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A smartphone-integrated rapid and sensitive lateral flow test strip for quantitative detection of Fusarium spp. in maize samples
(2025-05-01)
Rotamporn, Saowalak
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Cheubong, Chehasan
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Sansenya, Sompong
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Jantra, Jongjit
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Teepoo, Siriwan
In the world, maize is considered as one of the most valuable resources. Fusarium spp. are the primary soilborne plant-pathogenic fungi that can infect maize seeds and cause diseases that potentially decrease the production of crops. This study aims to develop a rapid and sensitive lateral flow test strip (LFTS) utilizing gold nanoparticles (AuNPs) for on-site detection of Fusarium spp. in maize samples. The smartphone-integrated LFTS enables the identification of Fusarium spp. within a concentration range of 0.2–1.5 nM and achieves a limit of detection (LOD) as low as 0.063 nM. The quantitative determination of the Fusarium spp. can be completed within 8 min. Maize samples were analyzed using both the LFTS and real-time polymerase chain reaction (real-time PCR). The LFTS demonstrated effective recovery in spiked samples, with values ranging from 80.1% to 101.1%. Furthermore, the real-time PCR results exhibited significant agreement with the LFTS results. Compared to the traditional real-time PCR technique, the proposed LFTS offers a sensitive, accurate, and rapid assay for the on-site detection of Fusarium spp. in maize samples.
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Smartphone-based imaging colorimetric assay for monitoring the quality of curcumin in turmeric powder
(2024-07-01)
Jantra, Jongjit
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Teepoo, Siriwan
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Thananimit, Suchera
This research developed a colorimetric assay for semi-quantitative curcumin detection. The screening test was performed using a ferric chloride to form a brownish color which was further used to evaluate the amount of curcumin in the turmeric powder samples. The quantitative assay was performed based on the color intensity of the curcumin target using a smartphone digital image colorimetry with a developed lightbox constructed with a white light-emitting diodes (LED) light source as the measurement device. Images in red, green, and blue (RGB) color were processed to obtain relevant colors from the image and the color values were used to analyze curcumin concentrations. The intensity of the ΔB was correlated to the concentration of curcumin with high sensitivity. The method showed a linear range between 0.25 and 5 mg L−1 with the LOD and LOQ of 0.12 and 0.41 mg L−1, respectively. Sample analysis was carried out in turmeric powders. Curcumin in turmeric powder samples was simply extracted using acetonitrile followed by dilution 100 times for sample preparation. The accuracy was tested by spiking 0.25, 1.00, and 4.00 mg L−1 of standard curcumin into the turmeric sample solution. The average percentage recoveries were acceptable in all samples (90–104%). The method was validated by comparing the results obtained from the proposed method and high-performance liquid chromatography (HPLC). There was no statistically significant difference between the two methods (P = 0.05). Graphical Abstract: (Figure presented.).
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Hierarchical KNN for Smartphone-Based 3D Indoor Positioning
(2024-01-01)
Adiyatma, Farid Yuli Martin
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Sunimit, Samita
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Chokporntaveesuk, Thanwa
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Lualum, Krittima
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Chaisang, Naphat
Fingerprint-based localization, or positioning technique, is well-known to achieve high accuracy in location estimation in indoor environments where the multipath fading effect is severe. However, the accuracy of location estimation depends on the choice of the pattern matching techniques that are developed in the on-line phase. This paper proposes a new algorithm called Hierarchical K-Nearest Neighbors (KNN) for the pattern matching phase to estimate the location of the target in 3-dimensional (3D) indoor environments. For practical usage and saving budget and time for implementation, the Wi-Fi-based indoor positioning system (IPS) is implemented, and the smartphone is used as the user device. In this work, an Android smartphone is used for the study case. The results demonstrate that Hierarchical KNN achieves the lowest mean distance error (MDE) of approximately 3.263 m, outperforming various fundamental machine learning approaches such as Random Forest and KNN classifiers, with MDE reductions of 8.19% and 11.52%, respectively.
