• Journal of Positioning, Navigation, and Timing
• /
• v.9 no.3
• /
• pp.175-182
• /
• 2020

This paper introduces a study to estimate the user altitude in need of rescue in an emergency. The altitude is estimated by using the barometric pressure sensor embedded in the smartphone. Compared to GPS, which is degraded in urban or indoor environments, it has the advantage of not having spatial restrictions. With the endless development of smartphone hardware, it is possible to estimate the absolute altitude using the measured value if only the bias of the embedded barometric pressure sensor is applied. The altitude information of the person in need of rescue in an emergency is a great help in reducing rescue time. Since time is tight, we propose online calibration that provides the barometric pressure sensor bias used for altitude estimation through database. Furthermore, experiments were conducted to understand the characteristics of the barometric pressure sensor, which is greatly affected by wind. At the end, the altitude estimation performance was confirmed through an actual field tests in various floors in the building.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.4 no.2
• /
• pp.103-110
• /
• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.3
• /
• pp.126-133
• /
• 2009

There are already many researches providing u-Healthcare service, but they have left problems to be improved. First of all, the transmission range between sensor nodes and the gateway are restricted. Hence, patients feel uncomfortable because of they need to possess or locate closed to a gateway all the time when they aggregates their medical data. Also, the existing systems have not considered life environment that is important to analyze patient's diseases. Moreover, a guardian need to located close to patient or possess a mobile device that monitors a patients' status in real time when they are in outdoor. In this research, we present multi-hop packet transfer algorithm and compilation of life environment which help improve the problem of the existing researches. Likewise, we designed and implemented a medical information database and a real-time web monitoring system that manage patients' personal history and monitor a patients' status in real time. In this paper, we design and implement the u-Healthcare system based on mobile environment and we present a result when we tested our u-Healthcare system in scenario environment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.2
• /
• pp.856-865
• /
• 2012

Maintenance systems are demanded to manage malodor-information and deal effectively with the odor-related civil complaints by constructing the database for sources of malodor compounds in real time. In this paper, to carry out these tasks, a real-time monitering system for malodor based on ubiquitous sensor networks(USN) is presented. The constructed monitering system stores the malodor data collected periodically from industrial complex into the database and shows in real time the circumstances of the odor sources being emitted around the industrial complex by indicating on the map where it is taking place. Besides, by clicking an icon indicating the sensor node on the map, we can figure out what firms are located near the malodor source and possible material related with those firms. The proposed system is considered to enhance the efficiency of management of malodor-emitting firms based on the malodor-related information.

• Journal of Biosystems Engineering
• /
• v.27 no.3
• /
• pp.259-266
• /
• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.103-112
• /
• 2008

In this paper we present two databases for two different systems each having novel implementation ideas: a u-Healthcare system with a mobile gateway and MAGI network monitoring system. u-Healthcare system is capturing and monitoring vital sign data without restrictions of location and time using body sensor network and a mobile gateway. MAGI is a system which has a dynamic firewall function and solves problems of existing traffic monitoring tools. In addition to presenting the design principles behind these two systems, we describe the respective database schemas together with detailed information of the data stored within the databases. We will also show and discuss performance measurements and calculations for both systems. Based on the performance data we will discuss the systems' suitability for their intended uses.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.2
• /
• pp.101-108
• /
• 2015

In this paper, a robust traffic light detection method is proposed by using vision sensor and DGPS(Difference Global Positioning System). The conventional vision-based detection methods are very sensitive to illumination change, for instance, low visibility at night time or highly reflection by bright light. To solve these limitations in visual sensor, DGPS is incorporated to determine the location and shape of traffic lights which are available from traffic light database. Furthermore the geometric relationship between traffic light and vision sensor is used to locate the traffic light in the image by using DGPS information. The empirical results show that the proposed method improves by 51% in detection rate for night time with marginal improvement in daytime environment.

• Journal of Software Assessment and Valuation
• /
• v.16 no.2
• /
• pp.127-133
• /
• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• Journal of the Korean Society for Railway
• /
• v.5 no.3
• /
• pp.148-157
• /
• 2002

A health monitoring system becomes a useful tool to obtain information on long term behavior of the important railway structures such as very long span and special type bridges. The health monitoring system not only gives the direct measurement data of the railway bridges but also provides the basic data on the maintenance of the structures. Therefore, periodic calibrations of the health monitoring system will be a necessary step toward precise and accurate assessment of the railway bridges. In this study, the calibration and gauge factor readjustment process made for the health monitoring system installed in the railroad bridges is reviewed and some findings are explained in detail: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in full length. Based on the regression results, it was found that the gauge factors need to be readjusted according to the regression equation but, since the deviation or shift is not serious so far, long-term observation on each sensor is also recommended. Future work will be concentrated on the long-term analysis of each sensor and on the database creation so that the assessment of the structures is possible.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.3
• /
• pp.248-253
• /
• 2008

This paper presents a sensing system for smart home which can detect an location transition events such as entrance/exit of a member and identify the user in a group at the same time. The proposed system is compose of two sub-systems; a wireless sensor network system and a database server system. The wireless sensing system is designed as a star network where each of sensing modules with ultrasonic sensors and a Bluetooth RF module connect to a central receiver called Bluetooth access point. We propose a method to discriminate a user by measuring the height of the user. The differences in the height of users is a key feature for discrimination. At the same time, the each sensing module can recognize whether the user goes into or out a room by using two ultrasonic sensors. The server subsystem is a sort of data logging system which read the detected event from the access point and then write it into a database system. The database system could provide the location transition information to wide range of context-aware applications for smart home easily and conveniently. We evaluate the developed method with experiments for three subjects in a family with the installation of the developed system into a real house.