• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.181-193
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• 2009

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.164-170
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• 2012

A Virtual Reality Modeling Language (VRML) database access in remote virtual reality control platform for dyeing enterprise $MiWi^{TM}$ thermal sensor network is presented in this paper. The VRML-ASP framework is introduced for 3D real-time data plotting in this application. The activities of thermal sensor nodes and sensor area are analyzed. The database access framework is optimized for $MiWi^{TM}$ wireless sensor networks. The experimental results show that VRML-ASP database access framework could be a reliable and competitive data-manage candidate for targeted virtual reality remote industrial visualization application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.931-942
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• 2010

A home network provides users with a variety of information services. The kind and quality of the services can be substantially enhanced by utilizing a variety of data from sensors. However, home networks currently limit their potential by focusing on providing multimedia services rather than services utilizing sensor data. Outdoor electronics are frequently made in a form that emphasizes only certain limited functions in contrast to home appliances. Thus, sensors with one or two functions rather than many can be used in outdoor systems and their use will be more economical than using sensor nodes indoors with more complex home appliances. In this study, we chose to work with motion sensors as they have many potential uses, and we selected a parking lot control system with to use the motion sensors. This parking lot control system was implemented and applied as part of a home network. For this purpose, we defined and implemented a protocol to manage the network in a ubiquitous sensor network environment for the wireless home network in this study. Although a network management system in a Ubiquitous Sensor Network (USN) related to this study is being advanced for other projects, the protocol interface and message system have not yet been clearly defined for use in a general purpose network or in an extension into heterogeneous kinds of networks, communication support, etc. Therefore, USN network management should be conducted for management of faults, composition, power, and applications. To verify the performance of the protocol interface designed in this study, we designed and implemented the necessary units (sensor nodes, sensor gateway, and server) for each network section and, with them, proved the validity of this study.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.89-108
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• 2022

The purpose of this study is to reveal the specific current and future shapes of the collaborative network among organizations witch cope the COVID-19 in Korea. For this, this study conducted social network analysis, based on the response data of 73 experts from 36 COVID-19-related organizations. As a result of the analysis, it was confirmed that the Korea Disease Control and Prevention Agency (KDCA) plays a pivotal role as a control tower in coping COVID-19 in all of the analysis of degree, betweenness, and closeness centrality. In addition, the results revealed concrete forms of collaborative relationships among participating organizations in the public and private sectors that constitute the present and future networks centered on the KDCA. Furthermore, this study presented which organizations and relationships should be the focus of establishing a future collaborative network through comparative analysis between the current cooperative network and the network to be built in the future. The analysis results and discussions of this study are expected to be used as useful information for policy development related to collaborative networks that can effectively respond to disasters caused by new diseases in the future.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.773-787
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• 2020

In the injection molding process, the controlling stability of products quality is a very important factor in terms of productivity. Even when the optimum process conditions for the desired product quality are applied, uncontrollable external factors such as ambient temperature and humidity cause inevitable changes in the state of the melt resin, mold temperature. etc. Therefore, it is very difficult to maintain prodcut quality. In this study, a system that learns the correlation between process variables and product weight through artificial neural networks and predicts process conditions for the target weight was established. Then, when a disturbance occurs in the injection molding process and fluctuations in the weight of the product occur, the stability control of the product quality was performed by ANN predicting a new process condition for the change of weight. In order to artificially generate disturbance in the injection molding process, controllable factors were selected and changed among factors not learned in the ANN model. Initially, injection molding was performed with a polypropylene having a melt flow index of 10 g/10min, and then the resin was replaced with a polypropylene having a melt floiw index of 33 g/10min to apply disturbance. As a result, when the disturbance occurred, the deviation of the weight was -0.57 g, resulting in an error of -1.37%. Using the control method proposed in the study, through a total of 11 control processes, 41.57 g with an error of 0.00% in the range of 0.5% deviation of the target weight was measured, and the weight was stably maintained with 0.15±0.07% error afterwards.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.92-99
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• 2016

