Research on Modern science and Utilizing Technological Innovation Journal (RMUTI Journal)

Design and Development of a Goat Manure Grinding Machine for Compost Production

Suhdee Niseng, Suchakree Srisuk, Adul Baochaemchoi, Thossapit Wissamitanan — Thu, 30 Apr 2026 00:00:00 +0700

This study aimed to design and construct a goat manure grinding machine and to investigate its optimal operating conditions for enhancing composting efficiency. Goat farming generates substantial amounts of manure, and reducing particle size prior to composting increases surface area, accelerates microbial activity, and improves nutrient uptake by plants. Experiments were conducted at three operating speeds 904, 1,201, and 1,827 rpm. The results showed that production capacity increased with higher speeds, with the maximum output of 163.19±23.34 kg/h achieved at 1,827 rpm using a 2-inch drive pulley. Ground manure at this condition was subsequently composted, and the composting period was reduced from 15 to 11 days, as the Increase of surface area enhanced microbial degradation. The resulting compost improved soil friability, decomposition rate, and nutrient
absorption by plants. An economic evaluation indicated a break-even point at 8,304.35 kg of processed manure, equivalent to approximately 51 operating hours. These findings demonstrate that the developed grinder adds value to goat manure, reduces composting time, and significantly improves both production efficiency and economic feasibility.

Using Prompt Engineering with Generative AI for the Analysis of Sentinel-2 Satellite Imagery on Google Earth Engine Platform

Suphakorn Iamsuntornkul, Chattichai WAISURASINGHA, Chutima Waisurasingha — Thu, 30 Apr 2026 00:00:00 +0700

This study aims to evaluate the potential of prompt engineering combined with generative AI to translate natural language into JavaScript code for Google Earth Engine (GEE), enabling land use classification of Sentinel-2 imagery in Mueang Khon Kaen District using a Support Vector Machine (SVM) classifier. The results demonstrated that code generated through prompt engineering and Generative AI could be effectively utilized for processing large-scale geospatial data on GEE, achieving 87 % overall accuracy and a Kappa coefficient of 0.84. The effectiveness of the results depended on two primary factors: (1) the quality of training data for the SVM classifier, and (2) the quality of natural language prompts used with Generative AI. Additionally, the user's geospatial expertise proved essential for optimizing command design, selecting appropriate indices, sampling code examples, and interpreting results. This research demonstrates that Generative AI combined with prompt engineering can serve as a valuable tool for supporting code generation for spatial data analysis on GEE, reducing technical barriers and expanding access to spatial data analysis technology for general users through effective natural language interaction.

Digital Platform for Green Agriculture: Driving Low-Carbon Economy toward Net-Zero in Thailand

Pannarat Wongpattananipas, Uthai Sumruamjit, Sethapong Wong-In — Thu, 30 Apr 2026 00:00:00 +0700

This research aimed to develop and evaluate a specialized digital platform for green agricultural products, serving as a critical mechanism to reduce the Carbon Footprint (CFP) and propel the farm sector towards Thailand's national Net-Zero goal. The study employed a mixed-methods research design, beginning with a user-centered approach inspired by Design Thinking to develop a functional prototype. Quantitative data were collected from a sample of 400 participants —200 farmers and 200 consumers —alongside qualitative insights from prototype testing. The results confirm that the developed platform successfully integrates essential functions, including the clear display of product Carbon Footprint information and a robust traceability system. Multiple Regression analysis indicated that the clarity of Carbon Footprint information had the most significant influence on user trust and purchasing intention ( =0.402, p<0.001). Furthermore, overall user satisfaction with the platform was high ( = 4.35, out of 5.00). In conclusion, this digital platform is a vital infrastructure component for establishing environmental trust between producers and consumers, providing transparent data on low-carbon products, and accelerating Thailand's agricultural economy's transition towards a sustainable, Net-Zero future. The findings underscore the importance of integrating verifiable environmental metrics into e-commerce for green commodities.

Influence of Mill Scale Waste as Sand Replacement in Fly Ash-Based Geopolymer Mortar on Physical, Mechanical, and Post-Fire Behaviors

Thu, 30 Apr 2026 00:00:00 +0700

This research investigated the use of mill scale waste (MS) to replace river sand (RS) in fly ash-based geopolymer mortar. The replacement at 0, 5, 10, 15, and 20 % by volume was studied, along with variations in the alkaline solution-to-fly ash ratio (L/FA) at 0.55, 0.60, and 0.65. The workability, compressive strength, density, porosity, water absorption, and post-fire behavior at 400, 700, and 1,000 ^oC were analyzed. The results showed that increasing MS decreased the flow value. Compressive strength at 5 - 15 % replacement was significantly higher than that of only RS using, with about 1.1 to 19.8 %. Furthermore, density increased with increasing volume of MS. Increasing MS volume in the mixture resulted in a slight decrease in water absorption despite an increase in porosity. After being exposed to high temperatures, the compressive strength of the geopolymer mortar decreased across all temperature ranges. However, the replacement with MS showed a tendency to reduce weight loss and increased normalized residual compressive strength, specifically, at 1,000 ^oC, using 20 % RS, the residual compressive strength achieves a maximum at 90 % compared to before heating. The research results demonstrate that MS can be used as an effective alternative aggregate for improving strength and enhancing high-temperature resistance. Furthermore, it promotes the recycling of industrial waste materials.

