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In the domain of healthcare, both process efficiency and the quality of care can be improved through the use of dedicated pervasive technologies. Among these applications are so-called real-time location systems (RTLS). Such systems are designed to determine and monitor the location of assets and people in real time through the use of wireless sensor networks. Numerous commercially available RTLS are used in hospital settings. The nursing home is a relatively unexplored context for the application of RTLS and offers opportunities and challenges for future applications. The paper aims to discuss these issues.

This paper sets out to provide an overview of general applications and technologies of RTLS. Thereafter, it describes the specific healthcare applications of RTLS, including asset tracking, patient tracking and personnel tracking. These overviews are followed by a forecast of the implementation of RTLS in nursing homes in terms of opportunities and challenges.

By comparing the nursing home to the hospital, the RTLS applications for the nursing home context that are most promising are asset tracking of expensive goods owned by the nursing home in order to facilitate workflow and maximise financial resources, and asset tracking of personal belongings that may get lost due to dementia.

This paper is the first to provide an overview of potential application of RTLS technologies for nursing homes. The paper described a number of potential problem areas that can be addressed by RTLS.

Uncontrolled and unsustainable urban development has a significant impact on the overall quality of the environment. Contemporary spatial management does not take into account the non-economic conditions of ecosystem functions and their biophysical limits, which results in a deterioration of the environment. Furthermore, urban development continues all over the world, which is associated with a projected population increase, particularly in cities. Therefore, there is need to include analyses in the field of environmental carrying capacity (ECC) for more sustainable spatial management and development. The ECC concept is a tool for sustainable development of human settlements. It could be defined as threshold level of anthropopressure, which the environment is able to balance and withstand without serious degradation and irreversible changes. The use of ECC assessment will help ensure the needs of the city’s residents, which are conditioned by the environment. The paper aims to discuss this issue.

This review study presents an overview of the ECC concept and its potential for use in spatial management at local level, especially for cities. The content analysis introduces definitions of spatial management and others main actions of spatial economy as well as the definitions of ECC. The overview of existing ECC models is a part of presented review.

The paper shows the ECC approach from global to local level on Poland as an example country.

The literature review identified that the idea of ECC could be a useful concept and tool for sustainable spatial development and management. This concept allows for verification of the resources and environmental state of given territory unit. Therefore, the assessment of ECC allows to verify if development of given area, for instance country, region or even city, is conducted within the framework of sustainable principles. Despite this, the assessment of ECC is not taken into account when future spatial management is defined. Thus, this circumstance could be a reason for this research area development.

The purpose of this study is to identify the barriers that hinder the implementation of age-friendly initiatives in smart cities.

A systematic review of the literature was conducted using Scopus search engine. Relevant keywords were used to discover 81 publications in academic journals. The titles, abstracts, keywords and full texts of the publications were examined to select 39 publications that were relevant for identifying the barriers that hinder the implementation of age-friendly initiatives in smart cities. The contents of the 39 relevant publications were analysed to ascertain the key barriers. A system thinking approach was adopted to understand the interaction among the barriers.

The study identified five key groups of barriers – namely physical barriers and environmental characteristics, technological barriers, social barriers, financial barriers and political barriers – that smart cities encountered or are likely to encounter in implementing age-friendly initiatives. Moreover, practical examples of good age-friendly implementation practices were highlighted.

A limitation of this study is in the number of publications reviewed. Despite the comprehensive review, the number of publications reviewed may not be exhaustive. This is justified by the inapplicability of considering all possible keywords in one review study.

The systemic perspective of the barriers that hinder the implementation of age-friendly initiatives in smart cities would support policymakers in formulating policy recommendations to improve age-friendliness in cities.

This study underscores the variable and dynamic nature of developing age-friendly smart cities and forms novel basis for gaining insights into the multiple factors that can promote the integration of age-friendly initiatives within smart cities.

This paper highlights the need for studies that explore the experiences of entrepreneurs based in a family business setting who are considering retirement.

This paper is based on a concise review of the literature.

Retirement planning and subsequent succession management is a significant event in a family business and is an issue that requires research that captures and interprets the perspectives of the different stakeholders.

This paper synthesizes existing research on retirement in an entrepreneurial context, with an emphasis on family business and proposes three key areas of research.

Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up dangerous contaminants in our surroundings. Addressing air pollution issues is critical for human health and ecosystems, particularly in developing countries such as Egypt. Excessive levels of pollutants have been linked to a variety of circulatory, respiratory and nervous illnesses. To this end, the purpose of this research paper is to forecast air pollution concentrations in Egypt based on time series analysis.

