• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.496-499
• /
• 2016

The smartfarm is a leader in the Field of environmental monitoring in agriculture. By the use of wireless remote systems, monitoring applications of the smartfarm are able to provide vital information to the farmer wherever he may be. Absentee farmers are finding the ease of viewing the application graphs on their mobile phone is providing them with peace of mind. We design system and technical requirements of service for managing and operating smart-farm based on cloud technology. It describes requirements of cloud technology for monitoring, controlling, managing, and operating cloud-based smart farm. Smart farm system and service with cloud platform contains 3 interfaces and 3 services. In addition, smart-farm using cloud platform could have several cases so it should be established and managed in varying way depending on cultivars, its size and type. This paper will focus the industry's attention on the importance of Open/Standard Cloud platform thereby stimulating the smartfarm in agriculture.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.331-337
• /
• 2021

The adaptation of smartfarm technology that converges ICT is increasing productivity and competitiveness in the agriculture. Technologies have been developed that enable environmental monitoring through various sensors and automatic control of the cultivation environment, and researches are underway to advance smartfarm technology using data generated from smartfarms. In this paper, an environmental control method to reduce the energy consumption of a smartfarm by using the environment and control data of the smartfarm is proposed. It was confirmed that energy consumption could be reduced compared to an independent environmental control method by creating an environmental prediction model using accumulated environmental data and selecting a control method to minimize energy consumption in a given situation by considering multiple environmental factors. In the future, research is needed to obtain higher energy efficiency through the advancement of the predictive model and the improvement of the complex control algorithms.

• Korean Journal of Agricultural Science
• /
• v.49 no.1
• /
• pp.151-162
• /
• 2022

This study was conducted to develop a rail-type boom sprayer, performing safe spraying with improved ergonomic postures during pesticide spraying of agro-photovoltaic power system. The sprayer was designed to reduce labor cost and to be safe from pesticide exposure, and was analyzed through a comparison with a conventional spray method. The rail-type boom sprayer, consisted of a self-propelled spray and hose winder, hose, and boom sprayer parts, was designed to automatically pull and spray in the vertical and horizontal directions. The performance of the sprayer for an agro-photovoltaic power system was appropriate. From the analysis of postures with the Ovako Working posture Analysis System (OWAS), Rapid Entire Body Assessment (REBA), and Rapid Upper Limb Assessment (RULA) methods, the musculoskeletal risk factors to the body using the rail-type boom sprayer were less than those with the conventional power sprayer. In addition, the possibility of pesticide poisoning was reduced compared to the conventional power sprayer. The working capacity with the rail-type boom sprayer was more than five times greater, compared with the conventional power sprayer. After performing pesticide spraying with the rail-type boom sprayer, the labor cost was reduced to 42,750 won·yr^-1, which was 90% (402,750 won·yr^-1) less than the cost with the use of a conventional power sprayer (445,500 won·yr^-1).

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.129-136
• /
• 2022

The most important part of the smart livestock building system is to maintain a breeding environment so that livestock can grow to high quality despite changes in the internal and external atmospheric environment. Especially, it is very important to maintain the temperature and humidity in the livestock building because various diseases occur during the summer and winter. To manage the environment suitable for livestock, a smartfarm system for livestock building is applied, but it is very expensive. In this study, we propose a hardware design and control method for low cost system based on HMI and fuzzy control. To evaluate the performance of the proposed system, we did a simulation experiment in the atmospheric conditions of summer and winter. As a result, it showed the performance of minimizing the temperature and humidity stress of livestock. And when applied to the livestock building, the proposed system showed stable control performance even in the change of the external atmospheric environment. Therefore, as with these results, if proposed system in this study is applied to the smart farm system, it will be effective in managing the environment of livestock building.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.01a
• /
• pp.71-72
• /
• 2020

본 논문에서는 시간과 공간의 제약없이 작물의 생육환경을 관측하고 자동 및 원격으로 제어할 수 있는 스마트팜 플랫폼을 설계 및 구현하였다. 스마트팜 플랫폼은 환경 데이터 수집을 위한 다양한 아두이노 센서 모듈, 웹과 데이터베이스 서버, 애플리케이션을 이용한 자동 및 원격 제어, 총 3가지 기술로 구성된다. 사용자가 앱을 통하여 언제 어디에서나 농장 주변의 환경 정보를 조회하고 원격으로 제어하면 농사에 대한 노동력 절감 뿐만 아니라 시간적·공간적 구속으로부터 자유로워져 여유시간도 늘고 삶의 질도 개선될 수 있을 것으로 기대된다.

