• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4541-4554
• /
• 2019

This paper proposes a planar projection DV-hop location algorithm (PTCDV-hop) based on the LED semi-angle at half power (SAHP, which accounts for LED SAHP characteristics in visible light communication (VLC)) and uses the DV-hop algorithm for range-free localization. Distances between source nodes and nodes positioned in three-dimensional indoor space are projected onto a two-dimensional plane to reduce complexity. Circles are structured by assigning source nodes (projected onto the horizontal plane of the assigned nodes) to be centers and the projection distances as radii. The proposed PTCDV-hop algorithm then determines the position of node location coordinates using the trilateral-weighted-centroid algorithm. Simulation results show localization errors of the proposed algorithm are on the order of magnitude of a millimeter when three sources are used. The PTCDV-hop algorithm has higher positioning accuracy and stronger dominance than the traditional DV-hop algorithm.

• Journal of Korea Multimedia Society
• /
• v.24 no.12
• /
• pp.1682-1692
• /
• 2021

Digital Twin, one of the core technologies of the Fourth Industrial Revolution, is attracting attention as a very suitable technology for disaster monitoring such as fires and earthquakes. In this paper, we implement a system equipped with UWB RTLS(Ultra-Wideband Real Time Location System), real-time remote control, and video streaming, which are element technologies for disaster monitoring digital twin. Since the proposed system structure is based on a cloud server, the actual location of the UWB indoor positioning-based client is transmitted to the user device in real time and stored on the cloud server for statistical and data analysis. In addition, we demonstrate through experiments that outliers occurs when the value of RSSI(Received Signal Strength Indicator) decreases due to communication collisions between UWB Tags, and propose an RSSI outlier correction algorithm to solve this problem.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.84-89
• /
• 2009

Personal mobile devices such as mobile phone, PMP and MP3 player have advanced incredibly. Such advance in mobile technology ignites the research related to the life-log to understand the daily life of an user. Since life-log collected by mobile sensors can aid memory of the user, many researches have been conducted. This paper suggests a methodology for user-context recognition and visualization based on the outdoor location by GPS as well as indoor location by wireless-lan. When the GPS sensor does not work well in an indoor location, wireless-lan plays a major role in recognizing the location of an user so that the recognition of user-context become more accurate. In this paper, we have also developed the method for visualization of the life-log based on map and blog interfaces. In the experiments, subjects have collected real data with mobile devices and we have evaluated the performance of the proposed visualization and context recognition method based on the data.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.12
• /
• pp.107-116
• /
• 2013

We proposed the WSN monitoring system applied the augmented reality to visualize effectively an indoor WSN. To implement system, we used wireless sensor network, indoor location determination, location-based augmented reality technology. First, we composed the wireless sensor networks indoors and implement web server and then get data from server DB using Android phones. Then, we obtained the (x, y) coordinates using the triangulation method from RSSI of three point of the strongest signal strength of the AP's. Also, we adjusted coordinates using the Kalman filter. Finally, we inserted the adjusted coordinates to the latitude and the longitude of the Mixare that use the GPS signal, and we got location of user and wireless sensor in the server DB. After that, we implemented augmented reality system using the android phone and wireless sensor location and data and real life image.

• Journal of Advanced Navigation Technology
• /
• v.23 no.6
• /
• pp.526-534
• /
• 2019

Localization methods using radio signals should obtain range measurements from three or more anchors. However, a typical building consists of narrow, long hallways and corners, making it difficult to secure more than three light of sight anchors. The result is a multi-modal solution that makes it difficult to estimate the user's location. In order to overcome this problem, this paper proposes a method for estimating the location using artificial neural networks. Using the artificial neural network, even if a multi-modal solution occurs, the position can be estimated by acquiring user movement pattern information based on accumulated range measurements. The method does not require any additional equipment or sensors, and only anchor-based range measurements can estimate the user's location. In order to verify the proposed method, location estimation tests were performed in situations where the multi-modal solution occurred by installing an insufficient number of anchors in a building. As a result, it was confirmed that the location can be estimated even when the number of anchors is insufficient.

