Anuwongpinit, Thanavit
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Anuwongpinit, Thanavit
Alternative Name
Anuwongpinit, T.
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Email
thanavit.an@kmitl.ac.th
21 results
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Item type:Publication, Sine-Squared pulse approximation using generalized bessel polynomials(2019-05-29); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identity checking system by visible light(2014-01-01); ; Dumrong, JirattawutA new identity checking system by visible light can fulfill some limitations of QRCode and RFID technology wherewith this system can check further distance. This paper is a model to be applied to other areas. In this system, the communication between LED Blinking and camera consists of transmitter and receiver. Transmitter is a microcontroller to control LED for blinking pattern one pattern for one identity of object and save in database. Receiver consists of camera to detect LED blinking by image processing. When detecting LED blinking receive code for identity of object then get code to check identity with database. This system can be applied to various such as security, advertising, identify system, and etc. © 2014 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, IoT-based Water Quality Monitoring Station and Forecasting System with Machine Learning(2025-01-01); This paper presents an IoT-based water quality monitoring and forecasting system designed for real-time and continuous assessment of water resources. The system integrates Siemens SIMATIC IOT2050 as an Industrial IoT Gateway, which collects data from sensors measuring conductivity, pH, dissolved oxygen, and temperature using RS485 Modbus RTU communication. Data processing occurs at the edge using Node-RED and is transmitted to AWS Cloud via MQTT for storage and visualization on a dashboard. Predictive analysis employs machine learning models, including XGBoost with Optuna parameter tuning and Long Short-Term Memory (LSTM) networks, for water quality forecasting. Results indicate superior performance of LSTM for most parameters, while XGBoost excels in pH prediction. This system demonstrates scalability, reliability, and potential for enhanced water quality management in diverse environments. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Implementation of ECG portable device for real-time signal monitoring(2017-11-24); ; ; Aoyama, H.In this paper presents a system for heart rate signal analysis in ECG (Electrocardiography) format using STM32f7 board. Electrode is used for recording the signal with stick on body in lead 2 orientations. Signal processing method are used upper average, slope and interval checking algorithm to process ECG signal in real-time. In experiment, to acquire a frequency of heart beat and display ECG signal and heart rate on STM32f7 board compare with wearable device that result have error rate less than 1%. This system is portable to use and sufficient battery for recording signal to analyze and monitor throughout the day. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Learning Process during the COVID-19 Crisis, Selected Topics in Telecommunication Engineering subject, Department of Electronics and Telecommunication Engineering, RUS, Thailand(2021-01-01); 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) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hybrid learning during the COVID-19 pandemic of engineering students at KMITL, Thailand(2021-01-01); ; Archevapanich, TuanjaiThis article presents the hybrid learning model during the COVID-19 for students of Agro-Industrial Systems Engineering who enrolled in the course embedded system, course code 01386304, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang for 29 students by selecting a specific sample group. The researcher presented a hybrid learning model during the COVID-19, where students were orientated for the same understanding and followed by teaching as active learning formed project-based learning. Finally, we assessed five aspects of hybrid learning satisfaction during the COVID-19. The evaluation results revealed that the students' satisfaction was at a good level and their arithmetic mean was 4.206 and the standard deviation is equal to 0.74 (X = 4.206, S.D. = 0.74) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Approximation of sine-squared pulse with additional transmission zero using bessel polynomials(2017-11-24); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Development of IoT portable device for saline water monitoring in Bang Kachao Area of Thailand(2023-01-01); ; This research developed a portable water salinity measurement device using internet of things technology to support farmers in Bang Kachao area in Samut Prakan province, Thailand, to select quality water for cultivation and consumption. The system hardware consists of a microcontroller ESP32 with a GPS module and an electrical conductivity sensor with an analog-to-digital conversion module for saline water measurement. This device can connect to an internet system via a Wi-Fi network and MQTT protocol to transmit the data of saline water value and measuring location to the cloud system. In the cloud system, the node-red system software is installed as a data gateway for device interfacing. In addition, a node-red dashboard is used to collect data from a portable device and previously installed water quality monitoring station for visualizing a portable device location and saline water data. This dashboard is a web page that allows people to monitor the water situation in the area that is suitable to use. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An improved performance simulated annealing based on evolution strategies for single objective optimization problems(2020-07-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 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); 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.