• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.137-142
• /
• 2022

Every year, the number of wild animals appearing in human settlements increases, resulting in increased damage to property and human life. In particular, the damage is more severe when wild animals appear on highways or farmhouses. To solve this problem, ecological pathways and guide fences are being installed on highways. In addition, in order to solve the problem in farms, horn repelling using sensors, installing a net, and repelling by smell of excrement are being used. However, these methods are expensive and their effectiveness is not high. In this paper, we used YOLO (You Only Look Once), an AI-based image analysis method, to analyze harmful animals in real time to reduce malfunctions, and high-brightness LEDs and ultrasonic frequency speakers were used as extermination devices. The speaker outputs an audible frequency that only animals can hear, increasing the efficiency to only exterminate wild animals. The proposed system is designed using a general-purpose board so that it can be installed economically, and the detection performance is higher than that of the devices using the existing sensor.

• Journal of Korea Multimedia Society
• /
• v.25 no.4
• /
• pp.559-567
• /
• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• Journal of the Korean Society of Systems Engineering
• /
• v.20 no.spc1
• /
• pp.108-118
• /
• 2024

As shared electric kick scooters spread to cities worldwide as a result of the proliferation of personal mobility, they have emerged as a significant social issue, impacting pedestrian and user safety, as well as urban aesthetics. In this study, we propose solutions to the unique problems associated with shared electric kick scooters, such as illegal parking, charging, and redistribution. Furthermore, we present research on supplementary services utilizing electric kick scooters in urban areas to enhance citizen safety and user satisfaction through the development of an autonomous electric kick scooter system structure and operational strategies. We suggest a low-cost autonomous electric kick scooter structure and propose AI processing, sensor fusion, and system operation methods to add autonomous capabilities to affordable electric kick scooters. Additionally, we propose operational systems and related technologies for offering various supplementary services.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.35 no.2
• /
• pp.155-159
• /
• 2022

Smart livestock, which combines information and communication technology (ICT) with livestock, can be said to be an effective solution to existing livestock problems such as productivity improvement, odors, and diseases. So far, it has hardly been universalized; thus, it is necessary to develop automation devices to reduce labor by localizing automation devices to expand the distribution of ICT technology to farms, and to advance precise specifications and health management technology using biometric information. Weighing scales currently being used in livestock farms are to prevent the spread of diseases by diagnosis and preparation for AI and other diseases in advance, using information on the growing weight of duck breeding. However, accurate values cannot be obtained due to poor breeding conditions. In this paper, we developed a separate data transmission system kit for the weighing scale and placed the sensor on top of the weighing scale so that the sensor wire is not affected by pollutants or ducks on the floor. A display function was provided, and a method of receiving and analyzing the serial port data of the weighing device, and then transmitting them to the data collection server was implemented.

• Journal of Internet of Things and Convergence
• /
• v.9 no.2
• /
• pp.61-69
• /
• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.3
• /
• pp.83-90
• /
• 2022

Diabetes is a common disease today, and there are also many cases of developing into serious complications called Diabetic Foot Ulcers(DFU). Diagnosis and prevention of DFU in advance is an important task, and this paper proposes the method. Based on existing studies introduced in the paper, it can be seen that foot pressure and temperature information are deeply correlated with DFU. Introduce the process and architecture of SmarTinsole, an IoT device that measures these indicators. Also, the paper describes the preprocessing process for AI-based diagnosis of DFU. Through the comparison of the measured pressure graph and the actual human step distribution, it presents the results that multiple information collected in real-time from SmarTinsole are more efficient and reliable than the previous study.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.07a
• /
• pp.427-429
• /
• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.2
• /
• pp.125-130
• /
• 2021

Implementation of livestock smart-farm can be done more effectively with IoT technology developing. An build of useful stock management system can be possibile if push messages of these judgement are notified on smart-phone after cattle's illness and estrus are judged using IoT technology. These judgement method of cattle's illness and estrus can be done with gathering living stock data using temperature sensor and 3 axis acceleration sensor and sending these data using IoT and internet network into server, and studying AI machine learning using these data. In this paper, to build this cattle management system based on IoT, effective system of the whole architecture is showed. Also an effective analysis and design method to develop this system software will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• Journal of Sensor Science and Technology
• /
• v.29 no.1
• /
• pp.19-26
• /
• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• Convergence Security Journal
• /
• v.18 no.2
• /
• pp.3-10
• /
• 2018

The existing smart grid, which is centered on the power grid, is rapidly spreading to new energy and renewable energy such as heat and gas, which are expressed as smart energy. Smart Energy interacts with electric energy and is connected to wired / wireless network based on IoT sensor based on energy analysis using AI to rapidly expand ecosystem with various energy carriers and customers. However, smart energy based on IoT is lacking in technological and institutional preparation for security compared to efforts to activate the market according to the interests of government and business operators. In this study, we will present Smart Energy 's privacy policy in terms of value system(CPND) of convergence ICT.