• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.4
• /
• pp.28-34
• /
• 2010

In this paper, we proposed an algorithm for utilizing visual information for non-contact predicting method of friction coefficient. Coefficient of friction is very important in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. The proposed method, non-contacting approach, has advantage over other methods that extract material characteristic of road by sensors contacting road surface. This method is composed of learning group(experiment, grouping material) and predicting friction coefficient group(Bayesian classification prediction function). Every group include previous work of vision. Advantage of our algorithm before entering such terrain can be very useful for avoiding slippery areas. We make experiment on measurement of friction coefficient of terrain. This result is utilized real friction coefficient as prediction method. We show error between real friction coefficient and predicted friction coefficient for performance evaluation of our algorithm.

• Journal of KIISE
• /
• v.45 no.1
• /
• pp.36-44
• /
• 2018

Due to the advent of the 4th Industrial Revolution, it is imperative that we aggressively continue to develop state-of-the-art, cutting edge ICT technology relative to autonomous vehicles, intelligent robots, and so forth. Especially, systems based on convergence IT are being developed in the form of CPSs (Cyber Physical Systems) that interwork with sensors and actuators. Since conventional CPS specification only expresses behavior of one system, specification for collaboration and diversity of CPS systems with characteristics of hyper-connectivity and hyper-convergence in the 4th Industrial Revolution has been insufficiently presented. Additionally, behavioral modeling of CPSs that considers more collaborative characteristics has been unachieved in real-time application domains. This study defines the non-functional requirements that should be identified in developing embedded software for real-time constrained collaborating CPSs. These requirements are derived from ISO 25010 standard and formally specified based on state-based timed process. Defined non-functional requirements may be reused to develop the requirements for new embedded software for CPS, that may lead to quality improvement of CPS.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.10
• /
• pp.415-424
• /
• 2019

In this paper, a minimum rotation radius was designed and fabricated to overcome the threshold so that elderly or disabled people who have difficulty moving can move and transfer safely and conveniently in a narrow room. In the indoor environment, where the sedentary culture develops, this study aimed to provide convenience for passengers with fracture diseases, geriatric diseases, and other knee and waist diseases. First, links, seats, armrests, covers, motors, batteries, chargers, controllers, etc. were attached to the frame so that they could be moved and lifted indoors. The product design and structure were designed considering the user's environment and physical characteristics, and IoT functions were added. A driving experiment was performed to confirm the operating performance of the manufactured indoor moving and lifting wheelchair. The performance tests, such as continuous running time, turning radius, maximum actuator load, maximum lift height, sound pressure level, minimum sensing distance of the driving aid sensor, interworking of server and app programs, device compatibility, and duty cycle error rate, were performed. As a result of the test, the built-in wheelchair could achieve the performance test target of each item and operate successfully.

• The Journal of the Korea Contents Association
• /
• v.21 no.9
• /
• pp.149-163
• /
• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.91-103
• /
• 2022

Determination of sound source characteristics such as: sound volume, direction and distance to the source is one of the important techniques for unmanned systems like autonomous vehicles, robot systems and AI speakers. There are multiple methods of determining the direction and distance to the sound source, e.g., using a radar, a rider, an ultrasonic wave and a RF signal with a sound. These methods require the transmission of signals and cannot accurately identify sound sources generated in the obstructed region due to obstacles. In this paper, we have implemented and evaluated a method of detecting and identifying the sound in the audible frequency band by a method of recognizing the volume, direction, and distance to the sound source that is generated in the periphery including the invisible region. A cross-shaped based sound source recognition algorithm, which is mainly used for identifying a sound source, can measure the volume and locate the direction of the sound source, but the method has a problem with "blind spots". In addition, a serious limitation for this type of algorithm is lack of capability to determine the distance to the sound source. In order to overcome the limitations of this existing method, we propose a QRAS-based algorithm that uses rectangular-shaped technology. This method can determine the volume, direction, and distance to the sound source, which is an improvement over the cross-shaped based algorithm. The QRAS-based algorithm for the OSSD uses 6 AITDs derived from four microphones which are deployed in a rectangular-shaped configuration. The QRAS-based algorithm can solve existing problems of the cross-shaped based algorithms like blind spots, and it can determine the distance to the sound source. Experiments have demonstrated that the proposed QRAS-based algorithm for OSSD can reliably determine sound volume along with direction and distance to the sound source, which avoiding blind spots.

• Journal of Adhesion and Interface
• /
• v.24 no.3
• /
• pp.95-99
• /
• 2023

In this study, LiDAR-detectable black materials are synthesized by coating and reduction of titanium dioxide onto plate-type natural mica, which evaluated practical LiDAR verification. In detail, black TiO₂@Mica materials are fabricated by utilizing a sol-gel reaction to coat titanium dioxide onto natural mica, followed by reduction using sodium tetrahydridoborate. Subsequently, Black TiO₂@Mica materials are dispersed in hydrophilic transparent varnish and sprayed onto the glass substrate to assess applicability as paints. As a result, Black TiO₂@Mica-based paints exhibit true blackness (L^*=12.1) and a higher NIR reflectance (30.2 R%). In addition, it was confirmed that as-synthesized Black TiO₂@Mica materials are successfully recognized by a LiDAR sensor. This phenomenon is attributed to Fresnel's reflection law, in which light reflection occurs at the interface between natural mica and titanium dioxide with different refractive indices. In this regard, the findings of the study are expected to contribute to the potential utilization of LiDAR-detectable materials in various fields such as autonomous vehicles, robotics, and drones.

• Journal of Appropriate Technology
• /
• v.7 no.2
• /
• pp.127-135
• /
• 2021

To respond to the threat of global warming, countries around the world are promoting the spread of renewable energy and reduction of carbon emissions. In accordance with the United Nation's Sustainable Development Goal to combat climate change and its impacts, global automakers are pushing for a full transition to electric vehicles within the next 10 years. Electric vehicles can be a useful means for reducing carbon emissions, but in order to reduce carbon generated in the stage of producing electricity for charging, a power generation system using eco-friendly renewable energy is required. In this study, we propose a smart electric mobility operating system integrated with off-grid solar power plants established in Tanzania, Africa. By applying smart monitoring and communication functions based on Arduino-based computing devices, information such as remaining battery capacity, battery status, location, speed, altitude, and road conditions of an electric vehicle or electric motorcycle is monitored. In addition, we present a scenario that communicates with the surrounding independent solar power plant infrastructure to predict the drivable distance and optimize the charging schedule and route to the destination. The feasibility of the proposed system was verified through test runs of electric motorcycles. In considering local environmental characteristics in Tanzania for the operation of the electric mobility system, factors such as eco-friendliness, economic feasibility, ease of operation, and compatibility should be weighed. The smart electric mobility operating system proposed in this study can be an important basis for implementing the SDGs' climate change response.