• Title/Summary/Keyword: performance of ICT technology

Search Result 398, Processing Time 0.024 seconds

LSTM-based Fire and Odor Prediction Model for Edge System (엣지 시스템을 위한 LSTM 기반 화재 및 악취 예측 모델)

  • Youn, Joosang;Lee, TaeJin
    • KIPS Transactions on Computer and Communication Systems
    • /
    • v.11 no.2
    • /
    • pp.67-72
    • /
    • 2022
  • Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

Implementation of Water Depth Indicator using Contactless Smart Sensors (비접촉식 스마트센서 기반 수위측정 방법 구현)

  • Kim, Minhwan;Lee, Jinhee;Song, Giltae
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.23 no.6
    • /
    • pp.733-739
    • /
    • 2019
  • Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.

Design and Implementation of a Smart Home Cloud Control System Using Bridge based on IoT (IoT 기반의 브리지를 이용한 스마트 홈 클라우드 제어 시스템 설계 및 구현)

  • Hao, Xu;Kim, Chul-Won
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.12 no.5
    • /
    • pp.865-872
    • /
    • 2017
  • Recently, in response to the Internet age, the demand for hardware devices has been increasing, centering on the rapidly growing smart home field, due to the growth and management of sensor and control technology, mobile application, network traffic, big data management and cloud computing. In order to maintain the sustainable development of the hardware system, it is necessary to update the system, and the hardware device is absolutely necessary in real time processing of complex data (voice, image, etc.) as well as data collection. In this paper, we propose a method to simplify the control and communication method by integrating the hardware devices in two operating systems in a unified structure to solve the simultaneous control and communication method of hardware under different operating systems. The performance evaluation results of the proposed integrated hardware and the cloud control system connected to the cloud server are described and the main directions to be studied in the field of internet smart home are described.

The Acceptance Factors for Electronic Medical Record System (전자의무기록시스템의 수용요인)

  • Chun, Je-Ran
    • Journal of Digital Convergence
    • /
    • v.13 no.12
    • /
    • pp.47-53
    • /
    • 2015
  • In this paper the factors are analyzed, which influenced on the acceptance of Electronic Medical System (EMR) of healthcare organization in Korea. The measured variables and factors were defined on the base of former research works. The questionnaires with Likert's 5 scale were administrated in the 102 general hospitals in Korea. This data was analyzed with SPSS v. 20. According to the result of factor analysis, the 4 influencing factors were grouped. They are, "ICT-infrastructure of healthcare organization", "Management strategy of healthcare organization", "EMR acceptance" and "EMR-performance". 5 hypotheses about the correlations between factors were formulated and analyzed with structural equation model(SEM). The result of this paper could be the good reference to the healthcare organizations on how they should implement and operate the EMR system.

A Study on the Impact of Speech Data Quality on Speech Recognition Models

  • Yeong-Jin Kim;Hyun-Jong Cha;Ah Reum Kang
    • Journal of the Korea Society of Computer and Information
    • /
    • v.29 no.1
    • /
    • pp.41-49
    • /
    • 2024
  • Speech recognition technology is continuously advancing and widely used in various fields. In this study, we aimed to investigate the impact of speech data quality on speech recognition models by dividing the dataset into the entire dataset and the top 70% based on Signal-to-Noise Ratio (SNR). Utilizing Seamless M4T and Google Cloud Speech-to-Text, we examined the text transformation results for each model and evaluated them using the Levenshtein Distance. Experimental results revealed that Seamless M4T scored 13.6 in models using data with high SNR, which is lower than the score of 16.6 for the entire dataset. However, Google Cloud Speech-to-Text scored 8.3 on the entire dataset, indicating lower performance than data with high SNR. This suggests that using data with high SNR during the training of a new speech recognition model can have an impact, and Levenshtein Distance can serve as a metric for evaluating speech recognition models.

