Abstract
The demographic growth that we have witnessed in recent years, which is expected to increase in the years to come, raises emerging challenges worldwide regarding urban mobility, both in transport and pedestrian movement. The sustainable development of cities is also intrinsically linked to urban planning and mobility strategies. The tasks of navigation and orientation in cities are something that we resort to today with great frequency, especially in unknown cities and places. Current navigation solutions refer to the precision aspect as a big challenge, especially between buildings in city centers. In this paper, we focus on the segment of visually impaired people and how they can obtain information about where they are when, for some reason, they have lost their orientation. Of course, the challenges are different and much more challenging in this situation and with this population segment. GPS, a technique widely used for navigation in outdoor environments, does not have the precision we need or the most beneficial type of content because the information that a visually impaired person needs when lost is not the name of the street or the coordinates but a reference point. Therefore, this paper includes the proposal of a conceptual architecture for outdoor positioning of visually impaired people using the Landmark Positioning approach.

Abstract
Industry 4.0 is a trendy concept that everyone is talking about. However there are several concepts and technologies attached to Industry 4.0. The concept is considered as the most recent industrial revolution and takes us to the domains of automation, digitalization and information, among others. The concept is trendy, but sometimes firms and employees are not able to follow new trends. This paper summarizes a research on the concepts of industry 4.0 and the 9 technologies commonly associated to Industry 4.0 umbrella. Most of the literature recognizes it as something that can bring several benefits to firms. However, it is also pointed out, that the adoption of these technologies relies in several factors. In this paper the focus is the human factors. A group of 260 persons participated in a questionnaire where were asked about their perceptions on industry 4.0 and its technologies. The main objective was to find different responses to Industry 4.0 technologies, according to age, education level, gender or field of studies. In general, all the individuals present a similar approach. Main differences were found on Big Data, Augmented Reality and Simulation technologies. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The urban development model practiced in the past has proved to be unsustainable. Due to this fact, cities such as Rio de Janeiro, with high population density, mainly regarding precarious settlements, need immediate practical actions to become more sustainable. The insufficiency of planning and investments contributed to the city occupying the 8th position of the most vulnerable cities in the world, triggering the primary motivation of the research study. Therefore, the leading research focused on exploring how sustainable habitats could contribute to Rio de Janeiro becoming more sustainable. A document analysis was carried out, and semi-structured interviews were designed, making it possible to identify projects to create sustainable habitats for Rio de Janeiro that can serve as benchmarks and listen to the engineers and architects regarding the importance of the sustainable building. Thus, consonant to structural changes in thinking, producing, consuming, and living, it was also possible to identify the main contributions of sustainable habitats to the city, classifying them within the pillars of sustainability.

Abstract
The current world context emphasizes the need and urgency of the sustainable cities theme. The construction industry is considered an essential role in satisfying the needs of society and contributing to the economy. However, it is heavily criticized for being a significant contributor to environmental degradation. Moreover, the building sector accounts for considerable energy and water consumption, waste formation, and extensive greenhouse gas emissions. Consequently, sustainable urban development becomes increasingly challenging due to the building sector's high potential for reducing its environmental impacts. Therefore, the research methodology used within this article was the literature review and document analysis to present to the construction industry stakeholders the contribution of the Building's Sustainable Assessment Systems towards the Sustainable Development Goals and essential information that arouses interest in applying them. It was concluded that the Building's Sustainable Assessment Systems contribute to creating sustainable cities, contributing to some of the Sustainable Development Goals.

Abstract
The present paper aims to identify the main trends and gaps in the digitalization of manufacturing SMEs. The most significant literature on this emergent theme was gathered through a criterion search, resulting in discovering 4060 related documents. To narrow this considerable number of documents, a bibliometric analysis was performed. A database was exported from Clarivates' Web of Science for clusters analysis in VOSviewer's software. Afterward, it was possible to identify the top authors and documents. Four trends were identified: one Asian, headed by China; another Anglo-Saxon, led by the USA; and two European trends, run by Italy and Germany. Furthermore, were identified two research gaps: (1) The development of pro-environmental technology and (2) digital readiness models for manufacturing SMEs.

Abstract
This project was developed to improve the cost estimation process of new products within the Product Development Department of a furniture manufacturer. This work involved developing a methodology using Machine Learning (ML) models trained on products' existing data to predict the cost of new innovative ones based on similarities and given data. The ML models used were Linear Regression (LR), Light Gradient-Boosting Machine (LGBM), Random Forest (RF), and Support Vector Machine (SVM). The proposed methodology considers the estimation of the total cost of producing a product, which encompasses both material and operational costs. Throughout this project, several analyses were developed to identify and evaluate different independent variables that could explain the behaviour of these two cost components. The suitability of the different variables was studied by applying several ML models, and a set of functions that return an estimate of the cost as a function of these predictor variables was obtained. The proposed approach, which incorporates ML models into more complex variables to predict, resulted in a 19.29% reduction in estimation error.