Traditionally, the standards of spatial modeling are oriented to represent the quantitative information of space. However, in recent years an increasingly common challenge is appearing: flexibly and appropriately integrating quantitative information that goes beyond the purely geometric. This problem has been aggravated due to the success of new paradigms such as the Internet of Things. This adds an additional challenge to the representation of this information due to the need to represent characteristic information of the space from different points of view in a model, such as WiFi coverage, dangerous surroundings, etc. While this problem has already been addressed in indoor spaces with the IndoorGML standard, it remains to be solved in outdoor and indoor–outdoor spaces. We propose to take the advantages proposed in IndoorGML, such as cellular space or multi-layered space model representation, to outdoor spaces in order to create indoor–outdoor models that enable the integration of heterogeneous information that represents different aspects of space. We also propose an approach that gives more flexibility in spatial representation through the integration of standards such as OpenLocationCode for the division of space. Further, we suggest a procedure to enrich the resulting model through the information available in OpenStreetMap.

While the importance of physical activity in older adults is beyond doubt, there are significant barriers limiting the access of older adults to physical exercise. Existing technologies to support physical activity in older adults show that, despite their positive impacts on health and well-being, there is in general a lack of engagement due to the existing reluctance to the use of technology. Usefulness and usability are two major factors for user acceptance along with others, such as cost, privacy, equipment and maintenance requirements, support, etc. Nevertheless, the extent to which each factor impacts user acceptance remains unclear. Furthermore, other stakeholders, besides the end users, should be considered in the decision-making process to develop such technologies, including caregivers, therapists and technology providers. In this paper, and in the context of physical rehabilitation and exercise at home, four different alternatives with incremental characteristics have been defined and considered: a software-based platform for physical rehabilitation and exercise (Alternative 1), the same software platform with a conventional RGB camera and no exercise supervision (Alternative 2), the same software platform with a convention RGB camera and exercise supervision (Alternative 3) and finally, the same software platform with a depth camera and exercise supervision (Alternative 4). A multiple attribute decision-making methodology, based on the ordinal priority approach (OPA) method, is then applied using a group of experts, including end users, therapists and developers to rank the best alternative. The attributes considered in this method have been usefulness, cost, ease of use, ease of technical development, ease of maintenance and privacy, concluding that Alternative 3 has been ranked as the most appropriate.

The main objective of this work is to determine whether social networks can be used to improve self-management skills in people with Intellectual or Developmental Disability (IDD) given the high rate of acceptance of such tools among them. The proposed methodology applies an employment-based intervention to evaluate whether social network services help improve self-management skills. A fit-for-purpose social networking service is built, and different evaluation mechanisms are applied to determine the degree to which users with IDD could use the tool without assistance. The working hypothesis is that in order to ensure the usability of the implemented tool, users (with and without IDD) should be involved throughout the whole software development cycle, following a co-design methodological approach. Results demonstrate that this methodological approach leads to high satisfaction and motivation rates. In terms of effectiveness and efficiency, results demonstrate that the tool is useful and usable for people with IDD. It can therefore be concluded that social network services built having users with IDD at its center will help improve their self-management skills. The main implication of this research is that when using social network services as a tool to support interventions, special attention should be paid to previously evaluating the usability and motivation rate as a measure of how autonomously the person with IDD can use the tool. Nevertheless, further research is needed to determine the impact that such tools can have on other types of intervention.

The occurrence of emergency situations in high-rise buildings, daily hosting hundreds of people, may force the massive evacuation of their occupants with the ultimate goal of preventing the loss of lives. In this paper, we propose an adaptive algorithm for dynamically computing safe evacuation routes, while the load of people is balanced between the accesses of each floor of the building, thus avoiding the accumulation of people in hotspots. The combination of this algorithm with sensors to detect the events of interest and a navigation system to guide the evacuees turns this solution into a specially suited approach for evacuation in high-rise buildings. Simulation results demonstrate that the yield evacuation routes drive all people outdoor with a similar average path length for the different risk scenarios addressed.

COVID-19 has become a global pandemic during 2020 due to its high contagiousness and the high mobility of the world's population today. In just one year, this virus has caused millions of infections and deaths worldwide. These numbers will continue to grow until the population becomes immune to the virus thanks to an effective vaccine. Until this is possible, the only viable strategy is to try to stop its expansion through preventive measures such as limiting mobility, the use of masks, etc. In order to support these measures, this article presents a service to provide safe navigation solutions to reduce the likelihood of infection by avoiding potential conflict areas in the city. To identify these hotspots, a strategy that combines a rule-based system and a common-sense knowledge base is proposed. Through this strategy, an occupation model and a danger model are inferred. This requires the prior capture of knowledge about the general functioning of the city, its inhabitants and the virus. The proposed service makes decisions from these two models. Finally, a validation process has been carried out through surveys to evaluate the proposed solution. Obtained results demonstrate the potential of the proposed solution as a tool to identify safe routes that allow citizens to move around the city with low exposure to COVID-19.