• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3475-3489
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• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.257-266
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• 2015

There is no polynomial-time algorithm that can be obtain the optimal solution for economic load dispatch problem with non-convex fuel cost functions. Therefore, electrical field uses quadratic fuel cost function unavoidably. This paper proposes a valve-point optimization (VPO) algorithm for economic load dispatch problem with non-convex fuel cost functions. This algorithm sets the initial values to maximum powers $P_i{\leftarrow}P_i^{max}$ for each generator. It then reduces the generation power of generator i with an average power cost of $_{max}\bar{c}_i$ to a valve point power $P_{ik}$. The proposed algorithm has been found to perform better than the extant heuristic methods when applied to 13 and 40-generator benchmark data. This paper consequently proves that the optimal solution to economic load dispatch problem with non-convex fuel cost functions converges to the valve-point power of each generator.

• Journal of KIBIM
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• v.6 no.3
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• pp.49-56
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• 2016

As project opportunities for the Architecture, Engineering and Construction (AEC) industry have grown more complex and larger, the utilization of Building Information Modeling (BIM) technologies for three-dimensional (3D) design and simulation practices has been increasing significantly; the typical applications of the BIM technologies include clash detection and design alternative based on 3D planning, which have been expanded over to the technology of construction management in the AEC industry for virtual design and construction. As for now, commercial BIM software has been operated under a single-user environment, which is why initial costs for its introduction are very high. Cloud computing, one of the most promising next-generation Internet technologies, enables simple Internet devices to use services and resources provided with BIM software. Recently in Korea, studies to link between BIM and cloud computing technologies have been directed toward saving costs to build BIM-related infrastructure, and providing various BIM services for small- and medium-sized enterprises (SMEs). This study addressed development of the usage metering functions of BIM software under cloud computing architecture in order to archive and use BIM data and create an optimal revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources. For the reason, we surveyed relevant cases, and then analyzed needs and requirements from AEC industry. Based on the relevant cases, customizing for cloud BIM and design for the development was performed. We also surveyed any related-law to support cloud computing-based BIM service. Finally, we proposed herein how to optimally design and develop the usage metering functions of cloud BIM software.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.117-122
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• 2021

Autonomous driving allows cars to drive without people and is being studied very actively thanks to the recent development of artificial intelligence technology. Among artificial intelligence technologies, deep reinforcement learning is used most effectively. Deep reinforcement learning requires us to build a neural network using an appropriate activation function. So far, many activation functions have been suggested, but different performances have been shown depending on the field of application. This paper compares and evaluates the performance of which activation function is effective when using deep reinforcement learning to learn autonomous driving on highways. To this end, the performance metrics to be used in the evaluation were defined and the values of the metrics according to each activation function were compared in graphs. As a result, when Mish was used, the reward was higher on average than other activation functions, and the difference from the activation function with the lowest reward was 9.8%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.691-700
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• 2021

The IP cameras have rapidly replaced the analog CCTVs as the cameras have the advantages of not only being able to remotely monitor, but also supplying power through the UTP cable, In this paper, we introduce the protocol architecture of the ONVIF standard which is widely applied to the IP camera and other Internet protocols to support it, and implement the ONVIF Device on a commercial board. Although these functions can be controlled by the Client (PC), several functions such as privacy masks, temperature display of the thermal camera, and ROI (Region of Interest) are implemented through a web viewer on the device. Through the experiment, the functions of ONVIF Profile S and web viewer are verified through SOAP messages exchanged between Device (IP camera) and Client program and streamed images.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.77-84
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• 2024

Over the past few years, IoT edges have begun to emerge based on new low-latency communication protocols such as 5G. However, IoT edges, despite their enormous advantages, pose new complementary threats, requiring new security solutions to address them. In this paper, we propose a cloud environment-based IoT edge architecture model that complements IoT systems. The proposed model acts on machine learning to prevent security threats in advance with network traffic data extracted from IoT edge devices. In addition, the proposed model ensures load and security in the access network (edge) by allocating some of the security data at the local node. The proposed model further reduces the load on the access network (edge) and secures the vulnerable part by allocating some functions of data processing and management to the local node among IoT edge environments. The proposed model virtualizes various IoT functions as a name service, and deploys hardware functions and sufficient computational resources to local nodes as needed.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.85-96
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• 2017

IoT-Cloud service, integration of Internet of Things (IoT) and Cloud, is becoming a critical model for realizing creative and futuristic application services. Since IoT machines have little computing capacity, it is effective to attaching public Cloud resources for realizing IoT-Cloud service. Furthermore, utilizing containers and adopting a microservice architecture for developing IoT-Cloud service are useful for effective realization. The quality of microservice based IoT-Cloud service is affected by service function chaining which inter-connects each functions. For example, an issue with some of the functions or a bottleneck of inter-connection can degrade the service quality. To ensure functionality of the entire service, various test procedures considering various service environments are required to improve the service continuously. Hence in this paper, we introduce experimental realization of continuous integration based on DevOps and employ application performance monitoring for Node.js based IoT-Cloud service. Then we discuss its effectiveness.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.73-82
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• 2008

Collecting and managing the sensor information through the Internet is critical to effectively manage and utilize the sensor information. The interworking technique of the sensor network and internet is required to realize the desirable condition for managing and utilizing the sensor information. Among many interworking techniques, the translation technique using the gateway had been widely studied. However, the technique which mounts IP-based Internet protocols directly on the sensor node is getting more attention recently. Particularly, IPv6 is suitable for the communication protocol for the sensor network, because its features, such as abundant address space or address auto-configuration, are well matched with the sensor network. In this paper, we design the tiny UDP/IPv6 protocol functions which are suitable for the sensor network environment, and we implemented the functions with TinyOS based nesC. After we examined the simulation results of by using TOSSIM and TinyViz, we carried out the experimental performance evaluation for the program by mounting the tiny UDP/IPv6 on the sensor node (Mote).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.239-244
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• 2015

We can build regular relationships with customers by integrating SNS (Social Networking Service) and internet shopping mall functions. For example of direct dealing of agricultural products, consumers can find news of regular sellers (seeding, farming, harvesting and new products) in the timeline at their SNS home. Then, they can purchase the necessary products by one click motion. The sellers provide news and discount information for building regular customers. Besides these SNS personal connection building, our system provides shopping mall functions to consumer's SNS home pages with auto classified catalog of products. Then, consumes easily find necessary products and these purchase may lead to regular relationships with sellers. Consumers may redistribute recommendations and reviews and it enables direct communications between consumers who are unknown to each other.