A Sustainability Evaluation of Buildings: A Review on Sustainability Factors to Move towards a Greener City Environment

Energy-efficient and sustainable building management has always been a key concern surrounding buildings. The rise of environmental and social concern in today’s world has brought more attention to the issue of sustainable and smart building management. This paper aims to review the state-of-the-art research and performance on building management that aims to make more sustainable and energy-efficient decisions. This paper classifies building management based on technologies utilized for management and different aspects of management that should be considered when regarding the larger picture of “sustainability”. Additionally, while keeping in mind that long-term sustainability cannot be achieved through energy management alone, this research investigates previous works that also mention diverse aspects that must be taken into consideration when creating a truly successful smart building environment: costs, occupant comfort, and security. Of course, each field deserves an extensive analysis, but the purpose of this review paper is to deliver current research that has brought attention to the rapidly shifting and developing field of smart buildings to provide a macro-level holistic viewpoint on how smart buildings and homes should be approached from a sustainability viewpoint

Molecular Probes to Evaluate the Synthesis and Production Potential of an Odorous Compound (2-methylisoborneol) in Cyanobacteria

The volatile metabolite, 2-Methylisoborneol (2-MIB) produced by cyanobacterial species, causes odor and taste problems in freshwater systems. However, simple identification of cyanobacteria that produce such off-flavors may be insufficient to establish the causal agent of off-flavor-related problems as the production-related genes are often strain-specific. Here, we designed a set of primers for detecting and quantifying 2-MIB-synthesizing cyanobacteria based on mibC gene sequences (encoding 2-MIB synthesis-catalyzing monoterpene cyclase) from various Oscillatoriales and Synechococcales cyanobacterial strains deposited in GenBank. Cyanobacterial cells and environmental DNA and RNA were collected from both the water column and sediment of a eutrophic stream (the Gong-ji Stream, Chuncheon, South Korea), which has a high 2-MIB concentration. Primer sets mibC196 and mibC300 showed universality to mibC in the Synechococcales and Oscillatoriales strains; the mibC132 primer showed high specificity for Pseudanabaena and Planktothricoides mibC. Our mibC primers showed excellent amplification efficiency (100–102%) and high correlation among related variables (2-MIB concentration with water RNA r = 689, p < 0.01; sediment DNA r = 0.794, p < 0.01; and water DNA r = 0.644, p < 0.05; cyanobacteria cell density with water RNA and DNA r = 0.995, p < 0.01). These primers offer an efficient tool for identifying cyanobacterial strains possessing mibC genes (and thus 2-MIB-producing potential) and for evaluating mibC gene expression as an early warning of massive cyanobacterial occurrence

Zone-Aware Service Platform: A New Concept of Context-Aware Networking and Communications for Smart-Home Sustainability

Recent advances in networking and communications removed the restrictions of time and space in information services. Context-aware service systems can support the predefined services in accordance with user requests regardless of time and space. However, due to their architectural limitations, the recent systems are not so flexible to provide device-independent services by multiple service providers. Recently, researchers have focused on a new service paradigm characterized by high mobility, service continuity, and green characteristics. In line with these efforts, improved context-aware service platforms have been suggested to make the platform possible to manage the contexts to provide the adaptive services for multi-user and locations. However, this platform can only support limited continuity and mobility. In other words, the existing system cannot support seamless service provision among different service providers with respect to the changes of mobility, situation, device, and network. Furthermore, the existing context-aware service platform is significant reliance on always-on infrastructure, which leads to great amounts of energy consumption inevitably. Therefore, we subsequently propose a new concept of context-aware networking and communications, namely a zone-aware service platform. The proposed platform autonomously reconfigures the infrastructure and maintains a service session interacting with the middleware to support cost- and energy-efficient pervasive services for smart-home sustainability

Design and Implementation of IoT-based HVAC and Lighting System for Energy Saving

Building Energy Management System(BEMS) technology is under study as one of the various solutions to environmental problems such as depletion of energy resources, global warming, and climate change. Solving the energy problems of the future BEMS is not the only goal. Occupants must be guaranteed a comfortable environment. HVAC systems and lighting systems are a large part of building energy consumption, which also means that it is an important part of energy conservation. In this paper, we propose IoT-based HVAC and Lighting(I-HVAC&L) system for HVAC system and lighting system management. With I-HVAC&L System, you can save energy efficiency without compromising the convenience of residents’

Design and Implementation of IoT-based HVAC and Lighting System for Energy Saving

Building Energy Management System(BEMS) technology is under study as one of the various solutions to environmental problems such as depletion of energy resources, global warming, and climate change. Solving the energy problems of the future BEMS is not the only goal. Occupants must be guaranteed a comfortable environment. HVAC systems and lighting systems are a large part of building energy consumption, which also means that it is an important part of energy conservation. In this paper, we propose IoT-based HVAC and Lighting(I-HVAC&L) system for HVAC system and lighting system management. With I-HVAC&L System, you can save energy efficiency without compromising the convenience of residents’

Distributed Energy IoT-Based Real-Time Virtual Energy Prosumer Business Model for Distributed Power Resource

Smart energy technologies, services, and business models are being developed to reduce energy consumption and emissions of CO2 and greenhouse gases and to build a sustainable environment. Renewable energy is being actively developed throughout the world, and many intelligent service models related to renewable energy are being proposed. One of the representative service models is the energy prosumer. Through energy trading, the demand for renewable energy and distributed power is efficiently managed, and insufficient energy is covered through energy transaction. Moreover, various incentives can be provided, such as reduced electricity bills. However, despite such a smart service, the energy prosumer model is difficult to expand into a practical business model for application in real life. This is because the production price of renewable energy is higher than that of the actual grid, and it is difficult to accurately set the selling price, restricting the formation of the actual market between sellers and consumers. To solve this problem, this paper proposes a small-scale energy transaction model between a seller and a buyer on a peer-to-peer (P2P) basis. This model employs a virtual prosumer management system that utilizes the existing grid and realizes the power system in real time without using an energy storage system (ESS). Thus, the profits of sellers and consumers of energy transactions are maximized with an improved return on investment (ROI), and an intelligent demand management system can be established

Reinforcement Learning-Based BEMS Architecture for Energy Usage Optimization

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

Direct Evidence on Effect of Oxygen Dissolution on Thermal and Electrical Conductivity of AlN Ceramics Using Al Solid-State NMR Analysis

Aluminum nitride, with its high thermal conductivity and insulating properties, is a promising candidate as a thermal dissipation material in optoelectronics and high-power logic devices. In this work, we have shown that the thermal conductivity and electrical resistivity of AlN ceramics are primarily governed by ionic defects created by oxygen dissolved in AlN grains, which are directly probed using 27Al NMR spectroscopy. We find that a 4-coordinated AlN3O defect (ON) in the AlN lattice is changed to intermediate AlNO3, and further to 6-coordinated AlO6 with decreasing oxygen concentration. As the aluminum vacancy (VAl) defect, which is detrimental to thermal conductivity, is removed, the overall thermal conductivity is improved from 120 to 160 W/mK because of the relatively minor effect of the AlO6 defect on thermal conductivity. With the same total oxygen content, as the AlN3O defect concentration decreases, thermal conductivity increases. The electrical resistivity of our AlN ceramics also increases with the removal of oxygen because the major ionic carrier is VAl. Our results show that to enhance the thermal conductivity and electrical resistivity of AlN ceramics, the dissolved oxygen in AlN grains should be removed first. This understanding of the local structure of Al-related defects enables us to design new thermal dissipation materials