• The KIPS Transactions:PartC
• /
• v.17C no.3
• /
• pp.259-270
• /
• 2010

In this paper, a Location Information-based Gradient Routing (LIGR) algorithm is proposed for setting up routing path based on physical location information of sensor nodes in wireless ad-hoc networks. LIGR algorithm reduces the unnecessary data transmission time, route search time, and propagation delay time of packet by determining the transmission direction and search range through the gradient from the source node to sink node using the physical location information. In addition, the low battery nodes are supposed to have the second or third priority in case of forwarding node selection, which reduces the possibility of selecting the low battery nodes. As a result, the low battery node functions as host node rather than router in the wireless sensor networks. The LIGR protocol performed better than the Logical Grid Routing (LGR) protocol in the average receiving rate, delay time, the average residual energy, and the network processing ratio.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.3
• /
• pp.565-571
• /
• 2016

This study check the construction site and borrow pit location using GIS-based Open Global Map. Construction Equipment (Dump, Grader) utilizes the GPS (Global Positioning System) to gain equipment's real-time position, speed, altitude, using the data such as directions to perform real-time monitoring. The analysis of the productivity is completed through using the data, and the optimal number of equipment is calculated. It was found that the analysis results showed approximately 30% less cost compared to the actual design plan.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.3
• /
• pp.124-129
• /
• 2021

As the 4th industrial era is in full swing, the public's interest in related technologies such as artificial intelligence, big data, and block chain is increasing. As artificial intelligence technology is used in various industrial fields, the need for research methods incorporating artificial intelligence technology in related fields is also increasing. Evidence collection among digital forensic investigation techniques is a very important procedure in the investigation process that needs to prove a specific person's suspicions. However, there may be cases in which evidence is damaged due to intentional damage to evidence or other physical reasons, and there is a limit to the collection of evidence in this situation. Therefore, this paper we intends to propose an artificial intelligence-based evidence collection system that analyzes numerous image files reported by citizens in real time to visually check the location, user information, and shooting time of the image files. When this system is applied, it is expected that the evidence expected data collected in real time can be actually used as evidence, and it is also expected that the risk area analysis will be possible through big data analysis.

• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.415-426
• /
• 2006

The essential characteristic of ubiquitous is context-awareness, and that means ubiquitous computing can automatically process the data that change according to space and time, without users' intervention. However, in circumstance of context awareness, since location information is able to be collected without users' clear approval, users cannot control their location information completely. These problems can cause privacy issue when users access their location information. Therefore, it is important to construct the location information system, which decides to release the information considering privacy under the condition such as location, users' situation, and people who demand information. Therefore, in order to intercept an outflow information and provide securely location-based information, this paper suggests a new system based CS-RBAC with the existing LBS, which responds sensitively as customer's situation. Moreover, it accommodates a merit of PCP reflecting user's preference constructively. Also, through privacy weight, it makes information not only decide to providing information, but endow 'grade'. By this method, users' data can be protected safely with foundation of 'Role' in context-aware circumstance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.639-640
• /
• 2018

Currently, the technique of identifying location using radio wave fingerprint is widely used in indoor positioning field. At this time, in order to confirm a successful position, it is necessary to construct the data necessary for learning and testing and to construct the multidimensional data. That is, location data collection and data management technology capable of responding to environmental changes that may occur due to various changes in peripheral radio wave fingerprint such as wireless AP, BLE iBeacon, and mobile terminal are required. Therefore, this paper proposes a technique to construct and manage multidimensional data which is less sensitive to environmental changes of radio wave fingerprinting required for positioning.

• Spatial Information Research
• /
• v.19 no.1
• /
• pp.127-133
• /
• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• Journal of Advanced Information Technology and Convergence
• /
• v.8 no.2
• /
• pp.27-39
• /
• 2018

In this paper, we describe the algorithms, EEG classification methods, and position data analysis methods using EEG and ADS1299 sensors. In addition, it is necessary to manage the amount of real-time data of location data and EEG data and to extract data efficiently. To do this, we explain the process of extracting important information from a vast amount of data through a cloud server. The electrical signals extracted from the brain are measured to determine the psychological state and health status, and the measured positions can be collected using the position sensor and triangulation method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.1
• /
• pp.41-46
• /
• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• Journal of Korea Spatial Information System Society
• /
• v.8 no.2 s.17
• /
• pp.75-89
• /
• 2006

LBS (Location-Based Service) systems have become a serious subject for research and development since recent rapid advances in wireless communication technologies and position measurement technologies such as global positioning system. The architecture named the GALIS (Gracefully Aging Location Information System) has been suggested which is a cluster-based distributed computing system architecture to overcome performance losses and to efficiently handle a large volume of data, at least millions. The GALIS consists of SLDS and LLDS. The SLDS manages current location information of moving objects and the LLDS manages past location information of moving objects. In this thesis, we implement a monitoring technique for the GALIS prototype, to allow dynamic load balancing among multiple computing nodes by keeping track of the load of each node in real-time during the location data management and spatio-temporal query processing. We also propose a buffering technique which efficiently manages the query results having overlapped query regions to improve query processing performance of the GALIS. The proposed scheme reduces query processing time by eliminating unnecessary query execution on the overlapped regions with the previous queries.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.543-556
• /
• 2015

We present a survey of contributions that defined the nature and extent of robust statistics for the last 50 years. From the pioneering work of Tukey, Huber, and Hampel that focused on robust location parameter estimation, we presented various generalizations of these estimation procedures that cover a wide variety of models and data analysis methods. Among these extensions, we present linear models, clustered and dependent observations, times series data, binary and discrete data, models for spatial data, nonparametric methods, and forward search methods for outliers. We also present the current interest in robust statistics and conclude with suggestions on the possible future direction of this area for statistical science.