On lot of ships, Ballast Water Treatment Systems(BWTS) are in use, or the newly built ship should be mandatory installation by 2017. It is IMO(International Maritime Organization) regulations. Because the vessel is in long distance, It is managed this system only in the vessel and it may occur considerable cost of maintenance when a problem arises from BWTS. We describe in this paper how to monitor treated ballast water to make sure the ballast water and BWTS on a ship is in proper condition, but before the port entrance. In addition, analysing and forecasting trend signal to prevent failure. Also we can expect reduce the cost of BWTS maintenance. We can monitor the sensor data value's change which collected through satellite from BWTS. And we can observate the ballasting and de-ballasting state of the vessel easily.

Demand Controller is a load control device that monitor the current power consumption and calculate the forecast power to not exceed the power set by consumer. Accurate demand forecasting is important because of controlling the load use the way that sound a warning and then blocking the load when if forecasted demand exceed the power set by consumer. When if consumer with fluctuating power consumption use the existing forecasting method, management of demand control has the disadvantage of not stable. In this paper, load forecasting of the unit of seconds using the Exponential Smoothing Methods, ARIMA model, Kalman Filter is proposed. Also simulation of load forecasting of the unit of the seconds methods and existing forecasting methods is performed and analyzed the accuracy. As a result of simulation, the accuracy of load forecasting methods in seconds is higher.

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

In this paper, we propose a position estimation method of an entertainment robot in a performance stage. A position information is needed to produce contents of an entertainment robot performance. First, the performance stage is realized by a CD (cadmium sulfide) sensor matrix with a constant distance. Then the proposed position estimation uses ON/OFF information of a CD sensor in a performance stage. We confirmed that the position of the robot is detected with an maximum 4cm in position evaluation experiments. The robot was traveling to the final target position in the walking experiment with 75cm and 120cm path plan. Ultimately, the effectiveness of the proposed estimation is assessed by experimental results of a robot in performance stage. Also, in the proposed system installed by a robot performance contents, there is no necessity to mount a position estimation device on a robot; therefore an advantage of our system is that an entertainment robot commercialized by robot vendor can be utilized in our performance stage directly.

This paper demonstrates the benefit of using MOOS-IvP in the development of control system for Unmanned Underwater Vehicles(UUV). The demand for autonomy in UUVs has significantly increased due to the complexity in missions to be performed. Furthermore, the increased number of sensors and actuators that are interconnected through a network has introduced a need for a middleware platform for UUVs. In this context, MOOS-IvP, which is an open source software architecture, has been developed by several researchers from MIT, Oxford University, and NUWC. The MOOS software is a communication middleware based on the publish-subscribe architecture allowing each application to communicate through a MOOS database. The IvP Helm, which is one of the MOOS modules, publishes vehicle commands using multi-objective optimization in order to implement autonomous decision making. This paper explores the benefit of MOOS-IvP in the development of control software for UUVs by using a case study with an auto depth control system based on self-organizing fuzzy logic control. The simulation results show that the design and verification of UUV control software based on MOOS-IvP can be carried out quickly and efficiently thanks to the reuse of source codes, modular-based architecture, and the high level of scalability.

In this paper, we propose the hardware and software of a test-bed of a hovering AUV (autonomous underwater vehicle). Test-bed to develop as the underwater robot for the hovering -type is planning to apply for marine resource development and exploration for deep sea. The RTU that controls a azimuth thruster and a vertical thruster of test-bed is a intergrated-type thruster. The main control unit that collects sensor's data and performs high-speed processing and controls a movement of test-bed is a underwater hybrid navigation system. Also it transfers position, posture, state information of test-bed to the host PC of user using a wireless communication. The host PC checks a test-bed in real time by using a realtime monitoring system that is implemented by LabVIEW.

The CRT monitor display system for SONAR signal that are commonly used in ships or naval vessels uses vector scanning method. Therefore the processing circuits of the system are complex. Also the purchase of parts is difficult as well as high-cost because the production had been shut down. FPGA-based embedded system is flexible to various digital applications because it can be able to simplify processing circuits and to make a easy customized design for end user, and it provides low-cost high-speed performance. In this paper, we describe an implementation of FPGA embedded system for real-time SONAR signal display using the triple buffering method to overcome some weakness of existing CRT system. Our system provides real-time acquisition and display capability of SONAR signal, and removes afterimage effect that is a critical problem of the system proposed in the preceding study.

The software running on avionic system is required to be highly reliable and productive. The air transport industry has developed ARINC Specification 653(ARINC653) as a standardized software requirement of avionics computers. The document specifies the interface boundary between avionics application software and the core executive software. Dependability in ARINC 653 is provided by spatial and temporal partitioning whilst fault-tolerance is provided by health monitoring mechanism. Legacy real-time operating systems are used to support ARINC653 health monitor on integrated modular avionics(IMA). However, legacy real-time operating systems are costly and difficult to modify the kernel. In this paper, we suggest a Linux-based ARINC653 health monitor. Functionalities to support ARINC653 health monitor are implemented as a Linux kernel module and its performance is evaluated.