• Journal of Platform Technology
• /
• v.9 no.4
• /
• pp.42-50
• /
• 2021

Recently, the need to introduce smart farms is increasing in order to solve the problems of intensifying competition such as a decrease in rural population due to aging, a decrease in production, and the inflow of foreign agricultural products, and accordingly, the need for education is increasing. This paper is a study on the implementation of an Android-based IoT smart farm for education so that it can be used in a real environment by reducing the farm's smart farm system. To confirm that Android-based education can be applied in a real environment using the IoT smart farm for education, experiments were performed in automatic mode and manual mode using Bluetooth, Wi-Fi, and server/client communication methods. In the automatic mode, the current status can be checked in real time by receiving all data, and in the manual mode, commands are transmitted in real time using the received sensor data and remote control is performed. As a result of the experiment, it was possible to understand the characteristics of each communication method, and it was confirmed that remote monitoring and remote control of the smart farm using the Android App was possible.

• Journal of Bio-Environment Control
• /
• v.32 no.3
• /
• pp.190-196
• /
• 2023

This study was carried out to collect gas emitted from agricultural heaters using kerosene and to identify the emission concentration of carbon dioxide according to the age of agricultural heating machine. As a result of the linear regression analysis, the carbon dioxide emissions according to the year of agricultural heating machine are R² = 0.84, which follows y = 26.99x+721.98. Distributed analysis was classified into three groups according to the age of agricultural heating machine. As a result of the distributed analysis, it was 2.196×10^-13, which was smaller than the 0.05 probability set for the analysis, which means that there is a difference in at least one group. As a result, the age of the agriculture machine was divided into three groups and the difference between groups was tested. A statistical analysis result was derived that there was a difference in the emission concentration of carbon dioxide according to the age of agricultural heating machine. It is thought that it can be used to investigate greenhouse gas emissions by investigating the amount of carbon dioxide generated by agricultural heaters in the agricultural field of Korea.

• Smart Media Journal
• /
• v.11 no.5
• /
• pp.26-37
• /
• 2022

In this paper, images are automatically acquired to control the initial disease of strawberries among facility cultivation crops, and disease analysis is performed using the EfficientNet model to inform farmers of disease status, and disease diagnosis service is proposed by experts. It is possible to obtain an image of the strawberry growth stage and quickly receive expert feedback after transmitting the disease diagnosis analysis results to farmers applications using the learned EfficientNet model. As a data set, farmers who are actually operating facility cultivation were recruited and images were acquired using the system, and the problem of lack of data was solved by using the draft image taken with a cell phone. Experimental results show that the accuracy of EfficientNet B0 to B7 is similar, so we adopt B0 with the fastest inference speed. For performance improvement, Fine-tuning was performed using a pre-trained model with ImageNet, and rapid performance improvement was confirmed from 100 Epoch. The proposed service is expected to increase production by quickly detecting initial diseases.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.1
• /
• pp.93-100
• /
• 2023

In this paper, the purpose of this study is to melt the process of returning to farming through games and settle down in a stable manner to ensure that there are no more prospective young farmers who wish to return to farming but cannot proceed with their dreams due to various barriers of reality. The game was designed to develop in the order of fields, greenhouses, automation systems, and smart farms, and to grow the crops they want at the early level, and added a community system to highlight that rural areas are community life, not individualistic life. Support benefits or information provided by local governments or governments were inserted into the community system so that prospective farmers could naturally access the information.

• Journal of Software Assessment and Valuation
• /
• v.17 no.1
• /
• pp.83-92
• /
• 2021

There are continuous and tremendous attempts to apply various sensor systems and ICTs into the dairy science for data accumulation and improvement of dairy productivity. However, these only concerns the fields which directly affect to the dairy productivity such as the number of individuals and the milk production amount, while researches on the physiology aspects of dairy cows are not enough which are fundamentally involved in the dairy productivity. This paper proposes the basic approach for extraction of daily behavior pattern from hourly behavioral data of dairy cows to identify the health status and stress. Total four clusters were grouped by k-means clustering and the reasonability was proved by visualization of the data in each groups and the representatives of each groups. We hope that provided results should lead to the further researches on catching abnormalities and disease signs of dairy cows.