This report provides an overview of the optics and photonics industry in Thailand. Driving by global geopolitics, the need for resilient supply chains, robust national policies, and the growth of artificial intelligence (AI), Thailand founded with good engineering infrastructure has supported deep technologies spanning silicon photonics, high-speed telecommunications, advanced imaging, and precision ophthalmic lenses manufacturing. The study analyzes the corporate landscape by categorizing the industry into four primary clusters: Ophthalmic Lenses, Precision Optics, and Eyewear Technology; Advanced Imaging Sensor Manufacturers; Industrial Laser Machinery; and Photonics, Optoelectronics, and Telecommunications. Sustaining this competitive advantage and evolving from a “Made in Thailand” to an “Innovated in Thailand” economy will still require hard work and dedicated public-private collaborations to nurture specialized science and engineering talent in materials science, optics and photonics, metrology, and quantum engineering.

A highly accurate and low-cost mobile platform for multiple object temperature measurement in 3D coordinate positions is introduced. The key idea relies on not only a combination of a 3D optical depth sensor and the 2D infrared thermal imager but also a determined distant-dependent compensation model. As a result, a cost-effective yet wider (>100.0∘C) temperature measurement range under the fluctuation of working distant shift is realized with a low standard deviation of 0.16°C at the working distance of 1.0 m. Accurate temperature measurement at different positions of objects along the suitable working distance is also demonstrated.

Multispectral imaging camera is an important tool for two-dimensional (2-D) and 3-D spectroscopic analysis. First deployment was in space for remote sensing application, and it is now available for applying on sites or installing with drones. In this work, we propose an affordable palm-size wide-band 3-D multispectral imaging camera, covering broad blue, green, red, near infrared, and long wave infrared regions. Our palm-size 3-D multispectral imaging camera module is also embedded with our own designed software for capturing or recording 2-D spectral images with depth information from each spectral band simultaneously. These spectral images and depth information can be combined into 2-D and 3-D fused spectral images. Promising applications are in industry, agriculture, environment, public health, and security.

We demonstrate quantum random number generation based on a photon-number detection scheme with the use of a silicon photomultiplier. We implement a time integral with detector response signals for resolving photon numbers, which are subsequently digitized into a stream of 4-bit sequences with a generation rate of 13.6 Mbit/s. Our generated random bits pass the statistical randomness validation according to the U.S. National Institute of Standards and Technology (NIST) Special Publication 800-22. This scheme is implementable with inexpensive components, and the system can be miniaturized to the size of a plug-and-play portable cryptographic device.

The optical spectrometer is a widely established and widely used scientific instrument for analyzing biochemical samples. However, it is expensive, bulky, and requires an external power source and a computer to operate, which makes it difficult to use in resource-limited countries and in remote locations. Advancement in smartphone technology has led to the development of portable, low-cost smartphone-based spectrometers. However, the lack of smartphone-based software and automatic wavelength calibration results in irrelevant workloads for students within the time limit of the course. In addition, most smartphone spectrometers are only able to capture images. As a result, a computer becomes an essential tool for the student to process and analyze the sample spectrum. Unlike many other smartphone-based spectrometers, our developed device also provides a smartphone application for both Android and iOS platforms. Thus, measurement data and data plots are transferrable among smartphones and computers. In addition, the wavelength calibration is carried out automatically using an embedded reference white light LED by the application. Furthermore, the provided 3D-printed parts, part lists, and circuit board are included with an example of an iPhone 7 mount, as well as their assembly instructions. Our developed device features a sufficiently quantitative measurement for wavelength ranges from 411.2 to 700 nm. For the spectral resolution, our device achieved resolutions of 9.8, 13.4, and 21.7 nm at wavelengths of 405, 532, and 650 nm, respectively, when evaluated with an iPhone 7.

Random numbers are indispensable resources for application in modern science and technology. Therefore, a dedicated entropy source is essential, particularly for cryptographic tasks and modern applications. In this work, we experimentally demonstrated a scheme to generate random numbers by multiplexing eight tunnel diodes onto a single circuit. As a result, the data rate of random number generation was significantly enhanced eightfold. In comparison to the original scheme that employed one diode, this multiplexing scheme produced data with higher entropy. These data were then post-processed with the Toeplitz-hashing extractor, yielding final outputs that achieved almost full entropy and passed the U.S. National Institute of Standards and Technology (NIST) Special Publication 800-90B validation. These data also passed the NIST Special Publication 800-22 statistical randomness examination and had no sign of patterns detected from an autocorrelation analysis.

Due to the current wide spread of infectious diseases in human and animals, we propose and demonstrate here a combination of thermal imaging-based mass temperature screening modules and crowdsourcing approach for low-cost and real-time surveillance purpose across communities.

Multispectral imaging camera is an important tool for two-dimensional (2-D) and 3-D spectroscopic analysis. Rather than using an available high-end product or prototype, we propose and engineer a low-cost 3-D broad-spectral imaging module, covering blue, green, red, near infrared, and long wave infrared regions. With our own designed software, it can collect 3-D spectral images from each spectral band simultaneously and it can combine these images into 2-D and 3-D fused spectral images. It is designed in a compact 16.9×2.9×7.1 cm 3 with just 310 grams.

The rice kernel inside a hull is composed of the embryo and endosperm. The embryo or germ of the rice seed will grow and become the shoot and the root parts of a seedling, while the endosperm is an important nutrient source for the embryo in the early stages. Hence, the health of seedlings depends particularly on the sizes of the embryo and endosperm. In this work, we propose and experimentally demonstrate how the embryo and endosperm areas of brown rice can simply be determined. Our key idea is based on the utilization of a smart mobile device equipped with our specifically designed lens module arranged in a simple cross-polarization imaging configuration for acquiring a rice grain image upon the illumination of a white light source and then spatially analyzing the sizes of embryo and endosperm areas. The prototype shows promising results in identifying the sizes of the embryo and endosperm within 2 s per seed with a measurement error of <9% compared with the use of off-the-shelf image editing software. In addition, the prototype is in a small package of 20×32.5×6.5cm3 with 4 kg weight, thus showing high potential to perform in the real scenario.

