Anuwongpinit, Thanavit

Preferred name

Alternative Name

Anuwongpinit, T.

Main Affiliation

School of Engineering

thanavit.an@kmitl.ac.th

Now showing 1 - 10 of 26

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Learning Process during the COVID-19 Crisis, Selected Topics in Telecommunication Engineering subject, Department of Electronics and Telecommunication Engineering, RUS, Thailand
(2021-01-01)
Archevapanich, Tuanjai
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Khunthawiwone, Park Poom
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Sithiyopasakul, Jiran
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Anuwongpinit, Thanavit
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Purahong, Boonchana
This article presents a learning process during the COVID-19 crisis, used in selected topics of telecommunication engineering subject, department of Electronics and Telecommunication Engineering, Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi. The sample consisted of 19 students, enrolled in the selected topics of telecommunication engineering course by selecting a specific sample group. The researcher presented a learning process during the COVID-19 crisis with the orientation of students for the same understanding and then teaching according to the given process. Finally, there are three aspects of satisfaction with learning processs during the COVID-19crisis assessed. The results showed that in all of the three aspects, having a very good level of students' satisfaction with an arithmetic mean of 4.614 and a standard deviation of 0.46 (\overline{X}=4.614, S.D. = 0.46)
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An improved performance simulated annealing based on evolution strategies for single objective optimization problems
(2020-07-01)
Chutchavong, Vanvisa
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Pumee, Thanapoom
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Thongkrairat, Somsin
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Anuwongpinit, Thanavit
This paper presents solutions for single objective optimization problems with developed algorithm from simulated annealing based on a simple (μ + λ) -ES, It is divided into two algorithms, separated mutation (SM1) and survival mutation (SM2). After that, compared with randomized local search and simulated annealing. The test function is part of the IEEE WCCI 2020 on the topic of CEC-C2 single objective bound constrained optimization. This research has chosen the basic functions in the test such as Bent cigar function, rastrigin function, high conditioned elliptic function, HGBat function, rosenbrock's function, griewank's function, discus function, expanded schaffer's function, weierstrass function, sphere function, natyas function, lévi function N.13, himmelblau's function, and three-hump camel function. These functions are attract attention and competition. A results of SM1 and SM2 can solve single objective optimization problems better than RLS and SA. In high conditioned elliptic, The fitness value of RLS is equal to 3.96E-11, The fitness value of SA is equal to 8.12E-10, The fitness value of SM1 is equal to 5.39E-14 and The fitness value of SM2 is equal to 9.70E-15, It let us show the efficiency of SM2 that can get better results than SM1.
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Design a Monitoring System for Lignite Transferring by Dump Trucks in the Coal Mine Using Deep Learning at the Edge Combined with Cloud Service
(2021-01-01)
Arjchariyaphat, Kritsada
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Anuwongpinit, Thanavit
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Chutchavong, Vanvisa
This research presents the design of a monitoring system for lignite transferring by dump trucks. The hardware developed has a camera to detect and process at the edge level. Two parallel processing models are applied for deep learning classification on the edge systems. The optimization model on the edge devices can be worked with performance and memory limitations in real-Time. In the fields experiments, the three-class output model had high accuracy with low FPS, so it was reduced to one class. In an object-detection design, YoloV4 and EfficientDet-D4 provide 95% and 98% accuracy, respectively, with low FPS. To apply the model optimization using TensorFlow Lite, accuracy is achieved 97% and 96% with higher FPS and better CPU utilization performance that can reduce 30.7% in thermal performance of CPU. The dump truck classification used the mobileNet, EfficientNet, and Xception models. The results show the Xception was the most accurate at 99.0%, demonstrating the model optimization for processing. The results are on the edge that can be effectively deployed into the fields.
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Medical Drone Managing System for Automated External Defibrillator Delivery Service
(2022-04-01)
Purahong, Boonchana
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Anuwongpinit, Thanavit
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Juhong, Aniwat
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Kanjanasurat, Isoon
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Pintaviooj, Chuchart
