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Currently, many intelligent building energy management systems (BEMSs) are emerging for saving energy in new and existing buildings and realizing a sustainable society worldwide. However, installing an intelligent BEMS in existing buildings does not realize an innovative and advanced society because it only involves simple equipment replacement (i.e., replacement of old equipment or LED (Light Emitting Diode) lamps) and energy savings based on a stand-alone system. Therefore, artificial intelligence (AI) is applied to a BEMS to implement intelligent energy optimization based on the latest ICT (Information and Communications Technologies) technology. AI can analyze energy usage data, predict future energy requirements, and establish an appropriate energy saving policy. In this paper, we present a dynamic heating, ventilation, and air conditioning (HVAC) scheduling method that collects, analyzes, and infers energy usage data to intelligently save energy in buildings based on reinforcement learning (RL). In this regard, a hotel is used as the testbed in this study. The proposed method collects, analyzes, and infers IoT data from a building to provide an energy saving policy to realize a futuristic HVAC (heating system) system based on RL. Through this process, a purpose-oriented energy saving methodology to achieve energy saving goals is proposed.
Sanguk Park; Sangmin Park; Myeong-In Choi; Sanghoon Lee; Tacklim Lee; Seunghwan Kim; Keonhee Cho; Sehyun Park. Reinforcement Learning-Based BEMS Architecture for Energy Usage Optimization. Sensors 2020, 20, 4918 .
AMA StyleSanguk Park, Sangmin Park, Myeong-In Choi, Sanghoon Lee, Tacklim Lee, Seunghwan Kim, Keonhee Cho, Sehyun Park. Reinforcement Learning-Based BEMS Architecture for Energy Usage Optimization. Sensors. 2020; 20 (17):4918.
Chicago/Turabian StyleSanguk Park; Sangmin Park; Myeong-In Choi; Sanghoon Lee; Tacklim Lee; Seunghwan Kim; Keonhee Cho; Sehyun Park. 2020. "Reinforcement Learning-Based BEMS Architecture for Energy Usage Optimization." Sensors 20, no. 17: 4918.
To build sustainable smart energy cities (SECs) around the world, many countries are now combining customized services and businesses within their energy infrastructure and urban environments. Such changes could then promote the development of platforms that ultimately provide benefits for citizens such as convenience, safety, and cost savings. Currently, the development of technologies for SECs focuses on independent products and unit technology. However, this is problematic, as it may not be possible to develop sustainable cities if there is a lack of connectivity between various elements within the SEC. To solve such problems, this paper presents an AI-based physical and virtual platform using a 5-layer architecture to develop a sustainable smart energy city (SSEC). The architecture employs both a top-down and bottom-up approach and the links between each energy element in the SSEC can readily be analyzed. The economic analysis based on return on investment (ROI) is carried out by comparing the economic benefits before and after the application of this system. Deploying the proposed platform will enable the speedy development and application of new services for SSECs and will provide SSECs with measures to ensure sustainable development, such as rapid urban development, and cost reductions.
Sanguk Park; Sanghoon Lee; Sangmin Park; Sehyun Park. AI-Based Physical and Virtual Platform with 5-Layered Architecture for Sustainable Smart Energy City Development. Sustainability 2019, 11, 4479 .
AMA StyleSanguk Park, Sanghoon Lee, Sangmin Park, Sehyun Park. AI-Based Physical and Virtual Platform with 5-Layered Architecture for Sustainable Smart Energy City Development. Sustainability. 2019; 11 (16):4479.
Chicago/Turabian StyleSanguk Park; Sanghoon Lee; Sangmin Park; Sehyun Park. 2019. "AI-Based Physical and Virtual Platform with 5-Layered Architecture for Sustainable Smart Energy City Development." Sustainability 11, no. 16: 4479.
Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it is necessary to take appropriate action accordingly. There has been an increasing effort to develop such disaster management systems worldwide by applying information communication technology (ICT), and many studies have been conducted in practice. In this paper, an augmented reality (AR)-based Smart Building and Town Disaster Management System is suggested in order to acquire visibility and to grasp occupants in case of fire disasters in buildings. This system provides visualization information and optimal guide for quick initial response by utilizing smart element AR-based disaster management service through linkage of physical virtual domain in the building. Additionally, we show a scenario flow chart of the fire extinguishment process according to the time from the ignition stage to the extinguishment stage in the building. Finally, we introduce the related sensors, the actuators, and a small test-bed for AR-based disaster management service. This test-bed was designed for interlocking and interoperability test of the system between the sensors and the actuators. It is expected that the proposed system can provide a quick and safe rescue guideline to the occupants and rescuers in the building where fire is generated and in regions of poor visibility.
Sangmin Park; Soung Hoan Park; Lee Won Park; Sanguk Park; Sanghoon Lee; Tacklim Lee; Sang Hyeon Lee; Hyeonwoo Jang; Seung Min Kim; Hangbae Chang; Sehyun Park. Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure. Applied Sciences 2018, 8, 2239 .
AMA StyleSangmin Park, Soung Hoan Park, Lee Won Park, Sanguk Park, Sanghoon Lee, Tacklim Lee, Sang Hyeon Lee, Hyeonwoo Jang, Seung Min Kim, Hangbae Chang, Sehyun Park. Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure. Applied Sciences. 2018; 8 (11):2239.
Chicago/Turabian StyleSangmin Park; Soung Hoan Park; Lee Won Park; Sanguk Park; Sanghoon Lee; Tacklim Lee; Sang Hyeon Lee; Hyeonwoo Jang; Seung Min Kim; Hangbae Chang; Sehyun Park. 2018. "Design and Implementation of a Smart IoT Based Building and Town Disaster Management System in Smart City Infrastructure." Applied Sciences 8, no. 11: 2239.
In this paper, we aim to provide a power trade system that will promote a sustainable electrical energy transaction ecosystem between prosumers and consumers of smart homes. We suggest a blockchain-based peer-to-peer (P2P) energy transaction platform be implemented to enable efficient electrical energy transaction between prosumers. We suggest the platform be built on the blockchain, as this technology allows a decentralized and distributed trading system, and allows a more transparent, trustworthy and secure P2P trading environment. We believe that such characteristics of the blockchain are necessary in electrical energy transactions within the smart home environment because the smart home aims to enhance user comfort and security, along with energy conservation and cost-savings. First, we classify the two different types of P2P trade to identify which will best benefit from the use of the suggested blockchain-based P2P energy-transaction platform. Within the two types of P2P trade, that we classify (pure P2P trade and hybrid P2P trade), the hybrid P2P trade will benefit more from a blockchain-based P2P energy-transaction platform. In the blockchain-based P2P energy-transaction platform, a smart contract is embedded in the blockchain and called an energy tag. The energy tag will set conditions for making every future energy transaction more cost-efficient while maintaining the most ideal and high-quality energy selection. With the blockchain-based energy tag in the energy-transaction process, multiple energy resources and home appliances will be democratically connected in order to provide users with high-quality, low-cost energy at all times and locations. In this paper, we provide simulation results that compare the unit price of electrical energy on the suggested platform to the unit price of electrical energy set by currently existing conventional power-generation companies. Additionally, we present simulation results that calculate how long initial investments to create a smart home environment that enables P2P energy transactions will take to be paid back. Based on simulation results, we believe that, in the long run, the suggested blockchain-based P2P energy-transaction platform will create a sustainable energy-transaction environment between consumers and prosumers, and the expanding ecosystem will enable the development of a trusted, sustainable, secure and energy-efficient energy transaction environment.
Lee Won Park; Sanghoon Lee; Hangbae Chang. A Sustainable Home Energy Prosumer-Chain Methodology with Energy Tags over the Blockchain. Sustainability 2018, 10, 658 .
AMA StyleLee Won Park, Sanghoon Lee, Hangbae Chang. A Sustainable Home Energy Prosumer-Chain Methodology with Energy Tags over the Blockchain. Sustainability. 2018; 10 (3):658.
Chicago/Turabian StyleLee Won Park; Sanghoon Lee; Hangbae Chang. 2018. "A Sustainable Home Energy Prosumer-Chain Methodology with Energy Tags over the Blockchain." Sustainability 10, no. 3: 658.