• Asia pacific journal of information systems
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• v.29 no.3
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• pp.524-546
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• 2019

Product-service systems (PSS), integrating physical products and services, currently play a crucial role in sustainable economies. In addition to the highly competitive global economy, the emergence of new digital paradigms is supporting the shift toward servitization. Although the great potential of such paradigms is recognized by both practice and research, their implications for PSS are not yet clear. In particular, features of Internet of Things (IoT), such as total connectedness and ubiquity of smart sensors and actuators, provide various new opportunities for PSS. This study explores such opportunities by conducting structured literature review and 13 interviews. We organize the findings in two folds: First, we introduce four degrees of IoT involvement in PSS business models and elaborate the opportunities that they create for different types of PSS. Second, we present the key technologies and approaches that IoT provides concerning PSS lifecycle management.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.1-12
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• 2022

The current progression in the Internet of Things (IoT) and Machine Learning (ML) based technologies converted the traditional healthcare system into a smart healthcare system. The incorporation of IoT and ML has changed the way of treating patients and offers lots of opportunities in the healthcare domain. In this view, this research article presents a new IoT and ML-based disease diagnosis model for the diagnosis of different diseases. In the proposed model, vital signs are collected via IoT-based smart medical devices, and the analysis is done by using different data mining techniques for detecting the possibility of risk in people's health status. Recommendations are made based on the results generated by different data mining techniques, for high-risk patients, an emergency alert will be generated to healthcare service providers and family members. Implementation of this model is done on Anaconda Jupyter notebook by using different Python libraries in it. The result states that among all data mining techniques, SVM achieved the highest accuracy of 0.897 on the same dataset for classification of Parkinson's disease.

• Journal of Computing Science and Engineering
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• v.11 no.3
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• pp.100-108
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• 2017

In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.70-75
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• 2017

Recent development of IT industry including smart phones and communication technologies has resulted in rapid growth of Internet of Things (IoT) technology and relevant markets. The access to IoT is becoming easier thanks to the boards and IoT products, such as Arduino and Raspberry Pi. Large-scale business sites use IoT technology to manage inventories, but small-scale business sites do not. In the present study, We ported Linux-based Raspbian to Raspberry Pi, It utilizes web server communication to control the Arduino through the application We used a color sensor to figure out the kind of inventory. We also built a database using MySQL to store the data. We used raspberry pi to check whether the proposed system works and apply it to small-scale business.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.233-238
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• 2019

Internet of Things (IoT) technology has been recently utilized in diverse fields. Smart city is one of the IoT application domains with a lot of research topics and which is operated by integrated IoT applications. In this paper, diverse kinds of solutions, processes, and frameworks to address the existing challenges in information technology are introduced. Such solutions involve various future track topics including blockchain, security, steganography, optimization, machine learning, smart system, and so on. In the subsequent paragraphs, we describe each topic in a summarized way in terms of the existing challenges and their solutions. Specifically, this paper introduced 18 novel and enhanced research studies from different countries in the world. We present diverse kinds of paradigms to subjects that tackle diverse kinds of research areas such as IoT and Smart City, and so on.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.393-396
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• 2014

Recently, the internet of things (IoT) has become increasingly attractive in many areas to realize smart worlds. JavaScript has become prevalent for IoT programming because of its familiarity with web programmers. On the other hand, JavaScript does not allow the direct control of IoT hardware due to its language limitation. This paper proposes the IoT software platform for JavaScript programming to resolve the limitation. For proof of concept, the platform based on SpiderMonkey and Raspberry Pi was implemented.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.223-224
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• 2018

Internet of Things (IoT) 특성상 경량 디바이스를 사용하기 때문에 한정된 메모리 용량과 컴퓨팅 파워를 효율적으로 활용하기 위한 경량 통신 프로토콜이 요구된다. 본 논문에서는 IoT 기기에서 사용하는 경량 프로토콜인 MQTT를 이용해 센서 노드들이 보내는 데이터의 양을 최소화하여 트래픽 효율을 높이는 broker 캐싱을 제안한다. Broker 캐싱은 MQTT에서 센서 노드가 보낸 데이터를 broker가 캐싱해두고, 센서 노드로부터 중복 처리형 패킷을 받았을 때 캐싱한 데이터를 subscriber에게 전송한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.255-256
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• 2017

IoT(Internet of Things)는 우리 일상생활에 깊숙이 관여하고 있어서 보안 문제는 중요해지고 있다. OAuth2.0은 웹기반 응용이나 REST 특성의 API를 안전하게 하는 권한부여(authorization) 프레임워크이다. 본 논문에서는 IoT에 OAuth2.0을 적용하여 효율적이고 효과적인 권한부여 기법을 제안한다. OAuth2.0 기술은 서버쪽 기술이지만, IoT에서도 웹을 이용할 수 있는 CoAP 기술이 있으므로 IoT 디바이스 쪽에 접근에 대한 권한부여 기법으로 적용할 수 있다. 제안기법은 권한 부여 서버와 자원 서버와의 키 분배와 해시 함수 및 암호화를 통해 권한부여 기법을 적용한다.

• Information and Communications Magazine
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• v.34 no.2
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• pp.12-19
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• 2017

The LED technology advancement introduce cuttingedge technology on Internet of Things (IoT) to connect the physical world to the digital realm, using digital smart lighting infrastructure called Internet of light (IoL). This paper proposes an Integrated IoT agent on networked smart LED lighting controller called IoL Filed Gateway using lighting infrastructure in which a lighting system that can connect to a network and can be monitored and controlled from a centralized system or via the cloud. The IoL Field Gateway defines new world of smart connected intelligence, lighting can become an integral and responsive part of everyday human life environments. The proposed connected lighting gateway uses the concept of multi-hop ad hoc network using visible light communication (VLC) with RF wireless technologies and Wired PLC (Power Line Communication). This connectivity and intelligence integrated into LED-based luminaires form the backbone of smart buildings and cities and make the Internet of Things (IoT) vision feasible and enables the lighting administrator can control numerous lightings easily and visitors can get visual information from the lightings with their smart devices. The proposed IoL gateway design is emulated on Arduino based HW platform with VLC, RF, and PLC connectivity and evaluated with four sensor interface.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1071-1081
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• 2021

In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.