• Journal of Convergence for Information Technology
• /
• v.10 no.10
• /
• pp.135-142
• /
• 2020

In the recent farming industry, there is a growing diffusion of drones, which are recognized as a crucial technology of the 4 th industrial revolution to cope with aging. Especially, filming and pest control using drones are representative fields that have different age groups for obtaining a national license of multicopter that is a ultra-light flying device, and can create profits after getting a license. However, pest control technology using drones has different spray effects depending on levels of operational proficiency, since this highly relies on an operator's operating skills. It is anticipated that if this issue is supplemented, the use of drones for pest control in the farming industry will diversify. For analysis of spraying characteristics of agricultural pest control drones, this study aims to formulate effective spraying hours and effective spraying intervals and suggest an algorithm, which facilitates an accurate calculation of pest control area depending on the kinds of pest control drones. This algorithm can be used in the field of pest control by improving scatterling issues caused by drone flight methods of drone pest controllers and building an optimum pest control manual in future.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.33 no.5
• /
• pp.179-186
• /
• 2021

We need measures that can come up with alternative about fishery living zone and enhance local acceptance for responding to the increase in the proportion of renewable energy production and construction of 12GW Offshore wind power according to Korea's Renewable Energy 3020 initiative and Korean-version New Deal. In this study, We suggest that differentiation plans of co-location model in connection with offshore wind power generation suitable for the East Sea. The East Sea is an optimal site for building of a floating offshore wind power generation(FOWPG) field. It is expected that economic effects like energy production, aquatic resource development and tourism industrialization by farming bluefin tuna which is high valued fish and suitable for offshore aquaculture on public waters in FOWPG field. And we can confirm that budget reduction, smart management by sharing operation management technology and increase in fishermen income.

• Journal of Internet Computing and Services
• /
• v.25 no.2
• /
• pp.49-55
• /
• 2024

This paper proposes PredFeed Net, a neural network model that mimics the food distribution of fish farming experts. Unlike existing food distribution automation systems, PredFeed Net predicts food distribution by learning the food distribution patterns of experts. This has the advantage of being able to learn using only existing environmental data and food distribution records from food distribution experts, without the need to experiment by changing food distribution variables according to the environment in an actual aquarium. After completing training, PredFeed Net predicts the next food ration based on the current environment or fish condition. Prediction of feed ration is a necessary element for automating feed ration, and feed ration automation contributes to the development of modern fish farming such as smart aquaculture and aquaponics systems.

• Journal of Mushroom
• /
• v.17 no.4
• /
• pp.211-217
• /
• 2019

Currently, cultivation of mushrooms using the Information and Communication Technology (ICT)-based smart farming technique is increasing rapidly. The main environmental factors for growth of mushrooms are temperature, humidity, carbon dioxide (CO₂), and light. Among all the mentioned factors, currently, only temperature has been maintained under automatic control. However, humidity and ventilation are controlled using a timer, based on technical experience.Therefore, in this study, a Pleurotus eryngii first-generation smart farm model was set up that can automatically control temperature, humidity, and ventilation. After installing the environmental control system and the monitoring device, the environmental condition of the mushroom cultivation room and the growth of the fruiting bodies were studied. The data thus obtained was compared to that obtained using the conventional cultivation method.In farm A, the temperature during the primordia formation stage was about 17℃, and was maintained at approximately 16℃ during the fruiting stage. The humidity was initially maintained at 95%, and the farm was not humidified after the primordia formation stage. There was no sensor for CO₂ management, and the system was ventilated as required by observing the shape of the pileus and the stipe. It was observed that, the concentration of CO₂ was between 700 and 2,500 ppm during the growth period. The average weight of the mushrooms produced in farm A was 125 g, and the quality was between that of the premium and the first grade.In farm B. The CO₂ sensor was in use for measurement purposes only; the system was ventilated as required by observing the shape of the pileus and the stipe. During the growth period, the CO₂ concentration was observed to be between 640 and 4,500 ppm. The average weight of the mushrooms produced in farm B was 102 g.These results indicate that the quality of the king oyster mushroom is determined by the environmental conditions, especially by the concentration of CO₂. Thus, the data obtained in this study can be used as an optimal smart farm model, where, by improving the environmental control method of farm A, better quality mushrooms were obtained.

