• Journal of Soil and Groundwater Environment
• /
• v.29 no.4
• /
• pp.1-11
• /
• 2024

This study evaluated a method for prompt and periodic monitoring of moisture content in the waste layer of a landfill using a Time Domain Reflectometry (TDR) sensor, aimed at ensuring the stable operation of the bioreactor facility at the 2nd landfill of the SUDOKWON Landfill Site. It was found that the TDR sensor is sensitive to variables such as temperature changes and ion content in both the waste layer and leachate, indicating that a correction equation is necessary. A correction equation derived through regression analysis demonstrated a high correlation (correlation coefficient = 0.9647), and field verification experiments confirmed its reliability with an average deviation of only 1.5%. This verifies that the TDR sensor is effective for measuring and monitoring moisture content in landfills. It is also anticipated to be useful for various applications, including monitoring leachate levels, detecting leachate leakage, and assessing rainwater infiltration.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.130-136
• /
• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• Journal of Digital Contents Society
• /
• v.19 no.7
• /
• pp.1423-1431
• /
• 2018

IoT(Internet of Things) is applied to technologies such as agriculture and dairy farming, making it possible to cultivate crops easily and easily in cities.In particular, IoT technology that intelligently judge and control the growth environment of cultivated crops in the agricultural field is being developed. In this paper, we propose a method of predicting the growth environment of plants by learning the moisture supply cycle of plants using the intelligent object internet. The proposed system finds the moisture level of the soil moisture by mapping learning and finds the rules that require moisture supply based on the measured moisture level. Based on these rules, we predicted the moisture supply cycle and output it using media, so that it is convenient for users to use. In addition, in order to reduce the error of the value measured by the sensor, the information of each plant is exchanged with each other, so that the accuracy of the prediction is improved while compensating the value when there is an error. In order to evaluate the performance of the growth environment prediction system, the experiment was conducted in summer and winter and it was verified that the accuracy was high.

• Journal of Biosystems Engineering
• /
• v.28 no.4
• /
• pp.369-376
• /
• 2003

This study was conducted to develop a precision measurement method of water content in soil (find sand and silty sand) using dual RF impedance changes. The electrically stable perpendicular plate capacitive sensor was fabricated and utilized to sense the water content in soil. Crystal oscillators of 5 and 20 MHz and related circuits were designed to detect the capacitance changes of a perpendicular plate capacitive sensor with soil samples at various volumetric water contents. A multiple regression model for volumetric water content having dual oscillation frequency changes at 5 and 20 MHz as independent variables resulted in coefficient of determination of 0.963 and standard error calibration of 0.030 cm$^3$/cm$^3$ for calibration and coefficient of determination of 0.966, standard error of prediction of 0.027 cm$^3$/cm$^3$ and bias of 0.001 cm$^3$/cm$^3$ for prediction.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_1
• /
• pp.931-946
• /
• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Journal of Korea Water Resources Association
• /
• v.56 no.11
• /
• pp.721-728
• /
• 2023

Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO₂) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO₂ concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO₂ flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO₂ flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO₂ (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO₂ flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.

• Agricultural and Biosystems Engineering
• /
• v.4 no.2
• /
• pp.45-49
• /
• 2003

Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen ($NO_3-N$), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

• Asian Journal of Turfgrass Science
• /
• v.20 no.2
• /
• pp.213-221
• /
• 2006

This study was designed to determine what sensor-based technologies might reliably and accurately predict irrigation scheduling needs of warm-season turfgrass. 'Floratam' St. Augustinegrass[Stenotaphrum secundatum(Walt.) Kuntze] and 'Sea Isle I' seashore paspalum(Paspalum vaginatum Swartz) were established in tubs in the Envirotron Turfgrass Research Laboratory in Gainesville, FL in the spring of 2002. Each grass was subjected to repeated dry-down cycles where irrigation was withheld. Sensor-based data were collected and these evaluations were used to determine if irrigation scheduling could be determined based on plant response during dry-down. Results indicated that reflectance indices($P{\le}0.001$) and soil moisture($P{\le}0.0001$) throughout the dry-down cycle can predict the need for irrigation scheduling as turf quality declined below acceptable levels.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3275-3298
• /
• 2022

Cloud-based architectures for precision agriculture are domain-specific controlled and require remote access to process and analyze the collected data over third-party cloud computing platforms. Due to the dynamic changes in agricultural parameters and restrictions in terms of accessing cloud platforms, developing a locally controlled and real-time configured architecture is crucial for efficient water irrigation and farmers management in agricultural fields. Thus, we present a new implementation of an independent sensor-enabled architecture using variety of wireless-based sensors to capture soil moisture level, amount of supplied water, and compute the reference evapotranspiration (ETo). Both parameters of soil moisture content and ETo values was then used to manage the amount of irrigated water in a small-scale agriculture field for 356 days. We collected around 34,200 experimental data samples to evaluate the performance of the architecture under different agriculture parameters and conditions, which have significant influence on realizing real-time monitoring of agricultural fields. In a proof of concept, we provide empirical results that show that our architecture performs favorably against the cloud-based architecture, as evaluated on collected experimental data through different statistical performance models. Experimental results demonstrate that the architecture has potential practical application in a many of farming activities, including water irrigation management and agricultural condition control.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.197-205
• /
• 2024

This paper presents a fully automated stand-alone irrigation system with GSM (Global System for Mobile Communication) module. Solar energy is utilized to power the system and it is aimed to conserve water by reducing water losses. The system is based on a DC water pump that draws energy from solar panels along with automated water flow control using a moisture sensor. It is also fitted with alert and protection system that consists of an ultrasonic sensor and GSM messages sender that transmits signals showing the levels of the water in the reservoir and the battery charge. The control system is designed to stop the water pump from pumping water either when the battery level drops to equal or less than 10% of its full charge, or when the water level becomes less than 10 cm high in the reservoir. The experimental results revealed that the system is appropriate to use in remote areas with water scarcity and away from the national grid.