• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

• Journal of Food Hygiene and Safety
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• v.34 no.6
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• pp.542-550
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• 2019

To detect Escherichia coli from agri-food and production environments, a device based on IoT (internet of things) technology that can check test results in real time on a mobile phone has been developed. The efficiency of the developed device, which combines an incubator equipped with a UV lamp, a high-resolution camera and software to detect E. coli in the field, was evaluated by measuring the device's temperature, detection limit, and detection time. The device showed a difference between its programmed temperature setting and actual temperature of about 1.0℃. In a detection limit test performed with a single-colony inoculation, a color change to yellow and a florescent signal were detected after 12 and 15 h incubations, respectively. The incubation time also decreased along with increasing bacteria levels. When applying the developed method and device to various samples, including utensils, gloves, irrigation water, seeds, and vegetables, detection rates of E. coli using the device were higher than those of the Korean Food Code method. These results show that the developed protocol and device can efficiently detect E. coli from agri-food production environments and vegetables.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.442-454
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• 2017

As the demand for meat products has steadily increased in Korea, so the livestock industry has full grown. However, the opening of import meat products is taking a toll on the local industry. Cost reduction on livestock feed, which comprises the majority of costs involved in the industry is urgent to gain a competitive edge. As Internet of Things (IoT) technologies are being applied across a multiple of industries, so are the cases of applied Smart Farm technology for efficient production. The following research aims to utilize IoT technologies to measure, in real time, the rate of depletion of feed and remaining amount and to propose an effective automated reorder & delivery system. First, a method of utilization of ultrasonic and temperature/humidity sensors to obtain corresponding data of remaining feed in the Feedbin is proposed. In addition, a method of sending the obtained data via on-the-farm gateway to Supply Chain Management (SCM) servers is proposed. Finally, utilization of the stored data to construct an automated reorder & delivery service system is proposed. It is in the researcher's intention to contribute to and enable the local livestock industry with the application of various IoT services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1228-1236
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• 2018

Recently, the maritime environment contaminated by the abandoned fishing gears. To solve this problem, there requires systematic management techniques for the fishing gears based on ICT technologies. The existed systems are optionally used by owners, but the systems need to adopt the monitoring and control architecture for integrated national surveillance. To do this, we designed an architecture for effective monitoring and management which collects position and state information using automatic identification buoy (AIB) device, to send the fishing ship, administrator ship, and shore side control center based on the IoT networks. Especially, in this paper, we developed the ENC-based integrated control system for efficient management which provides functions for position indication, state information display and loss alarm of fishing gears. Also, we conduct performance tests for data processing and visualization functions of the system to use a virtual buoy generation module.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.611-618
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• 2020

The reliability of the results of LCC analysis is determined by accurate analytical procedures and energy data from which the uncertainty is removed. Until now, systems that can automatically measure these energy data and produce databases have not been commercialized. Therefore this paper proposes a concept model of an S-LCC platform that can automatically collect and analyze electric energy consumption data of equipment systems using the IOT, which is the core tool in the Fourth Industrial Revolution and operates the equipment system efficiently using the analyzed results. The proposed concept model was developed by the convergence of existing BLCS and IOT and was comprised of five modules: Facility Control Module, LCC Analysis Module, Energy Consumption Control Module, Efficiency Analysis Module, and Maintenance Standard Reestablishment Module. Using the results of LCC analysis deduced from this system, the deterioration condition of an equipment system can be identified in real-time. The results can be used as the baseline data to re-establish standards for the maintenance factor, replacement frequency, and lifetime of existing equipment, and establish new maintenance standards for new equipment. If the S-LCC platform is established, it would increase the reliability of LCC analysis, reduce the labor force for entering data and improve accuracy, and would also change disregarded data into big data with high potential.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.11-20
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• 2014