Metal halide-based perovskite materials have received great attention in scintillating applications because they can emit strong visible light when interacting with X-ray particles. Here, we report a scintillator based on rubidium copper chlorine incorporated in the polydimethylsiloxane matrix. The scintillator shows a bright violet emission under ultraviolet and ionizing radiation. The temperature-dependent photoluminescence and radioluminescence shows maximum thermal enhancement at 80°C and 60°C, respectively. Moreover, the first X-ray image from this material reveals the detailed information of the object captured by a commercially available digital camera, indicating a potent scintillator for creating X-ray imaging screens.

Random numbers are important in many activities, including communication, encryption, science, gambling, finance, and decision making. There is a strong demand for a hardware random number generator that could support cryptographic applications. In this work, we propose a quantum tunneling diode as a source of true randomness achieved by applying electrical current sweeps through the device and then harnessing a time-counting unit to measure fluctuation of current flows. Our approach can be implemented with inexpensive electronics and could be integrated into systems that require random numbers such as portable communication devices.

Hand reeled Thai silk yarns can be classified based on its physical quality such as diameter, color and weight. In general, certified inspectors are randomly select parts of the silk yarn and evaluate the uniformity of diameter and color by their naked eyes. This process is laborious, and sometimes gives uncertain results due to the experience of inspectors, which affects the price of the silk yarn. To overcome these difficulties, we propose and implement an optical sensing system called “Silk Check” for classification of the hand reeled Thai silk yarn. It can determine in real time the length and the linear mass density of the silk yarn, and correctly classify into the corresponding grade under the Thai Agricultural Standard. Field test operation for 34 silk yarns shows that our “Silk Check” can precisely classify 24 silk yarns of the 1 st class into the premium, the first, and the second grades. It also can separate 10 silk yarns of the 2 nd class into the first and second grades. Additional important parameters such as the color shade and Ratio xy of silk are also determined by our “Silk Check.” These results indicate that our optical sensing system can benefit to the sericulture industry 4.0.

Nowadays, body temperature screening is very important especially in the current global coronavirus disease (COVID-19) epidemic. It can be considered as the first step in monitoring the fever symptom if the body temperature is checked regularly. Aiming at alleviating the influence of working distance and ambient temperature disturbance, this article proposes and demonstrates a self-compensation technique that is built into our low-cost thermal imaging-based temperature screening system. The key idea relies on a combination of a 3-D depth sensor, an electronic temperature sensor, and a reference temperature for realtime data feedback and control. In addition, we obtain simple mathematical models for compensating the influence of ambient temperature and measuring distance variations. Experimental demonstration using a blackbody radiation source as an object confirms that the measured temperature under our self-compensation agrees very well with the blackbody radiation source, showing a very low standard deviation of 0.10 °C under 21.0 °C–40.0 °C ambient temperature. In addition, an improved standard deviation of 0.18 °C and a low 0.020 °C/m for the measured temperature are obtained under the variation in measuring the distance from 0.50 to 2.00 m.

Liquid crystal display (LCD) is one of the optical devices that we see in our daily life. Its functionality is designed to operate in an amplitude modulation with up to a 32-bit resolution. As it is a low-cost spatial light modulator, this paper shows that two-dimensional (2-D) phase modulator can be obtained from this device. Experimental proof of concept using an off-the-shelf 60-USD 800x480-pixel LCD, a 633-nm wavelength laser diode, and a wavefront sensor shows that a linear 2-D phase modulator is obtained, offering a maximum 0.76-wave phase shift at a maximum grayscale value of 255. Varying digital bit control values from 0 to 255 leads to a very low optical power fluctuation of 1.53%.

As fast human temperature screening is needed in large public areas, this paper proposes a low-cost mobile platform module that combines the advantages of analyzing visible and thermal images. In particular, the key idea relies on face detection in the visible image. Then the coordinates of all faces detected are mapped on to the thermal image to determine their corresponding temperatures. Internal temperature compensation and external reference temperature also are employed to reduce the unwanted temperature fluctuation inside the module and in the surrounding environment. Our mobile platform module, called $\unicode{x00B5} {\rm Therm}$, uses a FLIR ONE camera as our visible and thermal imaging cameras. It can simultaneously determine the temperatures of nine people at a speed of 8 frames/second. A field test operation was performed for four days with 1,170 people, with very promising results of 100% sensitivity, 92.6% specificity, and 92.7% accuracy.

In this paper, automatic fever screening system is proposed and experimentally implemented using an IR camera and a mobile phone. Our system locates position of patients automatically using face detection algorithm on RGB image and obtains temperature from IR image at detected location. Advantages are fast, portable, non-contacting and simultaneously temperature measurement. Furthermore, face detection algorithm allows the system to track patient's face position. Hence, robust and non-contacting temperature measurement can be properly done even patients are not stand still. Our system has been field-tested to measure temperature and screen ill patients at a children medical clinic. In this experiment, the system is calibrated to measure temperature of patients at 1 meter away and gives an alarm sound when the measured temperature is above the desired setting threshold. According to experimental results, the correlation coefficient between temperature obtained from our system and commercial infrared forehead skin thermometer [2] is more than 0.80. In addition, our system achieves a 100% sensitivity and 70% specificity. Although our approach loses specificity, all fever patients are identified correctly. Thus, they are significantly correlated. Therefore, this system can reliably estimate body temperature of patients and can be used for effectively pre-screening fever patients.