Multi-Path Virtual Network Resource Allocation with Shared Backup Bandwidth (공유 백업 대역폭을 갖는 다중 경로 지원 가상 네트워크 자원 할당 방안)

  • Kim, Hak Suh;Lee, Sang-Ho
    • Journal of Convergence Society for SMB
    • /
    • v.6 no.4
    • /
    • pp.17-23
    • /
    • 2016
  • With the advance of ICT, the Internet has been creating new services in various fields. However, due to the architectural problem of the Internet, it may inhibit the development of network architectures and various services. Network virtualization is being investigated as an alternative to overcome the architectural problem of the Internet and a virtual network resource allocation algorithm is a very important issue. In this paper, we propose a multiple path resource allocation algorithm with shared backup bandwidth in order to overcome single link failure. It will be improved survivability of the virtual networks. Through our experiments, we confirmed that the multi-path creation time of the proposed algorithm has about 50% performance improvement than previous works.

Big Data Model for Analyzing Plant Growth Environment Informations and Biometric Informations (농작물 생육환경정보와 생체정보 분석을 위한 빅데이터 모델)

  • Lee, JongYeol;Moon, ChangBae;Kim, ByeongMan
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.25 no.6
    • /
    • pp.15-23
    • /
    • 2020
  • While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

The Analysis of Efficient Disk Buffer Management Policies to Develop Undesignated Cultural Heritage Management and Real-time Theft Chase (실시간 비지정 문화재 관리 및 도난 추적 시스템 개발을 위한 효율적인 디스크 버퍼 관리 정책 분석)

  • Jun-Hyeong Choi;Sang-Ho Hwang;SeungMan Chun
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.18 no.6
    • /
    • pp.1299-1306
    • /
    • 2023
  • In this paper, we present a system for undesignated cultural heritage management and real-time theft chase, which uses flash-based large-capacity storage. The proposed system is composed of 3 parts, such as a cultural management device, a flash-based server, and a monitoring service for managing cultural heritages and chasing thefts using IoT technologies. However flash-based storage needs methods to overcome the limited lifespan. Therefore, in this paper, we present a system, which uses the disk buffer in flash-based storage to overcome the disadvantage, and evaluate the system performance in various environments. In our experiments, LRU policy shows the number of direct writes in the flash-based storage by 10.7% on average compared with CLOCK and FCFS.

An Empirical Study on Perceived Value and Continuous Intention to Use of Smart Phone, and the Moderating Effect of Personal Innovativeness (스마트폰의 지각된 가치와 지속적 사용의도, 그리고 개인 혁신성의 조절효과)

