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이우식(Woosik Lee),김남기(Woosik Lee) 한국정보기술학회 2013 Proceedings of KIIT Conference Vol.2013 No.5
최근 스마트폰의 빠른 보급과 위치 기반 서비스의 급증은 위치 기반 관광 정보 서비스의 중요성을 부각하고 있다. 위치 기반 관광 정보 서비스는 LBS (Location Based Service)의 한 형태로 텍스트, 이미지, 동영상과 같은 다양한 형태의 컨테츠를 웹 또는 앱 형태로 제공해 주는 서비스라고 할 수 있다. 이런 서비스는 Push와 Pull 형태로 컨텐츠 서비스를 제공받으며, Wi-Fi, Cell-ID, GPS, NFS와 같은 측위 기술을 통해 위치 정보를 제공 받는다. 이런 정보를 사용자는 아이폰, 겔럭시 폰, 아이패드, 겔럭시 노트 등과 같은 스마트 디바이스에 스토리텔링, 증강현실, 위키피디아, QR코드와 같은 서비스 기술을 사용하여 다양한 서비스를 체험할 수 있다. 본 논문에서는 위치 기반 관광 정보 서비스에 대한 개념과 기술 동향을 살펴보며, 앞으로 위치 기반 관광 정보서비스가 나아가야 될 방향을 제시하고자 한다 Nowaday, location based tourism information service is important over time because of providing smartphone fastly and increasing location based service. Location based tourism information service is a type of LBS (Location Based Services) that supply various contents on web or app. This service received content service based on push and pull technologies and location service based on diverse location determination technologies such as wi-fi, cell-id, gps, and nfs. Consumers easily go through these services on smart devices such as iphone, galaxy phone, ipad, and palaxy tab using storytelling, augmented reality, wikipedia, and qr-code technologies. In this paper, we show a concept about location based tourism information service and technology trends. Lastly, we present a way of advanced location based tourism information service in the future.
Machine Learning based Prediction of The Value of Buildings
( Woosik Lee ),( Namgi Kim ),( Yoon-ho Choi ),( Yong Soo Kim ),( Byoung-dai Lee ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings’ value pricing and future value by using big data regarding buildings’ spatial information, as acquired from a database containing building value attributes. The algorithm’s availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings’ value ranking and value pricing, as predicted by intelligent machine learning.
( Woosik Lee ),( Namgi Kim ),( Byoung-dai Lee ) 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.3
In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor’s batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.
A Survey of the Transmission-Power-Control Schemes in Wireless Body-Sensor Networks
( Woosik Lee ),( Heeyoul Kim ),( Min Hong ),( Min-goo Kang ),( Seung Ryul Jeong ),( Namgi Kim ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.4
A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.