One of the common causes of a heart attack is fibrillation, a condition that causes an irregular and often abnormally fast heart rate. There is scientific evidence that the survival rate of sudden cardiac arrest patients who are rescued with cardiopulmonary resuscitation (CPR) and with the use of an automated external defibrillator (AED) is significantly increased. Despite the recommendation that automated external defibrillators should be installed in the workplace, along with a proper management system and training for employees on how to use the device, less than 70% of non-residential areas have an AED installed. The situation is even worse in residential areas, with less than 30% having an AED installed. This research concerns the development of a medical drone managing system that can deliver an AED in case of emergency. An application was developed that can be installed on the mobile phone and/or tablet of the patient or the accompanying person. In the event of a heart attack, the patient or the accompanying person can call a medical drone by sending coordinates to the drone station and a notification to medical staff. The drone station administrator can respond by sending the drone, which automatically lands at the patient’s location. After being tested in a simulation situation, the operational field test yielded satisfactory results. The medical drone can land within 1.5 meters of the destination. The designed AED drone can be used not only to deliver AEDs, but also first aid kits and prescribed drugs suitable for medical care. Such a system is especially useful in the current context of the COVID‐19 pandemic.
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Engineering Education Roadmap of the Future Trend of Basic Metaverse based on VR with cooperation between the government and the private sector
(2022-01-01)
Purahong, Boonchana
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Anuwongpinit, Thanavit
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Kanjanasurat, Isoon
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Chansuthirangkool, Manit
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Singto, Kamphon
This article presents an educational roadmap of future trends of Metaverse in VR-based by collaborating between the School of Engineering, King Mongkut's Institute of Technology Ladkrabang (KMITL) with iMAKE company to make a part-time learning plan. The objectives were to measure the achievement and evaluate satisfaction with the development of part-time learning skills in technology on the topic 'Basic Metaverse based on VR'. The sample group was students in a double-degree bachelor's degree program (Dual Degree) between the School of Engineering and the Faculty of Science, KMITL: Bachelor of Engineering (IoT System and Information Engineering) and Bachelor of Science (Industrial Physics) for 16 students by selecting a specific sample group, the engineering education program has a systematic process. The results showed that the achievement of part-time learning skills development in technology on the topic 'Basic Metaverse based on VR' higher than the set criteria 74 %, the overall satisfaction is at a very good level, the mean satisfaction was 4.636 and the sample standard deviation was 0.39.
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Multi-sector Collaboration for Students of different levels to Learn Digital Technology Skills using Competency Assessment from Learning to Create pieces with a 3D printers for Young Innovators Case Study: MogroWittayakom School
(2024-01-01)
Terdyothin, Alongkot
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Archevapanich, Tuanjai
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Chansuthirangkool, Manit
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Inyoo, Pondthip
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Anuwongpinit, Thanavit
This article is the result of collaboration across various associations to create learning spaces for students in compulsory and optional education as well as living skills. This article provides an example of learning digital technology skills through collaboration, starting with the establishment of an innovation room, followed by instructional activities to explore assessment methods for competency in creating works using a 3D printer tailored for young innovators. By employing rubric- based technology tailored to real-world conditions, it aims to fulfill teachers' expectations for student outcomes. This approach helps students understand and apply a rubric to evaluate and improve their own creations. The demographic involves 20 high school students from MogroWittayakhom, selected through purposive sampling. The students participated in a practical performance test, receiving step-by-step training over two days, totaling 12 hours. Upon completing the instruction, students designed and fabricated their projects using Tinkercad software, which were then printed with a 3D printer. The instructor evaluated the students using a rubric-based competency assessment with three scoring levels. The results showed that all 20 participants achieved a high competency level as per the rubric, validating the hypothesis with 100% of the participants meeting the performance criteria.
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Sine-Squared Pulse Approximation for Matched Filter Design Using Generalized Bessel Polynomials and Particle Swarm Optimization
(2022-01-01)
Chutchavong, V.
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Anuwongpinit, T.
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Pumee, T.
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Benjangkaprasert, C.
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Janchitrapongvej, K.
