The new era of mobile health ushered in by the wide adoption of ubiquitous computing and mobile communications has brought opportunities for governments and companies to rethink their concept of healthcare. Simultaneously, the worldwide urbanization process represents a formidable challenge and attracts attention toward cities that are expected to gather higher populations and provide citizens with services in an efficient and human manner. These two trends have led to the appearance of mobile health and smart cities. In this article we introduce the new concept of smart health, which is the context-aware complement of mobile health within smart cities. We provide an overview of the main fields of knowledge that are involved in the process of building this new concept. Additionally, we discuss the main challenges and opportunities that s-Health would imply and provide a common ground for further research.

Background: COVID-19 is one of the biggest pandemics in human history, along with other disease pandemics, such as the H1N1 influenza A, bubonic plague, and smallpox pandemics. This study is a small contribution that tries to find contrasted formulas to alleviate global suffering and guarantee a more manageable future. Objective: In this study, a statistical approach was proposed to study the correlation between the incidence of COVID-19 in Spain and search data provided by Google Trends. Methods: We assessed the linear correlation between Google Trends search data and the data provided by the National Center of Epidemiology in Spain—which is dependent on the Instituto de Salud Carlos III—regarding the number of COVID-19 cases reported with a certain time lag. These data enabled the identification of anticipatory patterns. Results: In response to the ongoing outbreak, our results demonstrate that by using our correlation test, the evolution of the COVID-19 pandemic can be predicted in Spain up to 11 days in advance. Conclusions: During the epidemic, Google Trends offers the possibility to preempt health care decisions in real time by tracking people's concerns through their search patterns. This can be of great help given the critical, if not dramatic need for complementary monitoring approaches that work on a population level and inform public health decisions in real time. This study of Google search patterns, which was motivated by the fears of individuals in the face of a pandemic, can be useful in anticipating the development of the pandemic.

The upcoming design and implementation of the new generation of 5G cellular systems, jointly with the multiple wireless communication systems that nowadays coexist within vehicular environments, leads to Heterogeneous Network challenging urban scenarios. In this framework, user’s Radiofrequency Electromagnetic Fields (RF-EMF) radiation exposure assessment is pivotal, to verify compliance with current legislation thresholds. In this work, an in-depth study of the E-field characterization of the personal mobile communications within urban public trams is presented, considering different cellular technologies (from 2G to 5G). Specifically, frequency bands in the range of 5G NR frequency range 1 (FR1) and millimeter wave (mm-wave) bands within frequency range 2 (FR2) have been analyzed for 5G scenarios, considering their dispersive material properties. A simulation approach is presented to assess user mobile phone base station up-link radiation exposure, considering all the significant features of urban transportation trams in terms of structure morphology and topology or the materials employed. In addition, different user densities have been considered at different frequency bands, from 2G to 5G (FR1 and FR2), by means of an in-house developed deterministic 3D Ray-Launching (3D-RL) technique in order to provide clear insight spatial E-field distribution, including the impact in the use of directive antennas and beamforming techniques, within realistic operation conditions. Discussion in relation with current exposure limits have been presented, showing that for all cases, E-Field results are far below the maximum reference levels established by the ICNIRP guidelines. By means of a complete E-field campaign of measurements, performed with both, a personal exposimeter (PEM) and a spectrum analyzer within a real tram wagon car, the proposed methodology has been validated showing good agreement with the experimental measurements. In consequence, a simulation-based analysis methodology for dosimetry estimation is provided, aiding in the assessment of current and future cellular deployments in complex heterogeneous vehicular environments.

In the last decade the number of wireless devices operating at the frequency band of 2.4 GHz has increased in several settings, such as healthcare, occupational, and household. In this work, the emissions from Wi-Fi transceivers applicable to context aware scenarios are analyzed in terms of potential interference and assessment on exposure guideline compliance. Near field measurement results as well as deterministic simulation results on realistic indoor environments are presented, providing insight on the interaction between the Wi-Fi transceiver and implantable/body area network devices as well as other transceivers operating within an indoor environment, exhibiting topological and morphological complexity. By following approaches (near field estimation/deterministic estimation), colocated body situations as well as large indoor emissions can be determined. The results show in general compliance with exposure levels and the impact of overall network deployment, which can be optimized in order to reduce overall interference levels while maximizing system performance.

The electromagnetic field leakage levels of nonionizing radiation from a microwave oven have been estimated within a complex indoor scenario. By employing a hybrid simulation technique, based on coupling full wave simulation with an in-house developed deterministic 3D ray launching code, estimations of the observed electric field values can be obtained for the complete indoor scenario. The microwave oven can be modeled as a time- and frequency-dependent radiating source, in which leakage, basically from the microwave oven door, is propagated along the complete indoor scenario interacting with all of the elements present in it. This method can be of aid in order to assess the impact of such devices on expected exposure levels, allowing adequate minimization strategies such as optimal location to be applied.