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This experimental study explores the possibility of using an existing Trombe wall as a space for year-round cultivation to increase building resource efficiency. To do so with the least cost to the building, a small 0.75 m2/5.45 m3 Trombe wall cavity space was retrofitted with shelves placed behind the glazing, additional ventilation, and a watering network to be able to grow 400 hydroponic Kratky basil plants in individual glass jars. Historical thermal observations made at the site over a year-long timespan were contrasted with the experimental readings. When fully equipped, the Trombe wall’s thermal mass increased by 51%, which had a balancing effect on the system, lowering the average daily thermal oscillations from 35.41 °C to 17.88 °C. The living plants and water have also had significant cooling (26.99 °C to 22.91 °C) and humidifying (39.88 to 47.74%) effects. The system’s energy efficiency, however, decreased from 26 to 18% (absorption) and from 85 to 46 (dissipation), lowering its energy contribution to the building by about 30%. The average plant’s lifespan within the Trombe wall was 46 days, with 15% of the specimens surpassing the 100-day mark. Over the course of a year, 20.55 kg of edible greens were grown in the Trombe wall. The experiment has shown that it is possible to grow the plants inside the Trombe wall cavity during the warmer half of the year, revealing many possible ways to improve the space’s comfort, yields, and energy efficiency.

Comfort temperature and sleep quality involving 20 participants were determined in two cases: Case A (arbitrary, controlled air-conditioner setting) and Case B (adjustment of 3 °C higher than the setting of Case A with cool bed linen). Data of indoor thermal comfort and electricity consumption were collected every night throughout the measurement period. Questionnaires on thermal comfort and sleep quality were distributed twice a night for a duration of three nights for each case; the first night was for respondents’ adaptation and the following two nights were for measurement. The sleep quality of the respondents was objectively measured using a commercially available activity tracker. Results found that most respondents were thermally comfortable in both cases, with 39% lower energy consumption reported for Case B compared to Case A. The thermal conditions of Case B were found to be more tolerable than those of Case A. Most respondents reported to have a calm and satisfied sleep for both cases. Comfort temperature and Sleep Efficiency Index (SEI) were found to be maintained in both cases.

Aquaponics systems and technologies are growing primary industries in many countries, with high environmental and socio-economic advantages. Aquaponics is a closed-loop system that produces aquatic animals and plants in a new way using recirculated water and nutrients. With a growing world population expected to reach 9.7 billion by 2050, food production sustainability is a primary issue in today’s world agenda, and aquaponics and aquaculture systems can be potential contributors to the challenge. Observing the climate changes and global warming’s impact on the ecosystem, decreasing aqua animal stocks, and responding to increasing demand are turning points in the sustainability era. In the past 15 years, fish production has doubled, thus denoting that aquaponics transforms into commercial scales with a revolutionized production, high efficiency, and fewer resources’ utilization, thus requiring proper operation and management standards and practices. Therefore, this study aims to shape a new framework for sustainable aquaponics modeling and utilization as the all-in-one solution platform covering technical, managerial, socio-economic, institutional, and environmental measures within the suitability requirements. The proposed model in this study offers a systematic approach to the design and implementation of sustainability-efficient aquaponics and aquaculture systems. Through an exhaustive coverage of the topic, this research effort can be counted as a practical reference for researchers, scholars, experts, practitioners, and students in the context of aquaponics and aquaculture studies.

As environmental and energy issues continue to emerge as global concerns, Leadership in Energy and Environmental Design (LEED) certification is becoming highly valued. However, since additional costs for LEED certification cannot be estimated before proceeding with certification projects, financial losses are often incurred. Additional construction costs are the most significant issue faced by enterprises aiming for LEED certification. Rough estimates of the range of additional construction costs are available, but it is difficult to identify factors that increase or decrease the price of a building. Thus, there is a need for a program that provides average data for LEED certification costs and suggests the easiest way to attain credits for a building. Considering that LEED certification is a rating system, this study develops an optimization algorithm that aims to derive the minimum score for a desired LEED level at minimal cost. Credits are studied and classified by their difficulty and the required cost, allowing for an algorithm that can suggest a customized approach to acquire the minimal required score. The practical, data-driven program developed herein helps shorten the consulting process and increases the accessibility of LEED certification.

Cities are perhaps one of the most challenging and yet enabling arenas for sustainable development goals. The Sustainable Development Goals (SDGs) emphasize the need to monitor each goal through objective targets and indicators based on common denominators in the ability of countries to collect and maintain relevant standardized data. While this approach is aimed at harmonizing the SDGs at the national level, it presents unique challenges and opportunities for the development of innovative urban-level metrics through big data innovations. In this article, we make the case for advancing more innovative targets and indicators relevant to the SDGs through the emergence of urban big data. We believe that urban policy-makers are faced with unique opportunities to develop, experiment, and advance big data practices relevant to sustainable development. This can be achieved by situating the application of big data innovations through developing mayoral institutions for the governance of urban big data, advancing the culture and common skill sets for applying urban big data, and investing in specialized research and education programs.

Identification and monitoring of diverse resources or wastes on the ground is important for integrated resource management. The unmanned aerial vehicle (UAV), with its high resolution and facility, is the optimal tool for monitoring ground objects accurately and efficiently. However, previous studies have focused on applying classification methodology on land use and agronomy, and few studies have compared different classification methods using UAV imagery. It is necessary to fully utilize the high resolution of UAV by applying the classification methodology to ground object identification. This study compared three classification methods: A. NDVI threshold, B. RGB image-based machine learning, and C. object-based image analysis (OBIA). Method A was the least time-consuming and could identify vegetation and soil with high accuracy (user’s accuracy > 0.80), but had poor performance at classifying dead vegetation, plastic, and metal (user’s accuracy < 0.50). Both Methods B and C were time- and labor-consuming, but had very high accuracy in separating vegetation, soil, plastic, and metal (user’s accuracy ≥ 0.70 for all classes). Method B showed a good performance in identifying objects with bright colors, whereas Method C showed a high ability in separating objects with similar visual appearances. Scientifically, this study has verified the possibility of using the existing classification methods on identifying small ground objects with a size of less than 1 m, and has discussed the reasons for the different accuracy of the three methods. Practically, these results help users from different fields to choose an appropriate method that suits their target, so that different wastes or multiple resources can be monitored at the same time by combining different methods, which contributes to an improved integrated resource management system.

Cities involve units of time and space, being part of historical, social, economic, cultural, and tourist imaginary constructions. The goal is to understand how the territorial brand, based on regional development theories, is being used in the metaverse city of Seoul, South Korea. The method used was a case study associated with bibliographic and documentary research, using a protocol with four analytical categories. The main results referred to a metaverse territorial-regional brand, bringing discussions about a new geographical-virtual-immersive metaverse scale. It also addressed the use of recognition and competitiveness strategies between interactive-immersive territories. The conclusion confirms that Seoul’s metaverse territorial-regional brand is strategically divided into three situations: (1) For city marketing purposes, positioning it as the first metaverse global city; (2) in city branding to strengthen the reputation and identity of the territory; and (3) to drive the transformation of physical territory with urban revitalization projects from the metaverse environment. Moreover, it serves Metaverse Seoul as an interactive and immersive field laboratory in virtual reality.