This paper presents the study of mathematical characteristics of generalized Bessel polynomial that can be applied to approximate a sine-squared pulse for designing matched filters in communication systems. The proposed pulse can be designed by using the transfer function, in which the numerator is the five pairs of a transmissions zero pairs, and the generalized Bessel polynomial is used as the denominator. A parameters of generalized Bessel polynomials can be adjusted by particle swarm optimization to find the best parameter value. From the simulation results can be found that a parameter can be adjusted. A proposed pulse is close to the ideal response in mainlobe, and one sidelobe to four sidelobes with stability, which outperformed previous research.
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Image Enhancement and 27 Pretrained Convolutional Neural Network Models for Diabetic Retinopathy Grading
(2023-01-01)
Kanjanasurat, Isoon
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Anuwongpinit, Thanavit
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Purahong, Boonchana
Diabetic retinopathy (DR) affects the retina's blood vessels and causes vision loss. Fundus images are used to diagnose DR, which is a lengthy process because experienced clinicians must accurately diagnose the disease and identify microlesions early to prevent blindness. Computer vision can be used for retinal image classification. The APTOS dataset contains 5990 normal, moderate, mild, proliferate, and severe retinal images. In this study, we proposed a convolutional neural network (CNN) ensemble for DR fundus grading. Each image channel was enhanced by contrast-limited adaptive histogram equalization (CLAHE) and gamma correction and then fed to 27 pretrained CNN models for one-time training to examine the DR grading. The results showed that MobileNet's green channel with the CLAHE technique is sufficiently fast and accurate for disease classification. The grading retinal images had an accuracy of 96.95%, a precision of 96.17%, a sensitivity of 97.80%, an F1 score of 96.98%, and a specificity of 97.75%. In addition, the proposed method improves the speed and robustness of retinal DR grading.
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Design and Implementation of a Hybrid Real-Time Salinity Intrusion Monitoring and Early Warning System for Bang Kachao, Thailand
(2025-07-01)
Seeboonruang, Uma
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Tanachaichoksirikun, Pinit
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Anuwongpinit, Thanavit
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Sirikaew, Uba
Salinity intrusion is a growing threat to freshwater resources, particularly in low-lying coastal and estuarine regions, necessitating the development of effective early warning systems (EWS) to support timely mitigation. Although various water quality monitoring technologies exist, many face challenges related to long-term sustainability, ongoing maintenance, and accessibility for local users. This study introduces a novel hybrid real-time salinity intrusion early warning system that uniquely integrates fixed and portable monitoring technologies with strong community participation—an approach not yet widely applied in comparable urban-adjacent delta regions. Unlike traditional systems, this model emphasizes local ownership, flexible data collection, and system scalability in resource-constrained environments. This study presents a real-time salinity intrusion early warning system for Bang Kachao, Thailand, combining eight fixed monitoring stations and 20 portable salinity measurement devices. The system was developed in response to community needs, with local input guiding both station placement and the design of mobile measurement tools. By integrating fixed stations for continuous, high-resolution data collection with portable devices for flexible, on-demand monitoring, the system achieves comprehensive spatial coverage and adaptability. A core innovation lies in its emphasis on community participation, enabling villagers to actively engage in monitoring and decision-making. The use of IoT-based sensors, Remote Telemetry Units (RTUs), and cloud-based data platforms further enhances system reliability, efficiency, and accessibility. Automated alerts are issued when salinity thresholds are exceeded, supporting timely interventions. Field deployment and testing over a seven-month period confirmed the system’s effectiveness, with fixed stations achieving 90.5% accuracy and portable devices 88.7% accuracy in detecting salinity intrusions. These results underscore the feasibility and value of a hybrid, community-driven monitoring approach for protecting freshwater resources and building local resilience in vulnerable regions.
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Sine-Squared pulse approximation using generalized bessel polynomials
(2019-05-29)
Anuwongpinit, Thanavit
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Chutchavong, Vanvisa
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Janchitrapongvej, Kanok
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Benjangkaprasert, Chawalit
This paper presents the approximation of sine-squared pulse based on the generalized Bessel polynomials. For designing a circuit to synthesize a sine-squared pulse test signal. The generalized Bessel polynomials have more parameter than classical Bessel polynomials that have alpha and beta parameters for adjusting the dominator of the transfer function to approximate the sine-squared pulse that closes to the ideal pulse. The simulation results show that the generalized Bessel polynomial can adjust the approximation response close to the ideal response. The orders of the transfer function are decreased that confirm a better performance than the previous works.
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Anuwongpinit, Thanavit

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