# Monitoring the Health and Residence Conditions of Elderly People, Using LoRa and The Things Network
###### Abstract  
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. IoT; LoRaWAN; pervasive systems; sensor data analytics; The Things Network; remote monitoring +
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and individuals, particularly the elderly, are prevented from taking advantage of this technological development, especially those living in small towns or isolated dwellings without families or continued institutional support. Nevertheless, recent studies have shown that the world population that currently suffers or is likely to develop mental pathologies is growing exponentially. Therefore, it is urgent to associate and put the various communication and information technologies at the service of people, minimizing the negative impact that these pathologies have on their quality of life [4; 5]. Based on this reality, the question arising as the starting point of the present work is the following: how can we monitor the health status of the elderly, detecting falls and monitoring their movement in the vicinity of their homes in a non-intrusive way? Using concepts already framed by other monitoring and follow-up environments based on miniaturized sensors and telecommunications equipment, we present a system model solution involving several actors, families, the security forces, and social solidarity institutions. This monitoring and protection system model for the elderly is named IS4 HMET--Information System for Home Monitoring and Elderly Tracking. It is targeted to populations without physical and mental disabilities residing in isolated or low-density communities, providing them with autonomy inside and outside their homes. Additionally, it should be noted that the inhabitants of rural areas still maintain their food gardens near the house, in areas without mobile communications signal coverage, or with a weak signal, as shown by the Portuguese National Communications Authority [6]. Coincidentally, there is a dispersed population with poor accessibility in these regions of Portugal that are currently installed the largest wind farms dedicated to energy production, particularly in the Caramulo mountain. The inclusion of entities related to these infrastructures in strategic partnerships will be enriched in the future, whether due to social responsibility or the installed technology. They can lend a decisive contribution since these infrastructures are monitored in real time, maintaining a permanent connection to the internet, either by satellite or mobile communications [7; 8]. This social responsibility must be practical and serve the most affected populations with the installation of wind farms, as stated by [PERSON], president of the company responsible for managing the Caramulo wind farm.