• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.9-17
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• 2023

Deep learning with large amount of computations is difficult to implement on micro-sized IoT devices or moblie devices. Recently, lightweight deep learning technologies have been introduced to make sure that deep learning can be implemented even on small devices by reducing the amount of computation of the model. Quantization is one of lightweight techniques that can be efficiently used to reduce the memory and size of the model by expressing parameter values with continuous distribution as discrete values of fixed bits. However, the accuracy of the model is reduced due to discrete value representation in quantization. In this paper, we introduce various quantization techniques to correct the accuracy. We selected APoT and EWGS from existing quantization techniques, and comparatively analyzed the results through experimentations The selected techniques were trained and tested with CIFAR-10 or CIFAR-100 datasets in the ResNet model. We found out problems with them through experimental results analysis and presented directions for future research.

• KNOM Review
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• v.22 no.2
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• pp.29-38
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• 2019

The rapid growth of IoT (Internet of Things) owing to the advancement and spread of technologies such as wireless networks, communication modules, sensors, smart terminals, etc. enables the development of new services in diverse public and private sectors. In particular, research on IoT technology and its applications has increased in the field of science. To establish an IoT infrastructure in this field, KREONET launched the wireless IoT network, called ScienceLoRa, based on low power wide area network (LPWAN). ScienceLoRa aims to collect a variety of data from sensors and utilize and analyze the collected data for research in a variety of scientific fields. In this article, the authors present the concept, current status, applications and future plans of ScienceLoRa.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.95-102
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• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.175-188
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• 2017

Radio-frequency identification (RFID) is being used in various fields as a technology for identifying objects (people, things etc.) using radio frequencies. In the past, there was an attempt to apply RFID into national defense, but failed to spread RFID in the defense field because of some limitations of RFID in a specific situation (e.g., low recognition rate). Therefore, in this paper, we propose how to overcome the limitation of RFID by adopting the Internet of Things (IoT) technology which is considered as an important technology of the future. Furthermore, we propose four scenarios (i.e., healcare band and RFID, identification and anormal state detection, access control, and confidential document management) that can be used for enhancing national defense security. In addition, we analyze the basic characteristics and security requirements of RFID and IoT in order to effectively apply each technology and improve security level.

• Design Convergence Study
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• v.15 no.2
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• pp.237-250
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• 2016

Along with rapid development, progress of the network technology and digital information technology, human are stepping into the intelligent society of internet. Thereby the quality of living environment and working environment are keep improving. Under the big background of internet era, the timeliness and convenience of smart home system has been improved greatly. While lots of smart products have gradually penetrated into people's daily life. The household appliances are among most popular ones. This paper is intended to compare smart features of household living products among most representative brands in China, Japan and South Korea. The smart features include self-learning, self-adapting, self-coordinating, self-diagnosing, self-inferring, self-organizing, and self adjusting. As result, most smart features of these products showed great similarity. While some features were dominated according to countries such as remote control feature in Korea, energy saving feature in Japan, and one button operation feature in China.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.610-632
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• 2024

Mobile Learning (M-learning) adoption and success in supporting students' learning engagement mainly depend on many factors. Therefore, this study systematically reviews the literature, synthesizes and analyzes the predictors of M-learning adoption, and uses success for students' learning engagement. Literature from 2016 to 2023 in various databases is covered in this study. Based on the review's findings, the factors that influence students' learning engagement when it comes to M-learning usage and adoption, can be divided into technical, pedagogical, and social factors. More specifically, technical factors include mobile devices availability and quality, connectivity to the internet, and user-friendly interfaces, pedagogical factors include effective instructional design, teaching methods, and assessment strategies, and social factors include motivation of students, social interaction and perceived enjoyment - all these factors have a significant impact on the M-learning adoption and use success. The findings of the review also indicated that M-learning has a key role in enhancing the learning engagement of students through different ways, like increasing their motivation, attention, and participation in their process of learning, paving the way for interaction and building relationships opportunities with peers and instructors, which in turn, can lead to strengthening the learning environment. The implications of these findings extend beyond immediate educational contexts, offering vital insights for future educational technology strategies and policy decisions, particularly in addressing global educational challenges and embracing technological advancements in learning.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.10-21
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• 2024

Recently, audio systems are changing the configuration of conventional sound reinforcement (SR) systems and public address (PA) systems by using audio over IP (AoIP), a technology that can transmit and receive audio signals based on internet protocol (IP). With the advancement of IP technology, AoIP technologies are leading the audio market and various technologies are being released. In particular, audio networks and control hierarchy over peer-to-peer (Anchor) technology based on AoIP is a system that transmits and receives audio signals over a wide bandwidth without an audio mixer, creating a novel paradigm for existing audio system configurations. Anchor technology forms an audio system by connecting audio sources and output equipment with On-site audio center (OAC), a device that can transmit and receive IP. Anchor's receiving OAC is capable of receiving and mixing audio signals transmitted from different IPs, making it possible to configure a novel audio system by replacing the conventional audio mixer. However, Anchor technology does not have the ability to provide audio effects to input devices such as microphones and instruments in the audio system configuration. Due to this, when individual control of each audio source is required, there is a problem of not being able to control the input signal, and it is impossible to individually affect a specific input signal. In this paper, we implemented a tone control module that can individually control the tone of the audio source of the input device using the audio processor core in the audio system based on Anchor technology, tone control for audio sources is possible through a tone control module connected to the transmitting OAC. As a result of the study, we confirmed that OAC receives the signal from the audio source, adjusts the tone and outputs it on the tone control module. Based on this, it was possible to solve problems that occurred in Anchor technology through transmitting OAC and tone control modules. In the future, we hope that the audio system configuration using Anchor technology will become established as the standard for audio equipment.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.1-12
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• 2024

Recently, Audio systems transform the configuration of conventional sound reinforcement and public address systems using audio over internet protocol (AoIP), whereby audio signals are transmitted and received based on internet protocol (IP). Currently, AoIP technologies are leading the audio market, and various technologies have been released. Audio networks and the control hierarchy over peer-to-peer (Anchor) technology based on AoIP transmit and receive audio signals over a wide bandwidth without an audio mixer. Audio system based on Anchor technology is constructed by connecting the on-site audio center (OAC), a device that can transmit and receive audio sources and output equipment over IP. Receiving OAC of the Anchor technology can receive and mix audio signals transmitted from different IPs; consequently, novel audio systems can be configured by replacing conventional audio mixers. However, the Anchor technology does not have an equalizer function for improving the quality of audio equipment. Therefore, tone distortion may occur owing to signal loss between equipment, poor audio-signal clarity, and howling due to audio deformation according to different architectural structures and environments. In this study, we implemented an audio effect device capable of tone control using the Audio Processor Core. Using Anchor technology, tone control was realized through an audio effect device in the receiving OAC. The output of the incoming OAC was received by the audio effect device, which adjusted the tone and then outputted it. Thus, the tone issues in Anchor technology were overcome by the receiving OAC and audio effect devices. In future, audio system configurations using Anchor technology could be the standard for audio equipment.