• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.222-229
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• 2022

Although stochastic programming and feedback control approaches could efficiently mitigate the overdue risks caused by inherent uncertainties in ground conditions, the lack of formal representations of planners' rationales for resource allocation still prevents planners from applying these approaches due to the inability to consider comprehensive resource allocation policies for hard rock tunnel projects. To overcome the limitations, the authors developed an ontology that represents the project duration estimation rationales, considering the impacts of ground conditions, excavation methods, project states, resources (i.e., given equipment fleet), and resource allocation policies (RAPs). This ontology consists of 5 main classes with 22 subclasses. It enables planners to explicitly and comprehensively represent the necessary information to rapidly and consistently estimate the excavation durations during construction. 10 rule sets (i.e., policies) are considered and categorized into two types: non-progress-related and progress-related policies. In order to provide simplified information about the remaining durations of phases for progress-related policies, the ontology also represents encoding principles. The estimation of excavation schedules is carried out based on a hypothetical example considering two types of policies. The estimation results reveal the feasibility, potential for flexibility, and comprehensiveness of the developed ontology. Further research to improve the duration estimation methodology is warranted.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.623-634
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• 2013

In this study, we provide empirical evidence of whether a spatial correlation among mode choices at the TAZ(Traffic Analysis Zone) level exists based on transit smart card data observed in Seoul, Korea. The results show that the areas with a higher probability that passengers choose to take a bus are clustered and that those regions have fewer metro stations than bus stations. We also found that the spatial correlation turned out to be statistically meaningful and provided an opportunity for the potential use of the spatial correlation in modeling mode choices. A reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1135-1145
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• 2022

Due to increase in concerns related to the climate change, state-wide promotion of the carbon neutrality has been in progress thus far. Smart City could be one of the measures as the initiative to mitigate the missions process. The primary purpose of Smart City can be summarized to be maximization of the social net-beneift to be returned for the local citizens and derivation of the optimal pattern of the energy consumption could belong to one of the elements included in the net-benefit. Currently, the energy consumption by the buildings has been determined to be responsible for the greatest consumption among the sectors considered to be energy-intensive. Moreover, considering the fact that the consumption by operations of HVAC is responsible for nearly 40% in the commercial buildings, it is virtually not possible to optimize schedules for the energy consumption with considerable deliverables from the perspective of the urban planners. Thus, the methods to implement the optimal schedules for the HVAC commissioned with the OHUs were concluded to be the suitable candidate resources for the simulation by EnergyPlus capable of monitoring the thermal changes in each subject space in the present research.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.165-172
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• 2024

In this paper, we designed a smart home system that can be used intuitively and easily in everyday life, such as sending text messages to users, providing various information and scheduling using smart AI, and providing lighting and atmosphere suitable for the atmosphere in situations such as listening to music using neopixels, as well as using ESP32, RFID, and Google Cloude Console using raspberry pie. As a result of the experiment, it was confirmed that security characters were normally sent to users when RFID was recognized on ESP32 connected to Wi-Fi even if the power was reconnected, and smart AI using Neopixel lighting, Raspberry Pie, and voice recognition, which calculated frequency, also changed the recognition rate over distance, but it worked.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1205-1210
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• 2004

The 4-20mA analog signal used in the various industrial fields to interface sensor in distributed process control has been replaced with relatively simple digital networks, called "fieldbus, and recently by Ethernet. Significant advances in Internet and computer technology have made it possible to develop an Internet based control, monitoring, and operation scheduling system for heating, ventilation and air-conditioning (HVAC) systems. The seamless integration of data networks with control networks allows access to any control point from anywhere. Field compatible field devices become so-called "smart" devices, capable of executing simple control, diagnostic and maintenance functions and providing bidirectional serial communication to higher level controller. The most important HVAC of BAS has received nationwide attention because of higher portion of more than 40% in building sector energy use and limited resources. This paper presents the Internet-based monitoring and control architecture and development of LonWorks control modules for AHU (air handling units) of HVAC in viewpoint of configuring BAS network. This article addresses issues in architecture section, electronics, embedded processors and software, and internet technologies.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.50-64
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• 2012

Quality of Service (QoS) and fairness considerations are undoubtedly essential parameters that need to be considered in the design of next generation scheduling algorithms. This work presents a novel game theoretic cross-layer design that offers optimal allocation of wireless resources to heterogeneous services in Orthogonal Frequency Division Multiple Access (OFDMA) networks. The method is based on the Axioms of the Symmetric Nash Bargaining Solution (S-NBS) concept used in cooperative game theory that provides Pareto optimality and symmetrically fair resource distribution. The proposed strategies are determined via convex optimization based on a new solution methodology and by the transformation of the subcarrier indexes by means of time-sharing. Simulation comparisons to relevant schemes in the literature show that the proposed design can be successfully employed to typify ideal resource allocation for next-generation broadband wireless systems by providing enhanced performance in terms of queuing delay, fairness provisions, QoS support, and power consumption, as well as a comparable total throughput.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.34-38
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• 2012

The recent increase in use of the IEEE 802.15.4 standard for wireless connectivity in personal area networks makes of it an important technology for low-cost low-power wireless personal area networks. Studies showed that voice communications over IEEE 802.15.4 networks is feasible by Guaranteed Time Slot (GTS) allocation; but there are some constraints to accommodate voice transmission beyond two hops due to the excessive transmission delay. In this paper, we propose a GTS allocation scheme for bidirectional voice traffic in IEEE 802.15.4 multihop networks with the goal of achieving fairness and optimization of resource allocation. The proposed scheme uses a greedy algorithm to allocate GTSs to devices for successful completion of voice transmission with efficient use of bandwidth while considering closest devices with another factor for starvation avoidance. We analyze and validate the proposed scheme in terms of fairness and resource optimization through numeral analysis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.179-182
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• 2012

스마트 기기의 보급률 향상에 따라 다양한 분야의 스마트 기기 애플리케이션 혹은 앱이 개발되어 활용되고 있으며, 동물 소리, 자연의 소리 등의 효과음을 선택 및 재생할 수 있는 앱이 개발되고 있다. 이러한 대부분의 앱들은 제공되는 효과음 중 특정 효과음만을 선택하여 1회 단순 재생할 수 있도록 하는 사용자 인터페이스를 채택하고 있다. 본 논문에서는 여러 개의 효과음들을 미리 선택하여 등록하였다가 재생할 수 있는 인터페이스를 채택한 효과음 재생 앱을 설계 및 개발하였다. 개발된 앱은 업무 특성 상 사전에 필요한 효과음들을 특정 시나리오에 따라 순차적으로 미리 선택 및 등록하여 재생이 필요한 환경에서 유용하게 사용될 수 있다.