• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.149-154
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• 2013

IoT is emerging topic of the post-smartphone era. But IoT service is actually not easy but due to the absence of the open standard IoT service platform. In this study, We propose and implement IoT services platform using commercial SNS platform like Tweet, Facebook or YouTube. we implement the intelligent control system of the urban farm using our IoT services platform as an example. Our system can save an additional server deployment and management cost using open SNS platform like Tweet or Facebook or Youtube. In addition, there are needs to develop App. for the smartphone because we can take advantage of the user interface which is developed by global enterprises.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.145-152
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• 2020

In this paper, we propose the Crop Classification Management System (CCMS) that detects changes in growth environment to improve crop production rate. The CCMS consists of two modules. First, the Crop Classification Module (CCM) classifies crops through CNN. Second, the Farm Anomaly Detection Module (FADM) detects abnormal crops by comparing accumulated data of farms. The CCM recognizes crops currently grown on farms and sends them to the FADM, and the FADM picks up the weather data from the past to the present day of the farm growing the crops and applies them to the Nelson rules. The FADM uses the Nelson rules to find out weather data that has occurred and adjust farm conditions through IoT devices. The performance analysis of CCMS showed that the CCM had a crop classification accuracy of about 90%, and the FADM improved the estimated yield by up to about 30%. In other words, managing farms through the CCMS can help increase the yield of smart farms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.43-52
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• 2018

Livestock production is the second largest economic activity of Pakistan's rural population, more specifically; sixty-seven percent of Pakistan's total population that live in rural areas sources their income from livestock activities. As this subsector of agriculture within rural Pakistan is so critical to Pakistan's economy it is especially important to further develop the sector through the introduction of cost effective, efficient, and practical technologies. In an effort to improve such an important sector within the agriculture sector in Pakistan research has been carried out to better understand the capabilities and feasibility of leveraging Internet of Things based technologies, such as, microprocessors and microcontrollers within Pakistan's livestock production and management. The internet of Things can potentially allow for the scaling of small-scale rural livestock production to larger operations through cost effective and efficient livestock management through the application of IoT technologies. This paper discusses the architecture models of IoT based smart animal farms and delves into the pitfalls and advantages of applying IoT technologies in this sector. In this work we will explore the cheap sensors to monitor the internal activities of cattle farm with the aim of using these sensors as part of system to detect the important operations that need on the time response. This system should provide the feed and water as required, and control the temperature in sheds to protect the cattle being ill and on heat, and humidity level .internet connection used to connect these devices with smartphones or computers. In this paper we proposed the architecture model of IoT based smart animal farm.

• 대한공업교육학회지
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• v.43 no.1
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• pp.158-176
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• 2018

The purpose of this study is to analyze the satisfaction of the manufacturing process and the satisfaction of manufacturing lesson in the lesson of model product manufacturing based on IoT(Internet of Things) for pre-service technology teachers. and we also analyzed 'smart farm' model production manufacturing among various products. The survey questionnaires with 8 questions to investigate satisfaction level of model manufacturing process, difficulties in manufacturing, and the satisfaction level of manufacturing lesson were collected from the 15 pre-service technology teachers and analyzed by using SPSS program. and The results of this study were as follows: First, the lesson satisfaction average level of pre-service technology teachers was high(M=4.22) in model product manufacturing process for the 'smart farm' model making based on the IoT. Second, the average satisfaction level of 'patent search and prior art search report writing education' was as high as 4.07. Therefore, the application of 'prior art search report writing education' showed that it helped to make the product. Third, the best high satisfaction level in the model production manufacturing procedure was 'education of inventive thinking method'(M=4.40). Therefore, the pre-service technology teachers showed that the 'education of inventive thinking methods' was very helpful from the idea design to the optimal selection of idea. The next order of satisfaction level was high(M=4.33) in 'design education and counseling' and 'guidance through selection of professor who guide the production manufacturing in addition to professors who are in charge of lesson'. Because they were helpful in solving the lack of knowledge of pre-service technology teachers. Fourth, satisfaction level with 'the presentation of model making results and exhibitions', 'presentations and participations of external event' was high (M = 4.13). Although the results of interviews with pre-service technology teachers showed that they suffered from lack of knowledge in various technologies, but it was an opportunity to learn things and felt a sense of accomplishment.

• Smart Media Journal
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• v.3 no.1
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• pp.16-21
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• 2014

The demand for food rises proportionally as population grows. To be able to achieve sustainable supply of livestock products, efficient farm management is a necessity. With the advancement in technology it also brought innovations that could be harness in order to achieve better productivity in animal production and agriculture. Precision Livestock Farming (PLF) is a budding concept of making use of smart sensors or available devices to automatically and continuously monitor and manage livestock production. With this concept, this paper introduces a swine management system that integrates image processing technique for weight monitoring. This system captures pig images using camera, evaluate and estimate the weight base on the captured image. It is comprised of Pig Module, Breeding Module, Health and Medication Module, Weighr Module, Data Analysis Module and Report Module to help swine farm administrators better understand the performance and situation of the swine farm. This paper aims to improve the management in both small and big livestock raisers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.376-378
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• 2021

According to the 2020 Global Climate Report released by the World Meteorological Organization, the average temperature of the Earth in 2019 was measured 1.1℃ higher on average than the temperature measured between 1850 and 1900 before industrialization. The change in average temperature affects the distribution of plants, and according to the vulnerability analysis paper, it can be seen that there is a change in the distribution area of plants when the average temperature rises. In this paper, to cope with these environmental changes, we propose a method of fabricating intermittent flow hydroponic smart farms using Arduino and sensors and controlling them through PCs and applications. The manufactured hydroponic smart farm identifies the farm's temperature and humidity, positive pH concentration, illumination, and water quality to check the amount of pumping, supplement LED control, sensor condition, overall management and cultivation of the farm, and grows in an appropriate environment.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.313-318
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• 2016

Recently, the smart farm development using a PC and smart phone to manag the farm for improving competitiveness is in progress. In the smart farm, by using the various ICT technology including RFID, Wi-Fi, ZigBee, Wireless LAN, and etc., the growing environment of the crop and animals can be managed with the remote. By using the network including not only the TCP/IP based wired network but also ZigBee, Wireless LAN, and etc., each of the devices installed in the smart farm transmits the growing environment data to the server. So, smart farms have information and network security vulnerability. Therefore, we propose the method that analyzes the security vulnerability which can begenerated in the smart farm and user authentication method.

• Smart Media Journal
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• v.13 no.1
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• pp.18-23
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• 2024

Power efficiency management in smart farms is important due to its link to climate change. As climate change negatively impacts agriculture, future agriculture is expected to utilize smart farms to minimize climate impacts, but smart farms' power consumption may exacerbate the climate crisis due to the current electricity production system. Therefore, it is essential to efficiently manage and optimize the power usage of smart farms. In this study, we propose a system that monitors the power usage of smart farm equipment in real time and predicts the power usage one hour later using GRU. CT sensors are installed to collect power usage data, which are analyzed to detect and prevent abnormal patterns, and combined with IoT technology to efficiently manage and monitor the overall power usage. This helps to optimize power usage, improve energy efficiency, and reduce carbon emissions. The system is expected to improve not only the energy management of smart farms, but also the overall efficiency of energy use.

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

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