• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.235-237
• /
• 2018

최근 IoT 센서 즉, 사물 인터넷 기반 기술에 대한 연구가 많이 진행되고 있으며, 다양한 제품들이 출시되고 있다. 대표적으로 홈 IoT 제품으로 가정에서 인터넷과 스마트폰 어플리케이션을 이용하여 가스 밸브, 보일러, 전등 등을 제어하는 것을 볼 수 있다. 하지만, 농업분야에서는 농작물 생산지의 환경 정보를 수집하고, 그에 맞춰 온습도 등을 제어하기 위해 관리자 혹은 생산자가 수동적으로 처리해야만 하는 단점이 존재하였다. 본 논문에서는 비닐하우스와 축산농가 등에서 사용할 수 있는 IoT 센서 기반 무인 관리 어플리케이션을 설계하고자 한다. 사용자가 비닐하우스 혹은 축산농가에 들어가지 않아도 사용자가 스마트폰 어플리케이션을 통해 모니터링 하면서 온습도를 조절하고, 센서의 고장 유무를 파악하여 교체시기를 알려 주는 등의 기능을 포함 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.1225-1226
• /
• 2012

도시 농업은 도시 과밀로 인한 긴장을 완화시키고 환경과 생태 보전, 경관을 아름답게 꾸미고 색다른 도시문화 형성에 기여도 할 수 있는 다원적인 기능을 제공한다. IT분야에서는 비닐하우스나 옥상녹화 등의 다양한 도시녹화 분야에서 솔루션들을 제공하게 되는데, 규모에 따라 다르지만, 비용이 많이 들어간다는 단점을 가지게 된다. 본 논문에서는 SNS 플랫폼을 저비용의 관리 플랫폼으로 활용할 뿐 아니라 사람들이 텃밭이나 옥상 정원을 통해 공감할 수 있도록 해주는 스마트 농장 관리 시스템을 설계하고 구현하였다.

• 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.

• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.10
• /
• pp.139-145
• /
• 2021

In this paper, by using the cattle feed intake, rumination, and in heat monitoring technology, RFI (Residual Feed Intake) monitoring and wearable devices and PCs for predicting abnormalities in budding target web and smart A monitoring system using a phone application was designed and implemented. With the development of this system, the farmer is expected to increase economic efficiency. By analyzing the feed intake, it is possible to identify the difference between the recommended feed amount based on the cow's weight and the feed amount consumed by the cow, and it is expected that early detection of metabolic disorders (abnormality of metabolism) is possible. Farmers using the results of this thesis can distinguish the cows with the most efficient performance, and the 6-axis motion sensor signals input from the wearable device attached to the cow's skin (neck) and the microphone attached to the wearable device. It is possible to measure the cow's rumination and feed intake through the sound of the cow's throat. In the future, improvements will be made to measure additional vital signs such as heart rate and respiration.

• Smart Media Journal
• /
• v.13 no.6
• /
• pp.16-23
• /
• 2024

Pigs express their reactions to their environment and health status through a variety of sounds, such as grunting, coughing, and screaming. Given the significance of pig vocalizations, their study has recently become a vital source of data for livestock industry workers. To facilitate this, we propose a lightweight deep learning model based on MobileNet that analyzes pig vocal patterns to distinguish pig voices from farm noise and differentiate between vocal sounds and coughing. This model was able to accurately identify pig vocalizations amidst a variety of background noises and cough sounds within the pigsty. Test results demonstrated that this model achieved a high accuracy of 98.2%. Based on these results, future research is expected to address issues such as analyzing pig emotions and identifying stress levels.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.6
• /
• pp.733-739
• /
• 2019

Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.

• Journal of agriculture & life science
• /
• v.46 no.5
• /
• pp.137-141
• /
• 2012

The foot and mouth disease(FMD) was occurred from Andong city on November 23, 2010 and spread out the whole country except Jeju island and Jeolla-do. About 3.4 million livestock such as cow and pig was buired at 4,200 sites during preventive measures of FMD. Government did not effectively respond to the FMD crisis management so FMD spread out the whole country. To Prevent the spread FMD, Farms have to fast approaching and respond directly to smartphones and Tablet PC applications. Resolve the difficulties of using smart devices and easy to operate for the effective utilization of the development of simple applications. This application of FMD, developed for the prevention and alarm applications, foot and mouth disease will be caused, farmers around the farm in case of risk and the seriousness of the FMD will notify smartphone, FMD prevent additional damage due to be interested in preventing further that allows your application is for development purposes.

• Advanced Industrial SCIence
• /
• v.1 no.2
• /
• pp.24-29
• /
• 2022

Recently, smart farm research that applies IoT technology to various farms is being actively conducted to improve agricultural cooling power and minimize cost reduction. In particular, methods for automatically and remotely controlling environmental information data around smart farms through IoT devices are being studied. This paper proposes a processing model that can maintain an optimal growth environment by monitoring environmental information data collected from smart farms in real time based on machine learning. Since the proposed model uses machine learning technology, environmental information is grouped into multiple blockchains to enable continuous data collection through rich big data securing measures. In addition, the proposed model selectively (or binding) the collected environmental information data according to priority using weights and correlation indices. Finally, the proposed model allows us to extend the cost of processing environmental information to n-layer to a minimum so that we can process environmental information in real time.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.1
• /
• pp.15-20
• /
• 2022

With the arrival of the fourth industrial era, demand for agriculture is increasing day by day, and smart farm technology, in which computers manage agriculture in line with the current situation, is developing. However, agricultural workers who use it find it difficult to set up and use a management system for smart farms. This paper aims to establish a Lab-View smart farm management system to facilitate the use of a control program for ICT technology farms (hereinafter referred to as smart farms), one of the promising projects of the next industrial revolution. Based on Lab-View, users simply set the type of crops they want to grow, set appropriate temperature/humidity data for each set crop, and collect data in real time through sensors and store it in DB. This functionality maximizes convenience and usability in terms of users.