Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 °C, affected negatively, the confirmed cases.

The objective of this review paper is to survey the state of the art on nature-based solutions (NBS) in the built environment, which can contribute to a circular economy (CE) and counter the negative impacts of urbanization through the provision of ecosystem services. NBS are discussed here at three different levels: (i) green building materials, including biocomposites with plant-based aggregates; (ii) green building systems, employed for the greening of buildings by incorporating vegetation in their envelope; and (iii) green building sites, emphasizing the value of vegetated open spaces and water-sensitive urban design. After introducing the central concepts of NBS and CE as they are manifested in the built environment, we examine the impacts of urban development and the historical use of materials, systems and sites which can offer solutions to these problems. In the central section of the paper we present a series of case studies illustrating the development and implementation of such solutions in recent years. Finally, in a brief critical analysis we look at the ecosystem services and disservices provided by NBS in the built environment, and examine the policy instruments which can be leveraged to promote them in the most effective manner – facilitating the future transition to fully circular cities.

The latest progress in information and communication technology (ICT) and the Internet of Things (IoT) have opened up new opportunities for real-time monitoring and controlling of cities’ structures, infrastructures, and services. In this context, smart water management technology provides the data and tools to help users more effectively manage water usage. Data collected with smart water devices are being integrated with building management systems to show how much water is used by occupants as well as to identify the consumption areas to use water more efficiently. By this approach, smart buildings represent an innovative solution that enhances a city’s sustainability and contributes to overcoming environmental challenges due to increasing population and climate change. One of the main challenges is resource-saving and recovery. Water is an all-important need of all living beings, and the concerns of its scarcity impose a transition to innovative and sustainable management starting from the building scale. Thus, this manuscript aims to provide an updated and valuable overview for researchers, consumers, and stakeholders regarding implementing smart and sustainable technologies for water resource management, primarily for building-scale uses.