• Title/Summary/Keyword: 인공지능산업

Search Result 1,062, Processing Time 0.025 seconds

Study on Development of LED Camping Light Design Based on IOT and Emotional Lighting Contents (IOT 및 감성조명 콘텐츠 기반의 LED 캠핑등 디자인 개발에 관한 연구)

  • Kim, Hee-Jun
    • The Journal of the Korea Contents Association
    • /
    • v.18 no.12
    • /
    • pp.332-342
    • /
    • 2018
  • This study is aimed at suggesting information about technical choices for designing LED camping lights based on emotional lighting contents of integrated IOT and design areas which take a central role in creation and knowledge based industries and the procedure for materializing them. 'i-Light,' a portable LED camping light, is 'connected lighting' connecting men, space and emotion and a smart camping light based on IOT and emotional lighting contents. 'i-Light' has two functions. One is about lighting for adjusting color and color temperature naturally and the other is about safety for detecting harmful gases. 'i-Light' also has various emotional functions for experiencing interaction and taste of light. For the purpose, portable LED camping lights were designed, first of all, and then a highly color rendering/full-color lighting module, a smart sensor module and an IOT device platform were developed. In addition, efforts were made to establish detailed data about emotional lighting contents and to develop a Web application based on them. Finally, prototypes of portable LED camping lights were made to get a test bench and usability evaluation from related organizations. According to the results, all of 12 developed emotional lighting contents and three IOT safety sensors were suitable and prototypes were satisfactory. This paper will suggest a direction about actual technical choices for development of contents and products integrating artificial intelligence and big data and about the procedure for materializing them.

Agent-based Modeling and Analysis of Tactical Reconnaissance Behavior with Manned and Unmanned Vehicles (에이전트 기반 유·무인 수색정찰 전술행위 모델링 및 분석)

  • Kim, Ju Youn;Han, Sang Woo;Pyun, Jai Jeong
    • Journal of the Korea Society for Simulation
    • /
    • v.27 no.4
    • /
    • pp.47-60
    • /
    • 2018
  • Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

A Longitudinal Study on Customers' Usable Features and Needs of Activity Trackers as IoT based Devices (사물인터넷 기반 활동량측정기의 고객사용특성 및 욕구에 대한 종단연구)

  • Hong, Suk-Ki;Yoon, Sang-Chul
    • Journal of Internet Computing and Services
    • /
    • v.20 no.1
    • /
    • pp.17-24
    • /
    • 2019
  • Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

Designing a Platform Model for Building MyData Ecosystem (마이데이터 생태계 구축을 위한 플랫폼 모델 설계)

  • Kang, Nam-Gyu;Choi, Hee-Seok;Lee, Hye-Jin;Han, Sang-Jun;Lee, Seok-Hyoung
    • Journal of Internet Computing and Services
    • /
    • v.22 no.2
    • /
    • pp.123-131
    • /
    • 2021
  • The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

A study on the Increase in Construction Cost for Zero Energy Building (제로에너지건축물의 공사비 증가분 산출에 관한 연구)

  • Shim, Hong-Souk;Lee, Sungjoo
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.22 no.1
    • /
    • pp.603-613
    • /
    • 2021
  • As a core policy for achieving the goal of reducing greenhouse gas emissions in the building sector, Korea has enforced the mandatory certification of zero energy buildings for new public buildings from 2020. This study suggests energy-saving technologies and economic factors that building officials can refer to for decision-making on the implementation of zero energy buildings. For this study, the construction cost for the energy item of a building was analyzed by collecting the building energy efficiency level certification data and detailed construction cost statement data from public institutions for the last three years. Based on the building energy efficiency certification data, each energy item of the baseline building was derived, and the energy performance of the zero energy building was derived through repetitive simulations by gradually increasing the energy performance value of the baseline building. By applying the analyzed construction cost, the construction cost for each energy item of the baseline and zero energy buildings was derived. As a result, the lighting equipment contributed up to 10.5% energy savings, and the increase in construction cost of the cooling and heating system was at least 9.1%.