For Web-based applications in IoT environment, IETF CoRE WG has standardizing the CoAP. One of limitations of CoAP is that CoAP standard does not consider the mobility management of the CoAP sensor node. In this paper, we propose the mobility management protocol of CoAP sensor node by considering the characteristics of the constrained network. The proposed mobility management protocol supports for Web client to be transmitted the sensing data from CoAP node reliably while the CoAP sensor moves into different wireless networks. To do this, we designed the architecture with the separate IP address management of CoAP sensor node and presented the mobility management protocol, which includes the holding and binding mode, in order to provide the reliable transmission. Finally, the numerical analysis and simulation with NS2 tool have been done for the performance evaluation in terms of the handover latency and packet loss with comparing the proposed mobility management protocol with other the existing mobility management protocols. The performance result shows that the proposed mobility management can provide the transmission of sensing data without the packet loss comparing with the existing mobility management protocol reliably.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.11
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• pp.44-52
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• 2011

In this article, we present a QoS-guaranteed IP mobility management scheme of Internet service for fast moving vehicles with multiple wireless network interfaces. The idea of the proposed mechanism consists of two things. One is that new wireless connections are established to available wireless channels whenever the measured data rate at the vehicle equipped with mobile gateway drops below to the required data rate of the user requirement. The other is that parallel distribution packet tunnels between an access router and the mobile gateway are dynamically constructed using multiple wireless network interfaces in order to guarantee the required data rate during the mobile gateway's movement. By doing these methods, the required data rate of the mobile gateway can be preserved while eliminating the possible delay and packet loss during handover operation, thus resulting in the guaranteed QoS. The architecture of the IETF standard HMIPv6 has been extended to realize the proposed scheme, and detailed algorithms for the extension of HMIPv6 has been designed. Finally, simulation has been done for performance evaluation, and the simulation results show that the proposed mechanism demonstrates guaranteed QoS during the handover with regard to the handover delay, packet loss and throughput.

• 재활복지
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• v.18 no.4
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• pp.221-235
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• 2014

Recently, the frequency of stroke disease is increased due to the rapid aging population, and is contributed to the major occurrence factors of the posteriori acquired disability. This study is about an postural change device for the control of supine posture which is an assisted equipment using in daily rehabilitation process for overcoming the disability by the aftereffects of the stoke disease. In this paper, the existing domestic and Japan postural appliances is examined and its comparison and categorization is performed according to its functions and purposes. Here, in order to control the supine posture state, the design method for advanced multi functional system is proposed, which is devised to have an unified mattress control operations of combining the bedsore prevention tube with the supine posture tilting tube. And also, in addition of an smart function, it is designed to enable to perform an RF functions such as the monitoring of the present device state, the alteration of the basic position and the control of alternative floating and supine posture. This system control hardware consists of three main parts : the sensor detection part, the motor driving /control part, and the system control part for bluetooth communication. In results, we confirmed that the system designed by this research is possible to make it practical as an advanced smart postural change device combined by IoT technology in the application field of the recent IT technology.

• Journal of Science Education
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• v.46 no.3
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• pp.223-236
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• 2022

The purpose of this study is to investigate pre-service elementary teachers' awareness on the sources of microplastics. The participants were 75 male and 91 female undergraduates. A 15-item survey questionnaire was developed based on prior researches regarding microplastics emission sources and were modified through expert review and preliminary research. The survey results show that over 80% of the respondents had heard of microplastics before through news, internet, TV, etc. However, they tended not to be aware that things such as lab coats, wet tissue, dust protective mask, or paper cup were made of microplastics-causing substances. For the questions on the expected situation of microplastics contamination, the frequency of their choices were relatively low in 'Tires of cars running are worn out' and 'The gum stuck to the floor becomes smaller.' These results show that many of them were not aware that synthetic fiber or synthetic rubber was one of the microplastics emission sources. Gender differences were found in the attitudes toward microplastics problems. Female students are more interested in the issues and are more willing to participate in the solution, and recognize the need for more education on microplastics. The implications and future directions for science education were discussed.