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Growth stage detection for food consumption management in smart cricket farming using a deep learning technique
(2025-11-01)
Nutnoi, Nitipoom
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Yindeesuk, Witoon
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Kamoldilok, Surachart
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Srinuanjan, Keerayoot
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Limsuwan, Pichet
This research proposed a novel method for tracking and predicting the growth stages of two-spotted crickets, reared in a temperature-controlled box at different growth stages using the YOLOv5s model. The images of crickets feeding inside the rearing box were taken with an infrared camera above the feeding point every hour. Images of the cricket were used to train a YOLOv5s model to detect crickets for each growth stage in the rearing box. The experimental results showed that the trained deep learning had an average accuracy of 95.7%. The relationship between the ratio of crickets at each growth stage throughout the 45-day rearing period was plotted and discussed. The results also showed a clear relationship between the amount of food consumed by crickets per day and their growth stage, which could be useful for appropriately managing food consumption according to the growth stage of crickets.
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Comparison of Interferometry Applications: Michelson vs. Sagnac Interferometers
(2025-05-14)
Wannasri, Thanawat
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Yindeesuk, Witoon
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Buranasiri, Prathan
An interferometer is a crucial instrument for collecting information on interference patterns, widely used in both scientific and industrial applications. This paper was focused on comparing the interferometric applications of the Michelson and Sagnac interferometers. The Michelson interferometer, characterized by its double-path setup, and the Sagnac interferometer, which operates on a common-path principle, were analyzed. Experiments were conducted to capture interference patterns of different samples using both interferometers. In the first experiment, the image fringes of the alphabet characters (K, M, I, T, and L) were captured, while in the second, fingerprint patterns were captured. The results showed that both interferometers produced similar fringes for the alphabet characters, although the Sagnac interferometer exhibited a higher circular frequency. In the fingerprint experiment, the Michelson interferometer produced linear fringes. This study highlights the distinct fringe patterns generated by each interferometer when different samples are analyzed, providing valuable insights into their diverse applications.
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Speckle imaging of graphene oxide and reduced graphene oxide
(2025-01-01)
Sirikarntayuprakit, Pakkanhan
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Yindeesuk, Witoon
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Buranasiri, Prathan
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Rattanasirawit, Chinnapat
Laser speckle imaging is a non-contact technique for analyzing materials' surface roughness and scattering characteristics. This study investigated the speckle patterns of graphene oxide (GO) in sheet form and reduced graphene oxide (rGO) in powder form under coherent laser illumination. The intensity distributions were recorded using a CMOS camera and analyzed statistically to determine key surface parameters, including speckle contrast and roughness. The results show that GO produces a finer, more uniform speckle pattern with lower contrast and roughness values than rGO, which exhibits coarser and more irregular patterns. These differences reflect the distinct structural characteristics of the two materials. The findings demonstrate the potential of speckle imaging for non-destructive optical characterization of graphene-based materials.
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Image Generation for Moina Classification using GAN-CNN and Digital Holography
(2024-01-01)
Voochaiyaphum, Bunyarit
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Buranasiri, Prathan
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Yindeesuk, Witoon
Moina are small aquatic organisms that cannot be differentiated by species with the naked eye. In this research, we employed the GAN-CNN technique to generate images of Moina from raw hologram data and to automatically classify the species. The experimental results demonstrate the effectiveness of the GAN-CNN technique for species classification.
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Image Generation for Moina Classification using GAN-CNN and Digital Holography
(2024-01-01)
Voochaiyaphum, Bunyarit
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Buranasiri, Prathan
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Yindeesuk, Witoon
Moina are small aquatic organisms that cannot be differentiated by species with the naked eye. In this research, we employed the GAN-CNN technique to generate images of Moina from raw hologram data and to automatically classify the species. The experimental results demonstrate the effectiveness of the GAN-CNN technique for species classification.
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The Effect of PbS Colloidal Quantum Dots with CdS and ZnS Coating on Photovoltaic Properties
(2023-01-01)
Wichaiyo, Napasuda
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Kitiwan, Mettaya
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Shen, Qing
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Yindeesuk, Witoon
In this research, we used the co-precipitation method to fabricate lead sulfide colloidal quantum dots (PbS CQDs) for photovoltaic cells. PbS CQDs were deposited uniformly on a titanium dioxide electrode by the dip-coating method. Photoelectrodes were prepared by coating layers using the successive ionic layer adsorption and reaction (SILAR) method. A solar simulation was used to investigate the photovoltaic properties of photoelectrodes under one sun illumination (100 mW/cm<sup>2</sup>) at room temperature (AM 1.5 G). The photovoltaic measurements demonstrated that TiO<inf>2</inf>/PbS CQDs with CdS and ZnS coating electrodes had a maximum power conversion efficiency (PCE) of 1.01 %. The crystallite size of PbS CQDs with different coating layers was analyzed using X-ray diffraction (XRD), and the crystallite size range was 6-7 nm. The existence of PbS CQDs and coating layers on the TiO<inf>2</inf> electrodes was confirmed by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). UV-visible spectroscopy was used to obtain the optical properties of the photoelectrodes. The optical band gap was 0.72-0.75 eV.