  • Han, Joonhyoung;Kang, Sungbae;Moon, Taesoo
    • Asia pacific journal of information systems
    • /
    • v.23 no.4
    • /
    • pp.53-84
    • /
    • 2013
  • With rapid development of ICT (Information and Communications Technology), new services by the convergence of mobile network and application technology began to appear. Today, smart phone with new ICT convergence network capabilities is exceedingly popular and very useful as a new tool for the development of business opportunities. Previous studies based on Technology Acceptance Model (TAM) suggested critical factors, which should be considered for acquiring new customers and maintaining existing users in smart phone market. However, they had a limitation to focus on technology acceptance, not value based approach. Prior studies on customer's adoption of electronic utilities like smart phone product showed that the antecedents such as the perceived benefit and the perceived sacrifice could explain the causality between what is perceived and what is acquired over diverse contexts. So, this research conceptualizes perceived value as a trade-off between perceived benefit and perceived sacrifice, and we need to research the perceived value to grasp user's continuous intention to use of smart phone. The purpose of this study is to investigate the structured relationship between benefit (quality, usefulness, playfulness) and sacrifice (technicality, cost, security risk) of smart phone users, perceived value, and continuous intention to use. In addition, this study intends to analyze the differences between two subgroups of smart phone users by the degree of personal innovativeness. Personal innovativeness could help us to understand the moderating effect between how perceptions are formed and continuous intention to use smart phone. This study conducted survey through e-mail, direct mail, and interview with smart phone users. Empirical analysis based on 330 respondents was conducted in order to test the hypotheses. First, the result of hypotheses testing showed that perceived usefulness among three factors of perceived benefit has the highest positive impact on perceived value, and then followed by perceived playfulness and perceived quality. Second, the result of hypotheses testing showed that perceived cost among three factors of perceived sacrifice has significantly negative impact on perceived value, however, technicality and security risk have no significant impact on perceived value. Also, the result of hypotheses testing showed that perceived value has significant direct impact on continuous intention to use of smart phone. In this regard, marketing managers of smart phone company should pay more attention to improve task efficiency and performance of smart phone, including rate systems of smart phone. Additionally, to test the moderating effect of personal innovativeness, this research conducted multi-group analysis by the degree of personal innovativeness of smart phone users. In a group with high level of innovativeness, perceived usefulness has the highest positive influence on perceived value than other factors. Instead, the analysis for a group with low level of innovativeness showed that perceived playfulness was the highest positive factor to influence perceived value than others. This result of the group with high level of innovativeness explains that innovators and early adopters are able to cope with higher level of cost and risk, and they expect to develop more positive intentions toward higher performance through the use of an innovation. Also, hedonic behavior in the case of the group with low level of innovativeness aims to provide self-fulfilling value to the users, in contrast to utilitarian perspective, which aims to provide instrumental value to the users. However, with regard to perceived sacrifice, both groups in general showed negative impact on perceived value. Also, the group with high level of innovativeness had less overall negative impact on perceived value compared to the group with low level of innovativeness across all factors. In both group with high level of innovativeness and with low level of innovativeness, perceived cost has the highest negative influence on perceived value than other factors. Instead, the analysis for a group with high level of innovativeness showed that perceived technicality was the positive factor to influence perceived value than others. However, the analysis for a group with low level of innovativeness showed that perceived security risk was the second high negative factor to influence perceived value than others. Unlike previous studies, this study focuses on influencing factors on continuous intention to use of smart phone, rather than considering initial purchase and adoption of smart phone. First, perceived value, which was used to identify user's adoption behavior, has a mediating effect among perceived benefit, perceived sacrifice, and continuous intention to use smart phone. Second, perceived usefulness has the highest positive influence on perceived value, while perceived cost has significant negative influence on perceived value. Third, perceived value, like prior studies, has high level of positive influence on continuous intention to use smart phone. Fourth, in multi-group analysis by the degree of personal innovativeness of smart phone users, perceived usefulness, in a group with high level of innovativeness, has the highest positive influence on perceived value than other factors. Instead, perceived playfulness, in a group with low level of innovativeness, has the highest positive factor to influence perceived value than others. This result shows that early adopters intend to adopt smart phone as a tool to make their job useful, instead market followers intend to adopt smart phone as a tool to make their time enjoyable. In terms of marketing strategy for smart phone company, marketing managers should pay more attention to identify their customers' lifetime value by the phase of smart phone adoption, as well as to understand their behavior intention to accept the risk and uncertainty positively. The academic contribution of this study primarily is to employ the VAM (Value-based Adoption Model) as a conceptual foundation, compared to TAM (Technology Acceptance Model) used widely by previous studies. VAM is useful for understanding continuous intention to use smart phone in comparison with TAM as a new IT utility by individual adoption. Perceived value dominantly influences continuous intention to use smart phone. The results of this study justify our research model adoption on each antecedent of perceived value as a benefit and a sacrifice component. While TAM could be widely used in user acceptance of new technology, it has a limitation to explain the new IT adoption like smart phone, because of customer behavior intention to choose the value of the object. In terms of theoretical approach, this study provides theoretical contribution to the development, design, and marketing of smart phone. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy formulation for acquiring and retaining long-term customers related to smart phone business. Since potential customers are interested in both benefit and sacrifice when evaluating the value of smart phone, marketing managers in smart phone company has to put more effort into creating customer's value of low sacrifice and high benefit so that customers will continuously have higher adoption on smart phone. Especially, this study shows that innovators and early adopters with high level of innovativeness have higher adoption than market followers with low level of innovativeness, in terms of perceived usefulness and perceived cost. To formulate marketing strategy for smart phone diffusion, marketing managers have to pay more attention to identify not only their customers' benefit and sacrifice components but also their customers' lifetime value to adopt smart phone.

Machine Learning for Predicting Entrepreneurial Innovativeness (기계학습을 이용한 기업가적 혁신성 예측 모델에 관한 연구)

  • Chung, Doo Hee;Yun, Jin Seop;Yang, Sung Min
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
    • /
    • v.16 no.3
    • /
    • pp.73-86
    • /
    • 2021
  • The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.