• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1131-1150
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• 2014

One of the issues in extending the range of applicable problems of real-time hybrid simulation is the computation speed of the simulator when large-scale computational models with a large number of DOF are used. In this study, functionality of real-time dynamic simulation of MDOF systems is achieved by creating a logic circuit that performs the step-by-step numerical time integration of the equations of motion of the system. The designed logic circuit can be implemented to an FPGA-based system; FPGA (Field Programmable Gate Array) allows large-scale parallel computing by implementing a number of arithmetic operators within the device. The operator splitting method is used as the numerical time integration scheme. The logic circuit consists of blocks of circuits that perform numerical arithmetic operations that appear in the integration scheme, including addition and multiplication of floating-point numbers, registers to store the intermediate data, and data busses connecting these elements to transmit various information including the floating-point numerical data among them. Case study on several types of linear and nonlinear MDOF system models shows that use of resource sharing in logic synthesis is crucial for effective application of FPGA to real-time dynamic simulation of structural response with time step interval of 1 ms.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• Spatial Information Research
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• v.11 no.1
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• pp.41-60
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• 2003

It is noted that the paper mapping system for University Building Facility has many limitations in terms of data maintenance, real-time GIS data acquisition, and economic efficiency. The aim of this research was to evaluate an operational potential of an on site real-time mobile GIS technique to resolve the problem faced in the university. The idea is based upon the recent trends in the field of 'Telecommunication and Information Technology' that uses a PDA (personal Digital Assistants), wireless network computing, mobile computing, etc. A real time mobile GIS approach has been adopted, in which a PDA is linked to a wireless internet and field workers record data on the computer at the site and analyse data on site. While there should be a considerable number and variety of factors associated with real-time mobile GIS quality, this research focuses on three criteria that are identified as fundamental to customer requirements; (1) data quarry (2) spatial analysis (3) real-time GIS database building. 'Art--empirical study for a case study facility has been conducted to confirm the validity for the system. The system has been checked experimentally, enabled the field users to quarry the data required simply and execute spatial analysis (buffer, overlay etc.,) accommodating versatile alternatives on the site. Detailed visual maps can be generated over large areas quickly and easily. The PDA interface, in particular, were ideally suited for field users to interactively displaying positional information with attribute data. This system has shown to be quite convenient to maintaining a highly reliable database since it could playa crucial role in documenting at real-time basis temporal and spatial changes occurred in the facilities. It is anticipated that this research output will greatly serve to introduce the reliable and cost-effective facility mapping system in the university by overcoming serious constraints suffered from the past non-real time mobile GIS approach.

• Journal of the Korea Computer Graphics Society
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• v.11 no.1
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• pp.40-49
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• 2005

Several optimization techniques have been proposed for volume ray casting, but these cannot achieve real-time frame rates. In addition, it is difficult to apply them to some applications that require perspective projection. Recently, hardware-based methods using 3D texture mapping are being used for real-time volume rendering. Although rendering speed approaches real time, the larger volumes require more swapping of volume bricks for the limited texture memory. Also, image quality deteriorates compared with that of conventional volume ray casting. In this paper, we propose a data structure for real-time volume ray casting named PERM (Precomputed dEnsity and gRadient Map). The PERM stores interpolated density and gradient vector for quantized cells. Since the information requiring time-consuming computations is stored in the PERM, our method can ensure interactive frame rates on a consumer PC platform. Our method normally produces high-quality images because it is based on conventional volume ray casting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.602-605
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• 2001

This paper focus on a method to use Ethernet Network for Industrial Communication Network. Ethernet use the CSMA/CD MAC(Medium Access Control) Protocol at the Data-Link Layer, Which isn't suit for Industrial Communication Network requiring Real-Time Communication, periodic data processing, critical data processing characteristics. In this paper we proposed the Virtual Polling Algorithm at the Application Layer will be solution of using the Ethernet Network for the Industrial Communication Network, Proposed Algorithm terminate the Collision in the network thus Delay Time is reduced and Real-Time Communication will be implemented.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.1-16
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• 2011

The real-time ubiquitous environment is required to be able to process a series of sensor data within limited time. The whole sensor data processing consists of several phases : getting data out of sensor, acquiring context and responding to users. The ubiquitous computing middleware is aware of the context using the input sensor data and a series of data from database or knowledge-base, makes a decision suitable for the context and shows a response according to the decision. When the real-time ubiquitous environment gets a set of sensor data as its input, it needs to be able to estimate the delay-time of the sensor data considering the available resource and the priority of it for scheduling a series of sensor data. Also the sensor data of higher priority can stop the processing of proceeding sensor data. The research field for such a decision making is not yet vibrant. In this paper, we propose a queuing time computation algorithm for sensor data processing in real-time ubiquitous environment.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.339-349
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• 2005

For recent years, data broadcast technology has been recognized as a very effective data delivery mechanism in mobile computing environment with a large number of cli;ents. Especially, a hybrid broadcast algorithm in real-time environment, which integrates one-way broadcast and on-demand broadcast, has an advantage of adapting the requests of clients to a limited up-link bandwidth and following the change of data access pattern. However, previous hybrid broadcasting algorithms has a problem in the methods to get a grip on the change of data access Pattern. It is caused by the diminution of requests for the data items which are contained in periodic broadcasting schedule because they are already broadcasted. To solve this problem, existing researches may remove data items in periodic broadcasting schedule over a few cycles multiplying cooling factor or find out the requests of data items with extracting them on purpose. Both of them are the artificial methods not considering the property of data. In this paper, we propose a real-time adaptive hybrid broadcasting based on data type(RTAHB-DT) to broadcast considering data property and analysis the performance of our aigorithm through simulation study.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3131-3139
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• 1999

Satisfying the rigid timing requirements of various real-time activities in real-time systems often requires some special methods to tune the systems run-time behaviors. Unbounded blocking can be caused when a high priority activity cannot preempt a low priority activity. In such situation, it is said that a priority inversion has occurred. The priority inversion is one of the problems which may prevent threads from meeting the deadlines in the real-time systems. It is difficult to remove such priority inversion problems in the kernel at the same time to bound the worst case blocking time for the threads. A thread is a piece of executable code which has access to data and stack. In this paper, a new real-time systems. It is difficult to remove such priority inversion problems in the kernel at the same time to bound the worst case blocking time for the threads. A threads is a piece of executable code which has access to data and stack. In this paper, a new real-time server model, which minimizes the duration of priority inversion, is proposed to reduce the priority inversion problem. The proposed server model provides a framework for building a better server structure, which can not only minimize the duration of the priority inversion, but also reduce the deadline miss ratio of higher priority threads.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1379-1386
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• 2017

As the Internet of Things evolves, various IoT services are provided. IFTTT is an abbreviation for If This Then That and refers to a service that links different web-based services. This paper proposes a system that generates and manages rules that combine the possibility of IFTTT service and the real-time event processing according to the concept of IoT service. Conventional database-based data processing methods are burdened to process a lot of data of IoT devices coming in real-time. The IoT device's data can be classified into formal data such as the amount of power, temperature value and position information, and informal data such as video or image data. Thus, this system classifies the data stream of IoT devices coming in real-time using the CEP engine Esper into a file signature table, classifies the formal/informal data, and shows the condition of the device data defined by the user and the service to be provided by applying the service.