Background and aims Population ageing is a typical phenomenon of developed countries with a great influence in their economy and society, with an increment on age-related expenditures. Disruptive solutions are needed to deploy new cost-effective and sustainable solutions for aging well and independent living of our seniors. In this sense, new technological paradigms as IoT technologies and smart cities have the potential to become main drivers for innovation uptake. The purpose of this study is to describe a longitudinal cohort study in smart cities for assessing early frailty symptoms deploying an unobtrusive IoT-based system in the Madrid city. Methods A system was deployed in the Madrid city with the participation of 45 elderly users for an average of 71 weeks. Metrics were assessed by the available sensors in combination with the open data infrastructure of Madrid. Metrics include activity of the user, weekly visits pattern and transport daily usage pattern. System engagement was also monitored. Participants are assessed bimonthly with health and functional questionnaires. Results 45 older adults with a mean age of 79.1 years. Participants activity patterns monitor detected changes during potentially risky situations that usually were not reported by traditional assessment tools. Analysis of data collected enabled to identify absence of frailty (robust or post-robust status) Discussion and conclusions The results demonstrate the feasibility of engaging older adults with an IoT-based system and the successful collection of their activity metrics. Variation in the activity patterns may be a first sign of functional decline and enables to identify potential areas of early intervention.

Ambient assisted living (AAL) is a complex field, where different technologies are integrated to offer solutions for the benefit of different stakeholders. Several evaluation techniques are commonly applied that tackle specific aspects of AAL; however, holistic evaluation approaches are lacking when addressing the needs of both developers and end-users. Living labs have been often used as real-life test and experimentation environments for co-designing AAL technologies and validating them with relevant stakeholders. During the last five years, we have been evaluating AAL systems and services in the framework of various research projects. This paper presents the lessons learned in this experience and proposes a set of harmonized guidelines to conduct evaluations in living labs.

This paper discusses the potential benefits of using augmented reality (AR) technology to enhance human–robot collaborative industrial processes. The authors describe a real-world use case at Siemens premises in which an AR-based authoring tool is used to reduce cognitive load, assist human workers in training robots, and support calibration and inspection tasks during assembly tasks. The study highlights the potential of AR as a solution for optimizing human–robot collaboration and improving productivity. The article describes the methodology used to deploy and evaluate the ARContent tool, which demonstrated improved usability, reduced task load, and increased efficiency in the assembly process. However, the study is limited by the restricted availability of workers and their knowledge of assembly tasks with robots. The authors suggest that future work should focus on testing the ARContent tool with a larger user pool and improving the authoring tool based on the shortcomings identified during the study. Overall, this work shows the potential for AR technology to revolutionize industrial processes and improve collaboration between humans and robots.

Hospitals need to optimize patient care, as, among other factors, life expectancy has increased due to improvements in sanitation, nutrition, and medicines. Hospitalization-at-home (HaH) could increase admission efficiency, moderate costs, and reduce the demand for beds. This study aimed to provide data on the feasibility, acceptability, and effectiveness of the integration of IoT-based technology to support the remote monitoring and follow-up of patients admitted to HaH units, as well as the acceptability of IoT-based solutions in healthcare processes. The need for a reduction in the number of admission days, the percentage of admissions after discharge, and the actions of the emergency services during admission were the most relevant findings of this study. Furthermore, in terms of patient safety and trust perception, 98% of patients preferred this type of digitally-supported hospitalization model and up to 95% were very satisfied. On the professional side, the results showed a reduction in work overload and an increase in trust when the system was adopted.

Recently, the European Commission announced Industry 5.0 as a strategic initiative toward a value-driven industrial transformation. This new paradigm coexists with previous Industry 4.0 revolution that has guided the efforts towards technology driven industrial digitalisation in the past ten years. As part of this Industry 4.0 strategies, numerous KPI-driven evaluation methods were proposed to cover the multiple pillars of smart industry assessment. However, they do not incorporate human workers and actors in a systematic way as drivers for digitalisation processes, as the new Industry 5.0 paradigm argues. This paper addresses this gap by proposing an evaluation methodology that incorporates multiple human actors in the digitalisation process. The final objective of this methodology is to evaluate the direct and indirect benefits of the technology-driven transformation process to achieve the goals of human workers and other human stakeholders. To this end, our methodology provides the basis for proposing assessment tools and instruments for technological and infrastructure integration, process optimisation, new functionalities and human factors benefits, and four core indicators that have been applied to a real case comparing the digitalisation processes of three different companies.

Digital transformation has a great effect on industries but also in the perception of their products with high consequences on society as a whole, as driver for innovation. However, there are still many barriers to the adoption of digital technologies, especially in small and medium-sized enterprises (SMEs). In the present study we propose a new software component that facilitates the adoption of industrial reference architectures (RAs) based on the semantic interoperability concept. Among these RAs, FIWARE has become a key enabler for flexible and resource effective digitalisation of shop floor processes. The proposed software component aims to enable full interoperability between these more widely used technologies and industrial standards and protocols such as OPC UA. As a result, a flexible, open, and adaptable implementation assists the automatic translation of messages from different standards enabling semantic interoperability of shop floor processes. The component aims to enable industrial SMEs to bring current barriers to digitalisation towards a more human-centred, resilient, and sustainable industry and society.