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Silica nanoparticle–modified paper strip–based new rhodamine B chemosensor for highly selective detection of copper ions in drinking water
(2023-08-01)
Sannok, Tadcha
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Wechakorn, Kanokorn
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Jantra, Jongjit
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Kaewchoay, Netnapit
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Teepoo, Siriwan
A new rhodamine B derivative (RDB) was synthesized and utilized for the colorimetric detection of copper ions (Cu2+). This chemosensor utilized a paper strip as a support and a smartphone as a detector for on-site quantitative detection of Cu2+ in water samples. Silica nanoparticles (SiNPs) were investigated as the modifier nanoparticles to achieve uniform color on the paper strip and showed a color response 1.9-fold higher than the one without SiNPs. The RDB chemosensor-based paper strip provided high selectivity toward Cu2+ with a detection limit of 0.7 mg/L, and the working concentrations for Cu2+ ranged from 1 to 17 mg/L. Parallel analyses of eight drinking water samples were conducted by inductively coupled plasma optical emission spectroscopy. The results were in good agreement, indicating the practical reliability of the established method with a short assay time and high selectivity. These indicate its great potential for on-site detection of Cu2+. Graphical abstract: [Figure not available: see fulltext.]
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Colorimetric test strip cassette readout with a smartphone for on-site and rapid screening test of carbamate pesticides in vegetables
(2022-10-01)
Rakkhun, Waraporn
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Jantra, Jongjit
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Cheubong, Chehasan
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Teepoo, Siriwan
A test strip cassette integrated with a smartphone detector was developed for the colorimetric detection of carbamate pesticides in vegetables. The influence of various experimental conditions was examined for the detection of the optimum analytical performance of the test strip cassette. The test strip cassette detection of carbamate pesticides was carried out by using 140 mM of acetylthiocholine, 13 mM of 5,5′-dithiobis (2-nitrobenzoic acid), temperature at 37 °C and pH of 8.0. The developed test strip cassette platform is rapid within 5 min. Based on the inhibition effect of carbaryl on acetylcholinesterase activity, the inhibition effect of carbaryl was proportional to its concentration ranging from 1 to 50 mg/L with the detection limit of 0.30 mg/L. The limit of quantitative value was determined to be 1.0 mg/L. The spiking carbaryl, the recoveries were within 96–103% and the relative standard deviations were less than 1.56%. The analysis of carbamate pesticides residual in vegetable samples gave the results in good agreement with the most widely used commercial test kit and UPLC-MS/MS method. The developed test strip cassette required only 5 min for an assay. With the simple procedures and tiny size, it showed a great promising for the developed test strip to work on-site for carbamate pesticides detection in vegetables.
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Small gardening robot with decision-making watering system
(2019-01-01)
Tangtisanon, Pikulkaew
At present, people who live in the countryside tend to move downtown in order to get jobs. As a consequence, only elders and children live in their hometowns with plenty of land left uncultivated. The aim of this research is to build cheap small gardening robots to help people grow plants in small yards as a hobby via a long-distance communication system. In this research, two robots composed of Raspberry Pi and ESP32 microcontrollers, which are low-price controller boards and convenient to buy within the country, were constructed. The robots can be controlled from long distances using Android smartphones. The capacities of the two robots with the two types of microcontroller are compared and discussed. To measure the soil moisture content, two types of moisture sensor, which are capacitive and resistive sensors, were implemented in this project. There are two main functions of the proposed model, which are weed cutting and watering plants. Moreover, a decision-making watering system was implemented and connected to moisture sensors and sprinkler controllers placed in the user’s garden. The robots were placed in the northern region of Thailand, while the user stayed in the central region and remotely controlled them with a smartphone for three months. The results show that the automatic watering system is better than a manual watering system since the plant growth rate for the automatic watering system was 20% higher than that for the manual watering system.