• Journal of Appropriate Technology
• /
• v.6 no.2
• /
• pp.136-145
• /
• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.

• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.366-375
• /
• 2022

The monitoring of electricity consumption using Internet of Things (IoT) technology is attracting attention as a technology to reduce operation costs of smart farms. In this study, we propose a method to apply a real-time electrical consumption monitoring system (the e-Gauge system) and utilization of the collected data real-time while a melon-producing smart farm is in operation. For this purpose, the electrical consumption data for the individual smart-farm facilities such as boilers, nutrient distribution systems, automatic controllers, circulation fans, boiler controllers, and other IoT-related utilities were collected during three months of melon cultivation period. By using the monitoring results, the electrical energy consumption pattern was analyzed as an example, and necessary considerations needed to optimally utilize the measurement data were suggested. This paper will be useful in lowering the technological implementation barriers for new researchers to build a electrical consumption monitoring system and reducing trial and errors in the usage of the generated data.

• Journal of Internet of Things and Convergence
• /
• v.3 no.1
• /
• pp.13-19
• /
• 2017

In this paper, we designed and implemented Thing Connected-Green, a self-installing agricultural automation system capable of remote monitoring and control based on Low Power Wide Area communication technology (LPWA). Farming requires water, sunlight, soil, fertilizer, temperature control, etc., and these elements can be remotely monitored and controlled using an automated system. Using this system, it is possible to construct an agricultural automation system which can be optimized according to the kind of plant and cultivation environment from vinyl house to flower garden. The information gathered from the sensor is stored in the server through the gateway, and the optimal cultivation environment can be set and operated using the smart phone based on the big data.

• Smart Media Journal
• /
• v.7 no.1
• /
• pp.45-51
• /
• 2018

Avian influenza (AI) is notorious for its rapid infection rate, and has a serious impact on consumers and producers alike, especially in poultry farms. The AI outbreak, which occurred nationwide at the end of 2016, devastated the livestock farming industries. As a result, the prices of eggs and egg products had skyrocketed, and the event was reported by the media with heavy emphasis. The purpose of this study was to investigate the correlation between the egg price fluctuation and the keyword changes in online news articles reflecting social issues. To this end, we analyzed 682 cases of AI-related online news articles for fourteen weeks from November 2016 in South Korea. The results of this study are expected to contribute to understanding the relationship between the actual price of eggs and the keywords from news articles related to social issues.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.4
• /
• pp.695-702
• /
• 2020

Recently, as research on smart farms has been actively conducted, indoor environment control, such as a green house, has reached a high level. However, In the field of forestry where cultivation is carried out in outdoor, the use of ICT is still insufficient. In this paper, we propose LPWA-based forest growth environment collection and big data analysis system using ICT technology. The proposed system collects and transmits the field cultivation environment data to the server using small solar power generation and LPWA technology based on the oneM2M architecture. The transmitted data is constructed as big data on the server and utilizes it to predict the production and quality of forest products. The proposed system is expected to contribute to the production of low-cost, high-quality crops through the fusion of renewable energy and smart farms. In addition, it can be applied to other industrial fields that utilize the oneM2M architecture and monitoring the growth environment of agricultural crops in the field.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1183-1194
• /
• 2021

Traditionally, electric power systems have been known as the centralized structures, which is organized into placing customers at the end of the supply chain. However, recent decades have witnessed the emergence of distributed energy resources(:DERs) such as rooftop solar, farming PV system, small wind turbines, battery energy storage systems and smart home appliances. With the emergence of distributed energy resources, the role of distributed system operators(:DSOs) will expand. The increasing penetration of DERs could lead to a less predictable and reverse flow of power in the system, which can affect the traditional planning and operation of distribution and transmission networks. This raises the need for a change in the role of the DSOs that have conventionally planned, maintained and managed networks and supply outages. The objective of this research is to designed the future distribution operation system with multi-DERs and the proposed distribution system model is implemented by hardware-in-the-loop simulation(HILS). The test results show the normal operation domain and reduction of distribution line loss.