A Development of Defeat Prediction Model Using Machine Learning in Polyurethane Foaming Process for Automotive Seat (머신러닝을 활용한 자동차 시트용 폴리우레탄 발포공정의 불량 예측 모델 개발)

  • Choi, Nak-Hun;Oh, Jong-Seok;Ahn, Jong-Rok;Kim, Key-Sun
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.22 no.6
    • /
    • pp.36-42
    • /
    • 2021
  • With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

A Study on Atmospheric Data Anomaly Detection Algorithm based on Unsupervised Learning Using Adversarial Generative Neural Network (적대적 생성 신경망을 활용한 비지도 학습 기반의 대기 자료 이상 탐지 알고리즘 연구)

  • Yang, Ho-Jun;Lee, Seon-Woo;Lee, Mun-Hyung;Kim, Jong-Gu;Choi, Jung-Mu;Shin, Yu-mi;Lee, Seok-Chae;Kwon, Jang-Woo;Park, Ji-Hoon;Jung, Dong-Hee;Shin, Hye-Jung
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.4
    • /
    • pp.260-269
    • /
    • 2022
  • In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

A Study on Optimization of Perovskite Solar Cell Light Absorption Layer Thin Film Based on Machine Learning (머신러닝 기반 페로브스카이트 태양전지 광흡수층 박막 최적화를 위한 연구)

  • Ha, Jae-jun;Lee, Jun-hyuk;Oh, Ju-young;Lee, Dong-geun
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.7
    • /
    • pp.55-62
    • /
    • 2022
  • The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

Legal Status and Major Issue of Maritime Autonomous Surface Ships (MASS) in International Law (자율운항선박의 국제법 지위와 주요쟁점에 관한 연구)

  • Chun, Jung-soo;Park, Han-seon
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.27 no.2
    • /
    • pp.256-265
    • /
    • 2021
  • Ground, sea and air mobility, such as vehicles, ships, and airplanes, are generally operated by people. Based on the innovative development of autonomous decision-making systems and artificial intelligence (AI) following the recent fourth industrial revolution, research and development on maritime autonomous surface ships (MASS) is been actively performed around the world. Before the realization of the commercialization of MASS in international maritime transport, it is urgent to clarify the characteristics of this ship and its international legal status. This paper aims to analyze the concern of whether a ship without crew members will eventually be operated as a fully unmanned ship or can be recognized as a ship under international law as the number of crew members is gradually reduced owing to the development stage of autonomous ships. Consequently, based on the United Nations Convention on the Law of the Sea (UNCLOS) and the regulations of the International Maritime Organization (IMO), it was found that MASS has the same international legal status as general ships. In addition this paper presents the working principles of enacting and revising the IMO Conventions and international legal measures necessary for the safe operation of MASS.

A Study on Next-Generation Data Protection Based on Non File System for Spreading Smart Factory (스마트팩토리 확산을 위한 비파일시스템(None File System) 기반의 차세대 데이터보호에 관한 연구)

  • Kim, Seungyong;Hwang, Incheol;Kim, Dongsik
    • Journal of the Society of Disaster Information
    • /
    • v.17 no.1
    • /
    • pp.176-183
    • /
    • 2021
  • Purpose: The introduction of smart factories that reflect the 4th industrial revolution technologies such as AI, IoT, and VR, has been actively promoted in Korea. However, in order to solve various problems arising from existing file-based operating systems, this research will focus on identifying and verifying non-file system-based data protection technology. Method: The research will measure security storage that cannot be identified or controlled by the operating system. How to activate secure storage based on the input of digital key values. Establish a control unit that provides input and output information based on BIOS activation. Observe non-file-type structure so that mapping behavior using second meta-data can be performed according to the activation of the secure storage. Result: First, the creation of non-file system-based secure storage's data input/output were found to match the hash function value of the sample data with the hash function value of the normal storage and data. Second, the data protection performance experiments in secure storage were compared to the hash function value of the original file with the hash function value of the secure storage after ransomware activity to verify data protection performance against malicious ransomware. Conclusion: Smart factory technology is a nationally promoted technology that is being introduced to the public and this research implemented and experimented on a new concept of data protection technology to protect crucial data within the information system. In order to protect sensitive data, implementation of non-file-type secure storage technology that is non-dependent on file system is highly recommended. This research has proven the security and safety of such technology and verified its purpose.