• Journal of Digital Convergence
• /
• v.14 no.2
• /
• pp.217-225
• /
• 2016

In this study, a dementia patient care monitoring system is suggested that uses a wearable type bluetooth beacon to prevent them from going missing. This system shows whether the patients stay within the manageable area and sends a warning message to their monitoring managers' or guardians' smart devices when they leave it. The feature of the system is that it provides the service based on indoor location that makes the beacon worn by dementia patients continuously transmit their location information to the managing server through the smart terminal installed indoors or in hospitals and that enables the monitoring managers or the guardians to receive messages sent from the server that tell the patients' whereabouts through their smart devices. The system suggested in this paper is believed to be a system that effectively contributes to the prevention of the dementia patients' going astray from the hospitals and facilities where they are taking care.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.6_2
• /
• pp.511-520
• /
• 2013

Recently, human activities have expanded from outdoor spaces to indoor spaces since a lot of complex buildings were constructed over the world. Especially, visitors in a shopping mall would like to receive specific information of interest regarding various shopping-related activities as well as shopping itself. However, when it comes to providing the information, existing guide services have some drawbacks. Firstly, the existing services cannot provide visitors with the information of other stores simply and promptly on the current location. Secondly, the services have difficulties in representation and share of the shopping-related knowledge, and in providing inferred information. Thus, the purpose of this study is to develop a method that allows topological analysis utilizing ontology technique around the current position in such shopping mall in order to provide shopping-related information. For this, the shopping activity ontology model is designed, and based on the ontology model, inferencing rules are defined in order to extract the information of interest efficiently through semantic queries. Also, a geocoding method in indoor spaces is used regarding the current location, and optimal routing analysis, which is one of topological analysis, is applied with the result from the semantic queries. As a result, an Android application is developed for 3D visualization and user interface.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.345-347
• /
• 2016

Recently location based services is being expanded into the indoor service that can not access to the outdoor location informations, such as GPS. Thus, the research and development of an indoor positioning system with BLE(Bluetooth Low Energy) iBeacon technology has expanded. However, RSSI (Received Signal Strength Indicator) that is used as the distance information between the terminal and for positioning iBeacon signal has a problem in that distortion occurs, information such as the signal attenuation and the delay due to the characteristics of radio waves. In this paper, we propose a reliable method of verifying iBeacon signal with the signal distortion problems for reliable indoor positioning systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.1
• /
• pp.277-290
• /
• 2019

The demand for indoor positioning is increasing day by day. However, the widely used positioning methods today cannot satisfy the requirements of the indoor environment in terms of the positioning accuracy and deployment cost. In the existing research domain, the localization algorithm based on three-dimensional space is less accurate, and its robustness is not high. Visible light communication technology (VLC) combines lighting and positioning to reduce the cost of equipment deployment and improve the positioning accuracy. Further, it has become a popular research topic for telecommunication and positioning in the indoor environment. This paper proposes a surface centroid TOA localization algorithm based on the VLC system. The algorithm uses the multiple solutions estimated by the trilateration method to form the intersecting planes of the spheres. Then, it centers the centroid of the surface area as the position of the unknown node. Simulation results show that compared with the traditional TOA positioning algorithm, the average positioning error of the surface centroid TOA algorithm is reduced by 0.3243 cm and the positioning accuracy is improved by 45%. Therefore, the proposed algorithm has better positioning accuracy than the traditional TOA positioning algorithm, and has certain application value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.458-459
• /
• 2021

Recently, researches using deep learning technology based on Wi-Fi fingerprints have been conducted for accurate services in indoor location-based services. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. At this time, continuous sequential data is required as training data. However, since Wi-Fi fingerprint data is generally managed only with signals for a specific location, it is inappropriate to use it as training data for an RNN model. This paper proposes a path generation method through prediction of a moving path based on Wi-Fi fingerprint data extended to region data through clustering to generate sequential input data of the RNN model.