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Machine Learning-Optimized Dual-Band LoRa Elliptical Patch Antenna in LoRa Communication System for Waterborne Microplastic Detection
(2026-02-01)
Romputtal, Adisak
;
Phongcharoenpanich, Chuwong
This research proposes a dual-band LoRa elliptical patch antenna for the LoRa communication system to detect waterborne microplastics. The proposed LoRa communication system comprises a LoRa sensor node board and an IoT-LoRa gateway board. The LoRa sensor node board is used to capture microplastic images using a digital camera and collect analog signal data from an 8 × 8 photodiode array which detects the reflected light from microplastic fragments. The data are transmitted using a LoRa elliptical patch antenna in the sensor node board, operating at 0.915 GHz for long-range data transfer. The IoT-LoRa gateway board is used to forward data received from the LoRa sensor node board to a cloud server via the internet, and the stored data are accessible and viewable via a smartphone. In this research, the antenna design is optimized by using machine learning (ML) algorithms, unlike conventional antenna design methods which rely on the manual and iterative process. The ML-optimized dual-band LoRa elliptical patch antenna covers the LoRa, UHF RFID, and ZigBee frequency bands, with an omnidirectional radiation pattern. The measured impedance bandwidths (IBWs) are 8.93% (0.868–0.949 GHz) and 12.69% (2.36–2.68 GHz) for the lower and upper frequency bands, respectively, with the corresponding impedance matching (|S<inf>11</inf>|) of –23.02 dB at 0.907 GHz and −27.27 dB at 2.52 GHz. Two ML-optimized LoRa elliptical patch antennas are subsequently integrated into the LoRa communication system, that is, one on the LoRa sensor node board and other on the IoT-LoRa gateway board. Furthermore, prior to indoor and outdoor experiments, the ML-driven waterborne microplastic detection scheme with the LoRa communication system is trained and tested using camera-captured images and analog signal-converted images from the photodiode array. The ML-driven microplastic detection scheme can classify different types of microplastics in water, achieving an accuracy of 100% for all types of microplastics. The detection scheme is also capable of identifying the presence of microplastics in water, achieving an overall accuracy of 98.5%. The originality of this work lies in the use of ML algorithm to optimize the antenna design and to streamline identification and detection of microplastics in water.
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T-Slot Antennas-Embedded ZigBee Wireless Sensor Network System for IoT-Enabled Monitoring and Control Systems
(2023-12-01)
Romputtal, Adisak
;
Phongcharoenpanich, Chuwong
This research proposes a 2.4 GHz T-slot antennas-embedded ZigBee wireless sensor network system, consisting of an Internet of Things (IoT) gateway board and a sensor node board, for IoT applications. Simulations were first carried out to optimize the parameters for the T-shaped slot patch antenna. The prototypes of the IoT gateway and sensor node boards were subsequently fabricated and measurements undertaken. The measured impedance matching (|S11|), bandwidth, and gain of the proposed ZigBee sensor network system were -18 dB, 15.38%, and 1.722 dBi, respectively. Furthermore, the ZigBee IoT-based monitoring and control schemes based on the ZigBee wireless sensor network system were set up and experiments carried out in an enclosed area for the monitoring scheme and in an open area for the control scheme. The experimental results revealed that the proposed IoT-enabled 2.4 GHz ZigBee sensor network system with embedded T-slot patch antennas could efficiently be utilized in IoT-based monitoring and control systems. In essence, the novelty of this research lies in the integration of the IoT and ZigBee sensor network technologies to store data in a cloud server in a real-time fashion, as opposed to in the microcontroller memory which is common in conventional ZigBee systems. In addition, the data stored in the cloud server are retrievable and viewable via the Blynk application on smartphone, rendering the proposed 2.4 GHz T-slot antennas-embedded ZigBee wireless sensor network system operationally suitable for IoT-based monitoring and control systems.
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IoT-Linked Integrated NFC and Dual Band UHF/2.45 GHz RFID Reader Antenna Scheme
(2019-01-01)
Romputtal, Adisak
;
Phongcharoenpanich, Chuwong
This research proposes a system board of integrated antenna scheme of near-field communication (NFC) and dual band ultra-high frequency (UHF, 920-925 MHz)/2.45 GHz radio frequency identification (RFID) reader antennas for Internet of Things (IoT) applications. The integrated antenna scheme is capable of simultaneous execution of NFC and UHF RFID functions whereby the NFC and UHF RFID modules, which are serially connected to a microcontroller with Wi-Fi module (NodeMCU), read the universal identification (UID) of NFC and UHF RFID tags. The data are then forwarded to a cloud server via Internet of Things (IoT) and are viewable on smartphones using Blynk mobile application via IoT. To realize the optimal antenna design, simulations were carried out using CST Studio Suite. Prototype antennas were subsequently fabricated and integrated into the system board for IoT-linked near- and far-field communication. The simulation and measured results are in good agreement. The NFC reader antenna resonates at 13.56 MHz, and the dual band UHF/2.45 GHz RFID reader antenna achieves the 920-925 MHz and microwave (MW) bands with high isolation. The novelty of the proposed integrated NFC and UHF RFID antenna scheme lies in the use of cloud technology to store real-time and archival data, in place of traditional servers. The integrated antenna scheme could achieve the NFC, UHF, and MW frequency bands, rendering it ideal for IoT applications.
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Frequency reconfigurable multiband antenna with embedded biasing network
(2017-08-16)
Romputtal, Adisak
;
Phongcharoenpanich, Chuwong
This research presents a frequency reconfigurable antenna scheme for wireless communications [worldwide interoperability for microwave access (WiMAX), mobile WiMAX and wireless local area network], in which a PIN diode is utilised for the discrete tuning and a varactor diode for the subsequent fine-tuning. A microcontroller-controlled embedded biasing network (EBN) is integrated into the antenna to regulate the PIN and varactor diodes for the simultaneous wideband and multiband operations. Specifically, two clusters constitute the proposed antenna scheme: the antenna and EBN clusters. The simulation and experimental results revealed that the antenna scheme could achieve the multiple frequency bands in the range of 2.4-5.8 GHz, with negligible changes in the antenna physical dimensions. Due to its compactness, the antenna scheme is ideal for small modern wireless communications devices.
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Characteristics of a multi-slotted PIFA for UHF RFID tag
(2015-01-26)
Romputtal, Adisak
;
Luadang, Bancha
;
Phongcharoenpanich, Chuwong
This paper presents a low profile planar inverted-F antenna (PIFA) for the sensing tag of UHF RFID applications. The proposed antenna that is optimized by using the multi-slotted PIFA in order to overcome the shortcoming of a narrow bandwidth of a typical PIFA can be increased of 9.2%. The |S11| of the simulated and measured results can be operated in the UHF RFID system in Thailand, which covers the frequency bands from 920 to 925 MHz. Furthermore, the radiation pattern is omnidirectional at 922.5 MHz. Therefore, slotted PIFA can be employed with a UHF RFID sensing tag.

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