• ETRI Journal
• /
• v.45 no.5
• /
• pp.811-821
• /
• 2023

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.7 no.6
• /
• pp.339-343
• /
• 2012

Security and monitoring system has many applications and commonly used for detection, warning, alarm, etc. As the networking technology advances, user requirements are getting higher. An intelligent and cooperative surveillance system is proposed to meet current user demands and improve the performance. This paper focuses on the implementation issue for the embedded intelligent surveillance system. To cover wide area cooperative function is implemented and connected by wireless sensor network technology. Also to improve the performance lots of sensors are employed into the surveillance system to reduce the error but improve the detection probability. The proposed surveillance system is composed of vision sensor (camera), mic array sensor, PIR sensor, etc. Between the sensors, data is transferred by IEEE 802.11s or Zigbee protocol. We deployed a private network for the sensors and multiple gateways for better data throughput. The developed system is targeted to the traffic accident detection and alarm. However, its application can be easily changed to others by just changing software algorithm in a DSP chip.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.6
• /
• pp.547-557
• /
• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.8
• /
• pp.780-786
• /
• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• 대한예방의학회:학술대회논문집
• /
• 1994.02a
• /
• pp.651-657
• /
• 1994

To assess quantitatively the association between benzene exposure and leukemia, we examined the mortality rate of a cohort with occupational exposure to benzene. Cumulative exposure for each cohort member was estimated from historical air-sampling data and, when no sampling data existed, from interpolation on the basis of existing data. The overall standardized mortality ratio (a measure of relative risk multiplied by 100) for leukemia was 337 (95 percent confidence interval, 154 to 641), and that for multiple myeloma was 409 (95 percent confidence interval, 110 to 1047). With stratification according to levels of cumulative exposure, the standardized mortality ratios for leukemia increased from 109 to 322, 1186, and 6637 with increases in cumulative benzene exposure from less than 40 parts per million-years (ppm-years), to 40 to 199, 200 to 399, and 400 or more. respectively. A cumulative benzene exposure of 400 ppm years is equivalent to a mean annual exposure of 10 ppm over a 40-year working lifetime; 10 ppm is the currently enforceable standard in the United States for occupational exposure to benzene. To examine the shape of the exposure-response relation, we performed a conditional logistic-regression analysis, in which 10 controls were matched to each cohort member with leukemia. From this model, it can be calculated that protection from benzene induced leukemia would increase exponentially with any reduction in the permissible exposure limit.

• Safety and Health at Work
• /
• v.3 no.1
• /
• pp.67-70
• /
• 2012

The surveillance programme of work-related diseases (WRD) is based on a network of occupational physicians who notify all WRD diagnosed during a two-week observation period. The aims are mainly to estimate the prevalence of non-compensated WRD in the working population according to socio economic factors; to determine new indicators of occupational health; to update the lists of compensable occupational diseases; to understand and assess under-compensation and under-notification. The participation rate for occupational physicians is around 33% in 2008. The main WRD are the musculoskeletal disorders, followed by the mental disorders. This 2-week protocol, repeated regularly, provides useful data on frequency of pathologies linked to employment as well as an estimate of unreported WRD subject to compensation or non-compensated WRDs, and the trends of WRDs over the time.

• Korea Journal of Hospital Management
• /
• v.28 no.3
• /
• pp.1-14
• /
• 2023

Purposes: It is very important to establish a clinical data warehouse based on a common data model to offset the different data characteristics of each medical institution and for drug surveillance. This study attempted to establish a clinical data warehouse for Dankook university hospital for drug surveillance, and to derive the main items necessary for development. Methodology/Approach: This study extracted the electronic medical record data of Dankook university hospital tracked for 9 years from 2013 (2013.01.01. to 2021.12.31) to build a clinical data warehouse. The extracted data was converted into the Observational Medical Outcomes Partnership Common Data Model (Version 5.4). Data term mapping was performed using the electronic medical record data of Dankook university hospital and the standard term mapping guide. To verify the clinical data warehouse, the use of angiotensin receptor blockers and the incidence of liver toxicity were analyzed, and the results were compared with the analysis of hospital raw data. Findings: This study used a total of 670,933 data from electronic medical records for the Dankook university clinical data warehouse. Excluding the number of overlapping cases among the total number of cases, the target data was mapped into standard terms. Diagnosis (100% of total cases), drug (92.1%), and measurement (94.5%) were standardized. For treatment and surgery, the insurance EDI (electronic data interchange) code was used as it is. Extraction, conversion and loading were completed. R language-based conversion and loading software for the process was developed, and clinical data warehouse construction was completed through data verification. Practical Implications: In this study, a clinical data warehouse for Dankook university hospitals based on a common data model supporting drug surveillance research was established and verified. The results of this study provide guidelines for institutions that want to build a clinical data warehouse in the future by deriving key points necessary for building a clinical data warehouse.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.394-396
• /
• 2017

In various types of UAV systems, which have been developed recently, the communication system that is responsible for the connection between the ground control unit and the UAV is called the data link.Especially, in the data link used in systems for transmission of surveillance images from UAV in real time, stability of communication should be ensured. In this paper, the design of the data link modem was proposed for the purpose of applying for UAV for surveillance. And, the designed wad verified through the performance measurement of the implemented systems.

• Journal of Advanced Navigation Technology
• /
• v.16 no.4
• /
• pp.578-585
• /
• 2012

CNS/ATM(Communication Navigation Surveillance/Air Traffic Management) was adopted as a standard navigation system of 21st century. Therefore, ICAO(International Civil Aviation Organization) members are developing the technology and infrastructure of CNS/ATM. ADS-B(Automatic Dependent Surveillance-Broadcast) system and Multilateration system are being implemented in the surveillance field of CNS/ATM. Multilateration system is installed in order to complement radar system and to surveil blind areas. Also, Multilateration system using TDOA(Time Difference Of Arrival) is more accurate than radar. In this paper, we applied an IMM(Interacting Multiple Model) filter which is widely used in radar systems to the Multilateration data in order to improve the reliability of the Multilateration data. Comparisons with the original Multilateration data and the Multilateration data with the IMM filter show that the ADS-B data with the IMM filter provides a better performance: 38.37% near the airport, 20.86% around 10 miles of the airport.

• Journal of Korea Multimedia Society
• /
• v.22 no.10
• /
• pp.1199-1207
• /
• 2019

Video surveillance data, which is used for preemptive or post-emptive action against any event or accident, is required for monitoring the location, but is reducing the capacity of the image data by removing intervals for cost reduction and system persistence. Such a video surveillance system is fixed in a certain position and monitors the area only within a limited angle, or monitors only the fixed area without changing the angle. At this time, the video surveillance system that is monitored only within a limited angle shows that the variation object such as the floating population shows different status in the image, and the background of the image maintains a generally constant appearance. The static objects in the image do not need to be stored in all the images, unlike the dynamic objects that must be continuously shot, and occupy a storage space other than the necessary ones. In this paper, we propose a mechanism to analyze the image, store only the small size image for the fixed background, and store it as image data only for variable objects.