Sirisuk, Phaophak

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Sirisuk, Phaophak
Alternative Name
Sirisuk, P.
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Email
phaophak.si@kmitl.ac.th

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    Simple and Effective Design Concept for Constructing In-Situ Soil Dielectric Property Sensor with Dual Low-Cost COTS Microwave Modules
    (2022-01-01)
    Leekul, Prapan
    ;
    Mgawe, Bonny
    ;
    Kazema, Twahir
    ;
    Dao, Hoang Nam
    ;
    Sirisuk, Phaophak
    This paper presents a compact sensor system for estimating the dielectric properties of materials based on commercial, off-the-shelf (COTS) modules. The dielectric constant and conductivity of a material under test can be determined from the measurement of the microwave reflected from the material. By using dual microwave sensor modules with a slightly different radio frequency, an identical intermediate frequency at the mixers of the modules was obtained. The intermediate frequency was chosen such that the associated microwave and data processing components could be easily obtainable, leading to a practical realization of the sensor system. Synchronization of the two microwave sensor modules was achieved using electronically controlled relays that simultaneously switch on the power supplies of both modules. Two microcontrollers were used to capture the corresponding signals. The sensor was designed at a 10 GHz band for measuring reflected waves from various kinds of materials, especially soils with different moisture and fertilizer contents. The evaluation results indicate a good agreement between the measured results from the proposed sensor and the ones from a network analyzer, verifying that the proposed sensor is fully functional for monitoring variation in the dielectric properties of materials, including soil. The average sensitivity for the dielectric constant of moist soil is 0.26/% moisture content and the error rate for dielectric constant measurement is 4.83%.
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    Exploitation of IoTs for PMU in Tethered Drone
    (2021-04-01)
    Wiangtong, Theerayod
    ;
    Pookaiyaudom, Panavy
    ;
    Sirisuk, Phaophak
    This paper presents the implementation of IoT (Internet of Things) for monitoring and control in the tethered drone PMU (Power Management Unit) system. Traditionally, power source of a drone is from battery which causes the tradeoff between weight and flight time. To overcome this limitation, stationary tethered drones consume energy from a ground energy source thru light weighted power cords. Tethered drones' benefits are ideally suited for military uses such as border security and surveillance system, where day-night surveillance capabilities are crucial to monitoring perimeters. It can also be used for tactical communication, fast-deployed relay stations. Since a long operation time, monitoring and control power onboard becomes necessary. Using extra cords for communication will increase the airborne weight. This paper presents the exploitation of wireless IoT system for the tethered drone PMU system. It consists of the PMU-ground constantly delivering 4000W power to PMU-air for BLDC motors also various payloads. With additional IoT including Raspberry Pi, NodeMCUs and sensors, users at ground station can monitor voltage and current values in real-time, also can control MOSFET switches connected with loads onboard via PMU touch screen monitor or smart devices.
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    Deployment of Machine Vision Platform for Checking Spot Welds on Metal Strap Belts
    (2023-01-01)
    Wiangtong, Theerayod
    ;
    Wongkharn, Siripong
    ;
    Sirisuk, Phaophak
    This paper presents a designed platform used to detect the perfection and number of spot welds on the strap belt of metal sheet coils. Three different approaches include image morphology, thresholding and Hough transform are compared. The results from real implementation show that using the adaptive threshold values in image thresholding approach instead of fixed value can increase the system accuracy from 69% to 88%. Also, to find the pad, the comparison of using Haar cascade machine learning and YOLO deep learning is described.
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    Single-Frequency Sensor for Thick Rind Fruit Quality Assessment
    (2025-01-01)
    Leekul, Prapan
    ;
    Dao, Hoang Nam
    ;
    Sirisuk, Phaophak
    ;
    Phongcharoenpanich, Chuwong
    ;
    Krairiksh, Monai
    A sensor capable of estimating the dielectric properties of the outer and inner materials of a concentric dielectric sphere is essential for assessing the quality of thick rind fruits. This article presents a sensor design that operates at a single frequency and is straightforward. The underlying principle of the sensor involves transmitting a microwave signal to a concentric dielectric sphere with two power levels. The low-power signal yields backscattered waves from the outer sphere, while the high-power signal provides information about backscattered waves from both the outer and inner spheres. The sensor, which operates at a frequency of 10 GHz using cost-effective components, effectively detects defects in spherical-shaped fruits, e.g., mangosteens. The accuracy in classifying translucent mangosteens from normal mangosteens is 92.5%, enabling effective classification of defected fruits.
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    Dielectric Constant Determination using Dual Doppler Modules
    (2021-01-01)
    Leekul, Prapan
    ;
    Mgawe, Bonny
    ;
    Kazema, Twahir
    ;
    Dao, Hoang Nam
    ;
    Sirisuk, Phaophak
    This paper presents a dielectric constant determination system based on dual Doppler modules. The key principle is to assign two slightly different radio frequencies to each module. It is demonstrated that dielectric constant of a material under test can be determined from the measured reflection coefficient. The concept was validated at 10 GHz band by measuring reflected waves from various materials including soil with different moisture content. Results illustrated good agreement between measured results from the proposed sensor as compared with the literatures. The results confirm that the proposed technique is applicable for monitoring soil characteristics.
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    A Low-cost Autonomous Lawn Mower with AI-Based Obstacle Avoidance and GPS Guidance System
    (2025-07-01)
    Kosri, Thanapon
    ;
    Seekhamharn, Tossawat
    ;
    Phoonsrichaiyasit, Phasawut
    ;
    Khungpo, Poowadon
    ;
    Sirisuk, Phaophak
    This paper presents a cost-effective robotic system capable of manual control via RF remote and autonomous navigation using GPS-based information. The system employs artificial intelligence to dynamically classify and avoid non-grass obstacles, ensuring safe operation in real environments. The prototype integrates affordable hardware including Arduino board, sensors, actuators and Raspberry Pi with lightweight algorithms to balance performance and cost. Experimental validation confirms its ability to follow predefined paths with ±1.5 meters deviation in open area and 90% obstacle avoidance success rate. With a total hardware cost under $200, this prototype highlights feasibility for larger-scale implementation.