Deep learning models are leveraged to analyze air quality time series in the 6th of October City, Egypt. In this regard, convolutional neural network (CNN), long short-term memory network and multilayer perceptron neural network models are used to forecast the overall concentrations of sulfur dioxide (SO₂) and particulate matter 10 µm in diameter (PM₁₀). The models are trained and validated by using monthly data available from the Egyptian Environmental Affairs Agency between December 2014 and July 2020. The performance measures such as determination coefficient, root mean square error and mean absolute error are used to evaluate the outcomes of models.

The CNN model exhibits the best performance in terms of forecasting pollutant concentrations 3, 6, 9 and 12 months ahead. Finally, using data from December 2014 to July 2021, the CNN model is used to anticipate the pollutant concentrations 12 months ahead. In July 2022, the overall concentrations of SO₂ and PM₁₀ are expected to reach 10 and 127 µg/m³, respectively. The developed model could aid decision-makers, practitioners and local authorities in planning and implementing various interventions to mitigate their negative influences on the population and environment.

This research introduces the development of an efficient time-series model that can project the future concentrations of particulate and gaseous air pollutants in Egypt. This research study offers the first time application of deep learning models to forecast the air quality in Egypt. This research study examines the performance of machine learning approaches and deep learning techniques to forecast sulfur dioxide and particular matter concentrations using standard performance metrics.

This paper presents the development of personal thermal comfort models for older adults and assesses the models’ performance compared to aggregate approaches. This is necessary as individual thermal preferences can vary widely between older adults, and the use of aggregate thermal comfort models can result in thermal dissatisfaction for a significant number of older occupants. Personalised thermal comfort models hold the promise of a more targeted and accurate approach.

Twenty-eight personal comfort models have been developed, using deep learning and environmental and personal parameters. The data were collected through a nine-month monitoring study of people aged 65 and over in South Australia, who lived independently. Modelling comprised dataset balancing and normalisation, followed by model tuning to test and select the best hyperparameters’ sets. Finally, models were evaluated with an unseen dataset. Accuracy, Cohen’s Kappa Coefficient and Area Under the Receiver Operating Characteristic Curve (AUC) were used to measure models’ performance.

On average, the individualised models present an accuracy of 74%, a Cohen’s Kappa Coefficient of 0.61 and an AUC of 0.83, representing a significant improvement in predictive performance when compared to similar studies and the “Converted” Predicted Mean Vote (PMVc) model.

While current literature on personal comfort models have focussed solely on younger adults and offices, this study explored a methodology for older people and their dwellings. Additionally, it introduced health perception as a predictor of thermal preference – a variable often overseen by architectural sciences and building engineering. The study also provided insights on the use of deep learning for future studies.

Higher education institutions (HEIs) around the world are engaged in internationalisation efforts. Yet internationalisation per se is associated with significant pressures on the environment and environmental resources, which need to be addressed. This study aims to assess the opportunities, benefits and challenges associated with the internationalisation of universities at a global level.

A total of 27 relevant case studies were extracted from the literature to illustrate how HEIs worldwide are ensuring sustainability in their internationalisation efforts.

Through case studies of international HEIs, the study lists the opportunities, benefits and challenges associated with the internationalisation of universities at a global level and some of the measures that may be deployed to reduce the environmental impacts of their international activities.

This study provides a welcome contribution to the literature because it outlines some of the works taking place at universities, where matters related to sustainable development are considered against a background of internationalisation efforts.

Based on profound information lacking in compiled information materials, the risks of losing knowledge related to the values of traditional woodworking processes are increasing. The purpose of this article is to collect and structure diverse marking tool data into a comprehensive, understandable and clear design schematic view, which serves as a basis for the accumulation and preservation of diverse marking objects and shows woodworking marking tool relation in the group and subgroup levels.

A method for marking tools structuring and analysis are described, including breaking down a set of objects into groups of marking objects, and assigning one or more attributes to the parcelled objects by arranging them into hierarchic levels. Research is based on marking tools used by carpenters, joiners and woodcarvers mainly in the Baltic region.

Collected data, object analyses and comparison within-group and subgroup levels are based on written and visual sources, museum and museum funds visits, and participation in the local craftsmen events. The created structure is expandable in group and subgroup levels. The most comprehensive way for object structuring is chosen as a base to reveal a diversity of the objects.

Structure schemes of woodworking marking tools are important in scientific, educative and cultural levels based on their wide range and use. Aggregated information of the woodworking tools serves as a base for existing tool studies and improvement, new tool and wood product creation as well as complements the structure of the upcoming woodworking hand tool database and book.