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As society moves towards a preventative approach to healthcare, there is growing interest in scientific research involving technology that can monitor and prevent adverse health outcomes. The primary objective of this paper is to develop an Internet of Things (IoT) wearable system based on Fried’s phenotype that is capable of detecting frailty. To determine user requirements, the system’s architecture was designed based on the findings of a questionnaire administered to individuals confirmed to be frail. A functional prototype was successfully developed and tested under real-world conditions. This paper introduces the methodology that was used to analyze the data collected from the prototype. It proposes an interdisciplinary approach to interpret wearable sensor data, providing a comprehensive overview through both visual representations and computational analyses facilitated by machine learning models. The findings of these analyses offer insights into the ways in which different types of activities can be classified and quantified as part of an overall physical activity level, which is recognized as an important indicator of frailty. The results provide the foundations for a new generation of affordable and non-intrusive systems able to detect and assess early signs of frailty.

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.

The general condition of urban watercourses is inextricably linked to ecological balance and public health (physical and mental well-being). Given the vulnerability of these systems to climate change and human pollution, this work aims to demonstrate the effective use of environmental indicators to: a) rapidly assess soil and water conditions near urban streams and b) highlight the importance of geoinformatics and earth observation supported by ground-based techniques. There is a great need for new technology and methods for spatial and temporal monitoring and further quantification of environmental quality in urban streams and the land surrounding them to sensitize policymakers and the public to the environmental degradation of these exceptional habitats and to further protect people's mental health.