• Journal of Information Technology Services
• /
• v.22 no.2
• /
• pp.57-70
• /
• 2023

In order to establish an autonomous driving environment, it is necessary to study traffic safety and demand prediction by analyzing information generated from the transportation infrastructure beyond relying on sensors by the vehicle itself. In this paper, we propose a real-time traffic information generation method using sensor convergence technology of transportation infrastructure. The proposed method uses sensors such as cameras and radars installed in the transportation infrastructure to generate information such as crosswalk pedestrian presence or absence, crosswalk pause judgment, distance to stop line, queue, head distance, and car distance according to each characteristic. create information An experiment was conducted by comparing the proposed method with the drone measurement result by establishing a demonstration environment. As a result of the experiment, it was confirmed that it was possible to recognize pedestrians at crosswalks and the judgment of a pause in front of a crosswalk, and most data such as distance to the stop line and queues showed more than 95% accuracy, so it was judged to be usable.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.6
• /
• pp.1-7
• /
• 2011

The depth camera measures range information of the scene in real time using Time-of-Flight (TOF) technology. Measured depth data is then regularized and provided as a depth image. This depth image is utilized with the stereo or multi-view image to generate high-resolution depth map of the scene. However, it is required to correct noise and distortion of TOF depth image due to the technical limitation of the TOF depth camera. The corrected depth image is combined with the color image in various methods, and then we obtain the high-resolution depth of the scene. In this paper, we introduce the principal and various techniques of sensor fusion for high-quality depth generation that uses multiple camera with depth cameras.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.888-893
• /
• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.

• Journal of Korean Society of Transportation
• /
• v.19 no.6
• /
• pp.171-182
• /
• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of the Korea Convergence Society
• /
• v.6 no.1
• /
• pp.1-5
• /
• 2015

In this paper, we describe the design of a fusion labeling system which is controlled by the Wi-Fi signals. The Current labeling system which is used in the industry is designed to work independently on the production line not connected with internet network services. For such reasons, it is very inconvenient for the labeling system to transfer such labeling data of the production line to the server computer. We propose a labeling system connected to the Wi-Fi service being able to send real-time transmission of labeling data. This system can supply the labeling data of production line to the server computer in realtime and improve the production quality than the existing system.

• Journal of Multimedia Information System
• /
• v.6 no.4
• /
• pp.265-270
• /
• 2019

The technology to locate an individual has enabled various services, its utilization has increased. There were constraints such as the use of separate expensive equipment or the installation of specific devices on a facility, with most of the location technology studies focusing on the accuracy of location verification. These constraints can result in accuracy within a few tens of centimeters, but they are not technology that can be applied to a user's location in real-time in daily life. Therefore, this paper aims to track the locations of smartphones only using the basic components of smartphones. Based on smartphone sensor data, localization accuracy that can be used for verification of the users' locations is aimed at. Accelerometers, Wifi radio maps, and GPS sensor information are utilized to implement it. In forging the radio map, signal maps were built at each vertex based on the graph data structure This approach reduces traditional map-building efforts at the offline phase. Accelerometer data were made to determine the user's moving status, and the collected sensor data were fused using particle filters. Experiments have shown that the average user's location error is about 3.7 meters, which makes it reasonable for providing location-based services in everyday life.

• Journal of the Korean Ceramic Society
• /
• v.41 no.2
• /
• pp.97-101
• /
• 2004

W $O_{x}$-based semiconductor type thin film gas sensor was fabricated for the detection of N $O_{x}$ by reactive d.c. sputtering method. The relative oxidation state of the deposited W $O_{x}$ films was approximately compared by the calculation of the difference of the binding energy between Ols to W4 $f_{7}$2/ core level XPS spectra in the standard W $O_3$ powder of known composition. As the annealing temperature increased from 500 to 80$0^{\circ}C$, relative oxygen contents and grain size of the sputtered films were gradually increased. As the results of sensitivity ( $R_{gas}$/ $R_{air}$) measurements for the 5 ppm N $O_2$ gas, the sensitivity was 110 and the sensor showed recovery time as fast as 200 s. The other sensor properties were examined in terms of surface microstructure, annealing temperature, and relative oxygen contents. These results indicated that the W $O_3$ thin film with well controlled structure is a good candidate for monitoring and controlling of automobile exhaust.haust.t.t.t.

• Smart Structures and Systems
• /
• v.6 no.3
• /
• pp.309-333
• /
• 2010

Civil infrastructure, in both its construction and maintenance, represents the largest societal investment in this country, outside of the health care industry. Despite being the lifeline of US commerce, civil infrastructure has scarcely benefited from the latest sensor technological advances. Our future should focus on harnessing these technologies to enhance the robustness, longevity and economic viability of this vast, societal investment, in light of inherent uncertainties and their exposure to service and even extreme loadings. One of the principal means of insuring the robustness and longevity of infrastructure is to strategically deploy smart sensors in them. Therefore, the objective is to develop novel, durable, smart sensors that are especially applicable to major infrastructure and the facilities to validate their reliability and long-term functionality. In some cases, this implies the development of new sensing elements themselves, while in other cases involves innovative packaging and use of existing sensor technologies. In either case, a parallel focus will be the integration and networking of these smart sensing elements for reliable data acquisition, transmission, and fusion, within a decision-making framework targeting efficient management and maintenance of infrastructure systems. In this paper, prudent and viable sensor and health monitoring technologies have been developed and used in several large structural systems. Discussion will also include several practical bridge health monitoring applications including their design, construction, and operation of the systems.

• The KIPS Transactions:PartB
• /
• v.14B no.4
• /
• pp.249-254
• /
• 2007

A mobile robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. We focus on how to detect a object region well using image processing algorithm because it gives robots the ability of working for human. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. Shape information and signature algorithm are used to segment the objects from background regardless of shape changes. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.34 no.5
• /
• pp.301-308
• /
• 2021

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.