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Electronic nose ammonia gas monitoring via IoT system for Chlorella sp. cultivation
(2023-01-01)
Srinuanjan, Keerayoot
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Kruakuanphet, Aphichaya
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Phongwisit, Phachara
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Yindeesuk, Witoon
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Kamoldilok, Surachart
In this paper, we present an electronic nose ammonia gas monitoring via IoT system for Chlorella sp. cultivation. The MQ–137 gas sensor module is selected as the primary sensor for measuring ammonia gas concentration. The pH sensor module is the sensor for measuring the pH levels in Chlorella sp. ponds. The MQ–137 gas sensors are calibrated with a known concentration of ammonia gas in the calibration box. Calibration conditions are set corresponding to low concentration of ammonia gas produced by Chlorella sp. cultivation. The pH sensor module is calibrated against a standard pH buffer. The calibration data obtained from the calibration method is input into computer programming and processed by the ESP8266 microprocessor. After calibration, the MQ–137 gas sensor and pH sensor modules are used to measure the ammonia gas concentration and pH levels in the Chlorella sp. ponds. Chlorella sp. is cultivated under three conditions of light intensity, natural light with an average light intensity of 1521 Lux, and artificial light with a light intensity of 1000 Lux and 2000 Lux, respectively. The ammonia gas concentration and pH levels of Chlorella sp. cultivation are transferred to the cloud system and displayed via the IoT system. And the system can also send a notification to a smartphone when ammonia gas concentration and the pH levels reach the specified value.
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An application of reflective holographic gratings for measurement of cylindrical curvature
(2022-01-07)
Inneam, Chanikan
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Srinuanjan, Keerayoot
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Yindeesuk, Witoon
This paper presented an application of reflective holographic gratings for the measurement of cylindrical curvature. The surface of the fabricated holographic grating was coated with gold by the sputtering method, where it became a reflective holographic grating. The grating was attached to the surface of various radius cylindrical objects. The diffraction pattern produced by the bent grating with different radius was observed by illuminating a laser beam normal to the grating surface. The gratings constant were calculated from the observed diffraction pattern. The relationship between the grating constants and the radius of cylindrical objects was obtained. The grating constant and the reciprocal of the radius of cylindrical objects was a linear relationship, with the least R-square between 0.85-0.97. Moreover, the y-intercept of the relationship between the grating constants and the reciprocal radius was consistent with the grating constant of the non-bended grating. As the radius of the grating approach is infinite, the reciprocal of the radius approaches zero, which is a non-bend grating. We can apply this method to measure the radius of cylindrical objects.
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Dry film Holographic grating based on computer-generated mask Lithography
(2022-01-01)
Inneam, Chanikan
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Tipawan Khlayboonme, S.
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Kitiwan, Mettaya
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Yindeesuk, Witoon
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Srinuanjan, Keerayoot
This paper presented an alternative technique for fabricating the dry film holographic grating based on a mask generated by computer simulation and experimental results. The mask was generated by a fringe pattern which is created by the mathematical model of two beams interference with various angles. Computer simulation of the fringe pattern was printed on film, i.e., the holographic grating mask. The mask was attached on dry film and then illuminated by UV light, where the lithography technique was applied. According to the lithography technique, the computer-generated holographic grating mask was transferred to dry film. After fabrication, fringe patterns obtained from the grating were observed. Then, the grating period was analyzed and confirmed by Scanning Electron Microscope (SEM). Experimental results show that the method could apply to fabricate the dry film holographic grating.
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Multi-range Ammonia Gas Sensor Control and Monitor via IoT System
(2022-01-01)
Kruakuanphet, Aphichaya
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Phongwisit, Phachara
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Yindeesuk, Witoon
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Kamoldilok, Surachart
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Srinuanjan, Keerayoot
In this paper, we present a multi-range of ammonia gas concentration control and monitoring via IoT system. We can select the ammonia gas concentration measurement range by adjusting load resistance within the voltage divider circuit. The appropriate measurement range, which corresponds to the concentration of ammonia gas produced by agricultural and industrial activities, can control and monitor via Blynk application. The MQ-137 gas sensor is selected as the main sensor, and each load resistance condition within the voltage divider circuit is calibrated with known ammonia gas concentration inside a calibration box. The calibration data is input into computer programming and processed by ESP8266 microprocessor. After calibration, we obtained a multi-range ammonia gas sensor suitable for measuring the ammonia gas concentration for each concentration range. The experiment showed that load resistance affects the measurement accuracy of ammonia gas concentration. We can select the load resistance suitable for the ammonia gas concentration and display on a smartphone via IoT system.

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