Connected health is expected to introduce an improvement in providing healthcare and doctor-patient communication while at the same time reducing cost. Connected health would introduce an even more significant gap between healthcare quality for urban areas with physical proximity and better communication to providers and the portion of rural areas with numerous connectivity issues. We identify these challenges using user scenarios and propose LoRa based architecture for addressing these challenges. We focus on the energy management of battery-powered, affordable IoT devices for long-term operation, providing important information about the care receivers’ well-being. Using an external ultra-low-power timer, we extended the battery life in the order of tens of times, compared to relying on low power modes of the microcontroller.

The pandemic declared by the World Health Organization due to the SARS-CoV-2 virus (COVID-19) awakened us to a reality that most of us were previously unaware of—isolation, confinement and the massive use of information and communication technologies, as well as increased knowledge of the difficulties and limitations of their use. This article focuses on the rapid implementation of low-cost technologies, which allow us to answer a fundamental question: how can near real-time monitoring and follow-up of the elderly and their health conditions, as well as their homes, especially for those living in isolated and remote areas, be provided within their care and protect them from risky events? The system proposed here as a proof of concept uses low-cost devices for communication and data processing, supported by Long-Range (LoRa) technology and connection to The Things Network, incorporating various sensors, both personal and in the residence, allowing family members, neighbors and authorized entities, including security forces, to have access to the health condition of system users and the habitability of their homes, as well as their urgent needs, thus evidencing that it is possible, using low-cost systems, to implement sensor networks for monitoring the elderly using the LoRa gateway and other support infrastructures.

The rapid development and widespread use of information and telecommunication technologies do not mitigate, in many situations, information exclusion, nor the physical isolation of people—mainly that of the elderly living in remote locations, whose mobile network coverage is deficient or non-existent, preventing them from accessing health care, be it routine follow-up procedures or emergencies. Addressing this, we raise the question that guides our study: how can we monitor the elderly’s residence and health conditions, detect falls, and track their movement in the vicinity of their homes in a non-intrusive manner? To answer this question, we present a system prototype that uses affordable, low-cost, and low-energy equipment with media and data processing, supported by LoRa (Long Range) and ESP32 microcontrollers, coupling several sensors. As a result, it is possible to monitor sensors that predict and detect falls or other risk events for the user, e.g., fire, with authorized persons and entities, family members, civil protection, and security forces accessing the gathered data, assuring their security. We conclude that the system could decisively improve people’s quality of life, particularly those of the elderly who live in remote places with greater vulnerability.

Background: The evolutionary forces that determine the arrangement of synonymous codons within open reading frames and fine tune mRNA translation efficiency are not yet understood. In order to tackle this question we have carried out a large scale study of codon-triplet contexts in 11 fungal species to unravel associations or relationships between codons present at the ribosome A-, P- and E-sites during each decoding cycle. Results: Our analysis unveiled high bias within the context of codon-triplets, in particular strong preference for triplets of identical codons. We have also identified a surprisingly large number of codon-triplet combinations that vanished from fungal ORFeomes. Candida albicans exacerbated these features, showed an unbalanced tRNA population for decoding its pool of codons and used near-cognate decoding for a large set of codons, suggesting that unique evolutionary forces shaped the evolution of its ORFeome. Conclusion: We have developed bioinformatics tools for large-scale analysis of codon-triplet contexts. These algorithms identified codon-triplets context biases, allowed for large scale comparative codon-triplet analysis, and identified rules governing codon-triplet context. They could also detect alterations to the standard genetic code.