A wind turbine is controlled for the purpose of obtaining the maximum power below its rated wind speed. Among the methods of obtaining the maximum power, TSR (Tip Speed Ratio) optimal control and P&O (Perturbation and Observation) control are widely used. The P&O control algorithm using the turbine power and rotational speed is simple, but its slow response is a weak point. Whereas TSR control's response is fast, it requires the precise wind speed. A method of measuring or estimating the wind speed is used to obtain a precise value. However, estimation methods are mostly used, because it is difficult to avoid the blade interference when measuring the wind speed near the blades. Neural networks and various numerical methods have been applied for estimating the wind speed, because it involves an inverse problem. However, estimating the wind speed is still a difficult problem, even with these methods. In this paper, a new method is introduced to estimate the wind speed in the wind-power graph by using the turbine power and rotational speed. Matlab/Simulink is used to confirm that the proposed method can estimate the wind speed properly to obtain the maximum power.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.15-26
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• 2013

IP-based Wireless Sensor Networks (IP-WSNs) are gaining importance for their broad range of applications in health-care, home automation, environmental monitoring, industrial control, vehicle telematics and agricultural monitoring. In all these applications, mobility in the sensor network with special attention to energy efficiency is a major issue to be addressed. Because of the energy inefficiency of networks-based mobility management protocols can be supported in IP-WSN. In this paper we propose a network based mobility supported IP-WSN protocol called Multicasting-based inter-Domain Mobility Management Scheme in Sensor-based Fast Proxy Mobile IPv6 Networks (mSFP). Based on [8,20], We present its network architecture and evaluate its performance by considering the signaling and mobility cost. Our analysis shows that the proposed scheme reduces the signaling cost, total cost, and mobility cost. With respect to the number of IP-WSN nodes, the proposed scheme reduces the signaling cost by 7% and the total cost by 3%. With respect to the number of hops, the proposed scheme reduces the signaling cost by 6.9%, the total cost by 2.5%, and the mobility cost by 1.5%. With respect to the number of IP-WSN nodes, the proposed scheme reduces the mobility cost by 1.6%.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.182-189
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• 2016

In this paper, we propose a buoy system based on multi-hop relay networks for ocean observation. The proposed system consists of various sensor modules, a gateway, wireless communication modules, and a remote monitoring site. The sensor modules are integrated with various communication interfaces and connected to the gateway of the proposed buoy system with an unified protocol based on controller area network (CAN)-bus. In order to communicate with the remote monitoring site and extend the coverage, the proposed system uses long-term evolution (LTE) router and XBee mesh network modules. The field test results show that the proposed system can extend the coverage using the proposed multi-hop relay network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.943-961
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• 2020

With the advent of IoT technology and Big Data computing, the importance of WSNs (Wireless Sensor Networks) has been on the rise. For energy-efficient and collection-efficient delivery of any sensed data, lots of novel wireless medium access control (MAC) protocols have been proposed and these MAC schemes are the basis of many IoT systems that leads the upcoming fourth industrial revolution. WSNs play a very important role in collecting Big Data from various IoT sensors. Also, due to the limited amount of battery driving the sensors, energy-saving MAC technologies have been recently studied. In addition, as new IoT technologies for Big Data computing emerge to meet different needs, both sensors and sinks need to be mobile. To guarantee stability of WSNs with dynamic topologies as well as frequent physical changes, the existing MAC schemes must be tuned for better adapting to the new WSN environment which includes energy-efficiency and collection-efficiency of sensors, coverage of WSNs and data collecting methods of sinks. To address these issues, in this paper, a self-organization scheme for mobile sensor networks with mobile multiple sinks has been proposed and verified to adapt both mobile sensors and multiple sinks to 3-dimensional group management MAC protocol. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of the various usage cases. Therefore, the proposed self-organization scheme might be adaptable for various computing and networking environments with big data.