An Integrated Energy and Environmental Monitoring System for Community-Scale Cricket Farming via Home Assistant

Thu, 30 Apr 2026 00:00:00 +0700

Cricket farming in semi-closed systems requires maintaining an optimal temperature range, which typically demands high electricity consumption and increases production costs. Moreover, low-cost monitoring sensors used in agriculture have rarely been calibrated against standard instruments, and the integration of renewable energy with intelligent control systems for insect farming remains limited. This study presents a temperature monitoring and control system for cricket farms powered by a 4.4 kW_p solar photovoltaic–thermal hybrid system (Solar PVT) and 10.8 kW_th heat pump, designed to maintain the temperature of 20 rearing bins within 28 - 30 ^oC. The control system was developed on the Home Assistant platform with a Tuya IoT module, which effectively regulates the temperature according to predefined conditions, ensuring stable operation throughout the rearing process. Experimental results demonstrated that the Tuya IoT sensors achieved high accuracy (R² > 0.99,
RMSE 0.496 ^oC, 0.0295 kW, and MAPE <2%), confirming the system’s reliability. Furthermore, the system reduced grid electricity consumption by 41.5 %. Additional analysis indicated an annual electricity generation of 7,570.63 kWh, a reduction in greenhouse gas emissions of 3,784.56 kgCO₂eq/year, and a payback period of 5.5 years. These findings highlight the system’s technical, economic, and environmental feasibility for adoption in community-scale cricket farms.

Toxicological Effects of Medicinal Plants for Controlling the Giant African Snail (Achatina fulica)

Duanpen Wongsorn, Pornlapat Boksanthia, Jirawit Yensuang — Thu, 30 Apr 2026 00:00:00 +0700

The Giant African Snail (GAS, Lissachatina fulica) is a plant pest that damages various economic crops. This study evaluated the molluscicidal efficacy of nine medicinal plant derivatives against GAS under controlled laboratory conditions. The tested materials included: tea seed cake (Camellia oleifera), ground coffee (Coffea spp.), soap berry (Sapindus rarak), neem seed (Azadirachta indica), Indian laurel leaf (Litsea glutinosa), soap pod (Acacia concinna), physic nut seed (Jatropha curcas), tobacco (Nicotiana tabacum), and licorice root (Glycyrrhiza glabra). A Completely Randomized Design (CRD) was employed to assess two application methods: dry powdered formulations and 10% (w/v) ethanol extracts. After a 48-hour exposure period, soap berry exhibited the highest mortality rates, achieving 73.33 %
(powder) and 80 % (extract). However, these values did not differ significantly (p>0.05) from the efficacy of tea seed cake (70 % powder, 76.67 % extract) or tobacco (70 % for both formulations). In contrast, no significant molluscicidal activity was detected in the negative control, ground coffee, or physic nut seed treatments. These results demonstrate that soap berry, tea seed cake, and tobacco exhibit promising molluscicidal properties against GAS, suggesting their potential as eco-friendly alternatives for integrated pest management (IPM) strategies.

Analytical Solutions for the Developed Five-Compartment Pharmacokinetic Model

Thanachok Mahahong, Teerapol Saleewong — Thu, 30 Apr 2026 00:00:00 +0700

This study presents analytical solutions for a developed compartment pharmacokinetic model consisting of five compartments to describe the dynamics of drug concentration in the body, namely the absorption compartment, the central compartment representing the blood circulation system, the rapidly equilibrating tissue compartment, the slowly equilibrating tissue compartment, and the effect-site compartment. The model is formulated as a system of ordinary differential equations describing drug transfer and elimination between compartments. The analytical solution process is divided into three stages: (1) deriving the solution for the absorption compartment using the method of separation of variables, (2) analyzing the system of equations for the central and tissue compartments using eigenvalue analysis combined with the Laplace transform, and (3) obtaining the solution for the effect-site compartment using the method of undetermined coefficients. The results show that, upon applying the initial conditions, closed-form analytical solutions for drug concentrations in all compartments can be obtained. Although some solutions involve complex eigenvalues, they effectively characterize the dynamic behavior of the system. Furthermore, a numerical
example is presented using rate constant parameters consistent with ranges reported in the pharmacokinetic literature, and the concentration-time profiles for all compartments are illustrated using the derived closed-form solutions, demonstrating drug behavior that is consistent with pharmacokinetic theory. These analytical solutions serve as a fundamental framework for validating numerical solutions and supporting future pharmacokinetic model development.

Application 3D Scanner for Heritage Building Data: Chetawan (Ka Pheuak)

Thu, 30 Apr 2026 00:00:00 +0700

This study aims to describe the distinctive characteristics of the study area and to compare the efficiency of heritage site data collection methods. The case study focuses on Wat Chetawan (Ka Phueak) in Phayao Province, an important Lanna heritage site with an estimated age of around 500 years. At present, only the remains of the stupa, brick temple base, and wall structures remain in deteriorated condition. The site reflects the historical, architectural, and cultural values of the local community, making it necessary to record detailed physical data for conservation and further research. The research methodology consists of two approaches: (1) traditional surveying using a Total Station and manual measurements, and (2) three-dimensional laser scanning with the Faro Focus M70 to generate Point Cloud datasets and digital models. The comparative results show that 3D scanning can capture data with a resolution of more than 2,000 points per square meter, access complex areas without physical
contact, and reduce fieldwork time. In contrast, traditional surveying, while cost-effective and familiar
to practitioners, is limited in terms of resolution and access to certain areas. In conclusion, 3D scanning demonstrates greater potential for digital conservation, 3D modeling, rapid fieldwork, and non-invasive data acquisition. Traditional methods, however, still offer advantages in terms of familiarity and lower costs. Integrating both methods enhances accuracy and data potential, enabling applications in engineering, archaeology, and sustainable cultural heritage preservation.