour and banana flour could be effectively used as the main raw materials for snack production via extrusion. The proportion of flour in the formula and production conditions, such as moisture content of the raw materials, barrel temperature, and screw speed, significantly influenced the nutritional value, bioactive compound levels, and antioxidant activity of the final products.
คณะวิทยาศาสตร์
This project presents the development of an automatic recycling machine for plastic bottles and cans, utilizing Machine Learning for packaging classification through image processing, integrated with smart sensor systems for quality inspection and operation control. The system connects to a Web Application for real-time monitoring and control. Once the packaging type is verified, the system automatically calculates the refund value and processes payment through e-wallet or issues cash vouchers. The system can be installed in public spaces to promote waste segregation at source, reduce contamination, and increase recycling efficiency. It also provides financial incentives to encourage public participation in waste management. This project demonstrates the potential of combining Machine Learning and smart sensor systems in developing accurate, convenient, and sustainable waste management solutions.
คณะวิทยาศาสตร์
A smartphone-based colorimetric sensor for quantitative detection of pyridoxine (Vitamin B6, VB-6) in functional drink samples has been realized by developing double layer hydrogel. Electrostatic interaction initiates the cross-linking and produces double layer hydrogel.
คณะวิทยาศาสตร์
This research will begin with a review of literature and related studies to examine existing technologies and methods for hand gesture recognition and their applications in controlling electronic devices such as drones, robots, and gaming systems. Subsequently, a hand gesture recognition system will be designed and developed using machine learning and computer vision techniques, with a focus on creating an algorithm that operates quickly and accurately, making it suitable for real-time control. The developed system will be tested and refined using various simulated scenarios to evaluate its efficiency and accuracy in diverse environments. Additionally, a user-friendly interface will be developed to ensure accessibility for all user groups. The research will also incorporate qualitative studies to gather feedback from both novice users and experts, which will contribute to further system improvements, ensuring it effectively meets user needs. Ultimately, the findings of this research will lead to the development of a functional prototype for gesture-based control, which can be applied in industries and entertainment. This will contribute to advancements in innovation and new technologies in the future.
คณะวิทยาศาสตร์
Currently, climate change and human activities are causing rapid deterioration of coral reefs worldwide. Monitoring coral health is essential for marine ecosystem conservation. This project focuses on developing an Artificial Intelligence (AI) model to classify coral health into four categories: Healthy, Bleached, Pale, and Dead using Deep Learning techniques. With pre-trained convolutional neural network (CNN) for image classification. To improve accuracy and mitigate overfitting, 5-fold Cross-Validation is employed during training, and the best-performing model is saved. The results of this project can be applied to monitor coral reef conditions and assist marine scientists in analyzing coral health more efficiently and accurately. This contributes to better conservation planning for marine ecosystems in the future.
วิทยาลัยนวัตกรรมการผลิตขั้นสูง
Ultrasonic cleaning tank is a machine that many factories widely used to clean objects. At one factory, a problem occurred in the cleaning process, resulting in the factory not being able to clean objects, but cracks also appeared on some objects. It was anticipated that these were caused by uneven acoustics pressure distribution which resulted in unsuitable cavitation This directly affected cleaning performance within the tank. In order to improve the tank's efficacy, in this research, we use Harmonic Response Analysis in ANSYS simulate simulate the occurrence of acoustic pressure in the tank to find the appropriate conditions of factors affected the intensity and the distribution pattern of acoustic pressure in ultrasonic tank, including the position of object, power, ultrasonic frequency and a suitable type and placing position of the transducer for the tank. Reliability of the simulate results was validate by the actual result from the foil corrosion test and the ultrasonic power probe. We found that objects receive different pattern of corrosion at each location. When temperature increasing the intensity of cavitation was increased. When we increase the ultrasonic frequency, acoustic pressure that is evenly dispersed throughout the tank.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
This study aims to identify the toothbrush appearance factors that affect baby boomers purchasing decisions. The research divide into three stages: The first stage is to classify the toothbrush appearance factors through a review of literature, research, and examining toothbrushes currently available on the market, summarizing them as appearance factors. The second stage is to summarize the results of the toothbrush appearance factors to create a multiple-choice questionnaire in three dimensions: purchasing decisions, aesthetics, and functionality. Collecting data from a group of 30 Baby Boomers aged 57-75 years old. The last stage is to summarize the three dimensions of appearance factors affecting baby boomers' toothbrush purchasing decisions and report as percentages and rank them. The research findings indicate that the most significant toothbrush appearance factor is a "Curved handle," accounting for 80%, followed by “Multi-level bristles” at 70%, a "Rubber thumb rest" at 53.3%, "Handle divided into more than two parts" at 50%, and “Offset shape” at 40%, respectively. In terms of the reason for purchasing decision based on various factors are as follows: the curved handle and offset shape give a sense of purchase with its aesthetic, While the selection of multi-level bristles, the Rubber thumb rest, and the handle divided into more than two parts due to functionality.
คณะวิทยาศาสตร์
In today’s rapidly expanding e-commerce environment, the massive volume of product reviews makes it crucial to summarize user opinions in a way that is both comprehensible and practically applicable. This research presents a system for analyzing product reviews using Aspect-Based Sentiment Analysis (ABSA), a Natural Language Processing (NLP) technique that identifies key aspects of a review (such as shipping, product quality, and packaging) and evaluates the sentiment (positive, negative, or neutral) associated with each aspect, allowing both consumers and merchants to gain more efficient access to in-depth insights. This project focuses on developing AI for Thai-language ABSA by utilizing WangchanBERTa, a model trained on Thai data, and comparing it with various standard approaches such as TF-IDF + Logistic Regression, Word2Vec + BiLSTM, and Multilingual BERT (mBERT/XLM-R) to assess their performance in terms of accuracy, speed, and resource usage. Additionally, a dashboard visualization is provided to help users quickly grasp review trends. The expected outcome is to create an AI tool that can be practically employed in the e-commerce industry, enabling consumers to make easier purchasing decisions and assisting merchants in effectively improving their products and services.