An Assessment Model for Sustainable Cities Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

Ependi, Usman; Rochim, Adian Fatchur; Wibowo, Adi

doi:10.3390/smartcities6060136

Cited by 5 publications

(2 citation statements)

References 80 publications

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“…The growth in population has led to an increase in the demand for energy in the construction and welfare sectors, and it is certain that this trend is going upwards (Babayomi et al, 2023;Liao et al, 2023). This surge reflects an interconnected web where societal advancements, population dynamics, and energy requirements converge, painting a comprehensive picture of the intricate relationship between human wellbeing and the need for sustainable energy solutions (Ependi et al, 2023). Given these trends, understanding and addressing the factors driving escalating energy demand, especially in the context of building cooling and heating, is imperative for devising effective strategies to promote energy efficiency and environmental sustainability (Hafez et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Novel approach to energy consumption estimation in smart homes: application of data mining and optimization techniques

Lin,

Peng,

Liu

et al. 2024

Front. Energy Res.

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Buildings account for a significant portion of total energy consumption, and the introduction of intelligent buildings represents a significant step forward in efficiently managing energy utilization. The proposed solutions represent a significant step forward in the development of intelligent residential environments. Beginning the process of achieving improved building intelligence necessitates a thorough evaluation and prediction of the necessary heating and cooling energy requirements, taking into account all relevant influencing factors. This study describes methodologies for using data mining models to predict the heating and cooling energy requirements of intelligent buildings during the construction phase. Data mining techniques, specifically Support Vector Machines (SVM) and Random Forest, are used, demonstrating their superior efficiency over alternative methods. Metaheuristic algorithms, particularly the Owl Search Algorithm (OSA), are described as effective tools for optimizing results across a wide range of problem resolutions. OSA is described and proposed alongside novel data mining methods, demonstrating that this combination of algorithms improves the performance of Random Forest and SVM-based models by 11% and 24%, respectively. The proposed models can generate predictions with a small number of parameters, eliminating the need for complex software and tools. This user-friendly approach makes the prediction process more accessible to a wider audience. While specialized equipment and professional-grade tools will be used, the proposed models are accessible to a wide range of individuals interested in participating in the prediction process.

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Section: Introductionmentioning

confidence: 99%

Novel approach to energy consumption estimation in smart homes: application of data mining and optimization techniques

Lin,

Peng,

Liu

et al. 2024

Front. Energy Res.

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“…The analyses described in the following sections are focused on Bologna, Italy, an emerging touristic destination whose real estate market is traditionally under pressure due to different incumbent categories (e.g., university students and long-term renters) [43][44][45][46]. This paper also aims to demonstrate the primary role of open data and, in general, the combination of different data sources [47] in today's need for smartness [48][49][50], since analyses are based on open datasets from official statistics, natively open geographic databases (i.e., OpenStreetMap; [51]) and insideairbnb.com portal [52], a web scraper able to collect and share information about Airbnb lodgings.…”

Section: Introductionmentioning

confidence: 99%

Unveiling the Socio-Economic Fragility of a Major Urban Touristic Destination through Open Data and Airbnb Data: The Case Study of Bologna, Italy

Nalin,

Cameli,

Pazzini

et al. 2023

Smart Cities

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In the last decades, tourism in urban areas has been constantly increasing. The need for short-term accommodations has been coupled with the emergence of internet-based services, which makes it easier to match demand (i.e., tourists) and supply (i.e., housing). As a new mass tourist destination, Bologna, Italy, has been experiencing tensions between tourists and long-, mid-, or short-term renters. The possibility of easy profits for lessees has led to an increase in such housing, which can be rented out either for touristic reasons or not. This paper aims to unveil the contribution of short-term rental accommodations in distorting the real estate market and conditioning social and economic inequalities. To do this, multiple linear regression analyses (MLR) were performed between accommodation density, real estate market information, and indicators about social, economic, and demographic vulnerability and fragility. Analyses were based on official open data and datasets from a major web-based hospitality exchange platform, i.e., Airbnb, able to provide information on registered accommodations, e.g., type, characteristics (e.g., number of bedrooms and average rating), and location. Outputs of the analyses reveal the role of Airbnb in both rental market and social, economic, and demographic vulnerability and fragility and, hence, can be a solid tool for public policies, both housing- and tourism-related.

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Implementation of Sustainable City Concept in New Capital City Development Planning

Fatonah,

Rahmawati

2024

SHS Web Conf.

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New capital City development will be carried out in the Eastern Kalimantan region with the concept of a sustainable city. The research aims to find out whether the planning process carried out in new capital city development is in line with the concept of the sustainable city according to the Research Triangle Institute (1996) with indicators of ecology, economy, Society equity, engagement, and energy. The research uses qualitative methods through a descriptive approach using secondary data that comes from online news sites and previous research. Based on the results of this research, implementation of the concept of a sustainable city in New capital city development planning shows that (a) engagement aspects have shown the involvement of stakeholders of the community and investors; (b) environmental aspects have applied efforts of conservation of biodiversity and waste management in planning this development; (c) in energy aspects has taken into account the planning of intelligent building concepts and environmentally friendly transportation; (d) the society aspects is marked by the availability of facilities and services Education as well as Health; (e) in economic aspects take into consideration the development of the agriculture and plantation industry and development of ecosystems.

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An Assessment Model for Sustainable Cities Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

Cited by 5 publications

References 80 publications

Novel approach to energy consumption estimation in smart homes: application of data mining and optimization techniques

Novel approach to energy consumption estimation in smart homes: application of data mining and optimization techniques

Unveiling the Socio-Economic Fragility of a Major Urban Touristic Destination through Open Data and Airbnb Data: The Case Study of Bologna, Italy

Implementation of Sustainable City Concept in New Capital City Development Planning

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