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Industrial IoT Edge Computing Platform for Real-Time Monitoring
(2022-01-01)
Glomglome, Sorayut
;
Damrongphokaphan, Watanyou
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Phormraksa, Kittisak
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Witchuvanit, Korntawat
This research's goal is to develop an industrial IoT edge computing platform for Industrial IoT 4.0 that are currently in the process of transitioning from legacy systems to adopting IoT system. Due to connecting and collecting data from each machine part is still a problem of transition from the old system, this is the origin of this research. The system consists of a Remote Terminal Unit (RTU) which collect data from machines with sensors and an Edge Computing Device used to collect data from RTUs via MQTT Protocol. The system also has an IoT platform that processes incoming data for storing in the database and displays on the Web Application in real time and in retrospect and can also alert to Line Notify according to the conditions predefined by the user. Based on the benchmark test, an edge computing device can concurrently handle RTU connections up to 800 connections.
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Blockchain and Smart Contract Payment for Electric Vehicle Charging
(2020-06-01)
Chanthong, Natthanan
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Ruangsakorn, Thitiwat
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Glomglome, Sorayut
Our research aims to study, design and build the electronic payment system for electric vehicle (EV) charging using blockchain and smart contract technologies. Both technologies are used to control and manage payments and to decentralize the payment system, so the devices can automatically pay each other. In addition, our system lessens the inadequate of charging station for EV when travel in the long distance because our proposed let EV owners who also have charging facilities at their homes share their facilities and automatically get paid. Blockchain node is set up in charging station and is controlled by the application for EV owners. The application can show the charging information and control the payment and charging process automatically. For EV part, we simulated the data transmission between charging station and EV.
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Usage-based Insurance Using IoT Platform
(2018-08-21)
Lertpunyavuttikul, Puntavut
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Chuenprasertsuk, Pinyarat
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Glomglome, Sorayut
The premium of car insurance is normally calculated based on statistics i. e. car and driver information. Drivers who have the same age range pay equivalent premiums regardless of their driving behavior. We propose the usage-based insurance (UBI) system that takes driver behaviors into account. Locations and vehicle speed obtained from smartphones while driving are sent to the Internet of things platform for live monitoring and data storing. Stored data are later used to calculate driver behaviors i.e. annual distance and the frequency of harsh braking. The premium discount of 30% maximum will be awarded to drivers who have annual distance and the number of harsh braking less than predetermined thresholds.
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Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters
(2018-01-01)
Chitsobhuk, Orachat
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Kasemsiri, Watjanapong
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Glomglome, Sorayut
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Lapamonpinyo, Pipatphon
In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.
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Optical spin generated by a soliton pulse in an adddrop filter for optoelectronic and spintronic use
(2012-07-01)
Glomglome, Sorayut
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Srithanachai, Itsara
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Teeka, Chat
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Mitatha, Somsak
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Niemcharoen, Surasak
A new concept of an optical spin generation using bright and dark soliton conversion behaviors within a modified optical adddrop filter known as PANDA ring resonator is proposed. The orthogonal solitons can be formed within the system and detected simultaneously at the output ports. Under the resonant condition, the dark and bright soliton pair corresponding to the left-hand and right-hand rotating solitons (photons) can be generated. When a soliton is absorbed by an object, an angular momentum of either or - is imparted to the object, in which two possible spin states known as optoelectronic(soliton) spins are exhibited. Furthermore, an array of soliton spins, i.e. particles can be generated and detected by the proposed system, which can be used to form large scale spin generation. © 2011 Elsevier Ltd. All rights reserved.

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