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PLC-Based Wheelchair Control with Integration of the Internet of Things
(2018-10-15)
Gulpanich, Suphan
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Petchhan, Jirayu
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Wongvanich, Napasool
This paper presents a PLC-based mobile mecanum-wheeled wheelchair control algorithm with the integration of the Internet of Things (IoT). The design aims to enhance comfort to the handicapped by offering wireless wheelchair control in addition to the Human Machine Interface (HMI) over the Ethernet port. The bottom-up approach was taken where proportional mobility control in the vector form of speed and direction is firstly configured and displayed over the touch screen. Remote access is then designed to access through the use of the HMI Remote Viewer application which supports and displays the corresponding speed and direction on a smartphone, upon wireless communication. Results show that the communication speed is within the rapidity range, whereas the locomotion test shows an average of 8.5% drop in speed from the no-load case to the loaded case. The proposed design thus provides a complete range of wheelchair control which can be used to assist the handicapped.
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The use of smartphone for gait analysis
(2017-06-07)
Yodpijit, Nantakrit
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Tavichaiyuth, Nicha
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Jongprasithporn, Manutchanok
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Songwongamarit, Chalida
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Sittiwanchai, Teppakorn
In today's information-rich environment, one of the most popular devices is a smartphone. Research has shown significant growth in the use of smartphones and apps all over the world. Accelerometer within smartphone is a motion sensor that can be used to detect human movements. Compared to other major vital signs, gait characteristics represent general health status, and can be determined using smartphones. The objective of the current study is to design and develop the alternative technology that can potentially predict health status and reduce healthcare cost. This study uses a smartphone as a wireless accelerometer for quantifying human motion characteristics from four steps of the system design and development (data acquisition operation, feature extraction algorithm, classifier design, and decision making strategy). Findings indicate that it is possible to extract features from a smartphone's accelerometer using a peak detection algorithm. Gait characteristics obtain from the peak detection algorithm include stride time, stance time, swing time and cadence. Applications and limitations of this study are also discussed.
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A smartphone-based real-time simple activity recognition
(2017-06-07)
Jongprasithporn, Manutchanok
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Yodpijit, Nantakrit
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Srivilai, Rawiphorn
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Pongsophane, Paweena
This paper explores a physical activity monitoring application in smartphones. The combination of smartphone application and sensors could perform as a biomedical sensor to monitor physical activities. Thai 3 Axis (TH3AX) was developed as a real-time physical activities monitoring application such as standing, walking, and running. The smartphone was attached to right hip of 10 young, healthy adult subjects to collect accelerometer data to determine threshold range for each activity. After finding thresholds, the results were used as range for a predictive model of activity recognition. The second experiment was scheduled with 6 young healthy subjects performed three physical activities (standing, walking, and running) to evaluate TH3AX application. Then, a diagnostic test was computed to test TH3AX's sensitivity, specificity, and accuracy. Results showed that TH3AX sensitivity, specificity, and accuracy are 0.981, 0.988, and 0.986, respectively.
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Telecare application and tools for older adults
(2015-01-26)
Tangtisanon, Pikulkaew
Recently, with the innovation of modern medical technology, the elderly population has been rapidly increased than before. In the past, without the Internet technology, the elderly must spend their life in the nursing home even though they are not in any serious sickness due to the expensive wage of the personal curator. Fortunately, nowadays, the capability of mobile phone and the quality of networking have been improved. With the proposed model, the elderly health care strategy is changed. To begin with, the questionnaire has been carried out to the caretaker of the elderly. The result shows that almost all of them would like to tend the elderly at home if these three major problems; falling, medicine taking, and monitoring, can be solved. In this paper, not only the senior patient can recuperate at home safely without home health aides but also, this new model runs with everyday technologies and low-cost equipment such as Smartphone. The falling is detected with an integrated tri-axial gyroscope and the alert will be sent to the caretaker via the Internet. The medicine taking problem is solved with the medicine box that can be controlled by the caretaker in a remote distance. Lastly, the monitoring application is developed.

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