# Monitoring the Health and Residence Conditions of Elderly People, Using LoRa and The Things Network
## 2 Related Work  
Several studies have been carried out in recent years on the use of low consumption and long-distance communication networks, mainly in the context of home automation [11; 12] and agro-industrial applications [13], using LoRa networks and other similar technologies, namely SigFox [14], NB-IoT [15], LTE-M [16], and TV Whitespace [17], among others.  
LoRa communication technology enables the interconnection of several-thousand-batteries-powered devices over long distances with reduced power consumption. The LoRa technology takes part in the LPWAN (Low Power Wide Area Network) group, particularly LoRaWAN, allowing communication over long distances, even in adverse conditions, with 15 km in open space or 7 km in urban areas [18]. Furthermore, low power consumption is essential in devices intended to be used for an extended time on a battery. LoRa technology uses the unlicensed frequency band, with 868 MHz in Europe, 915 MHz in North America, and 433 MHz in Asia [19]. The basic architecture of the LoRaWAN network is composed of several nodes (devices) and Gateways that can be connected to The Things Network (TTN). In addition, the data are stored in the cloud and later made available on interface platforms. These platforms contain dashboards that enable the interaction and availability of data on other platforms, using REST web services and access platforms by MQTT (Message Queuing Telemetry Transport), e.g., Node-RED. Figure 1 shows a Node-RED connection to the prototype system developed, using an MQTT Input object to obtain data from the apptesttemp application created in TTN. Node-RED is an IoT application development framework based on streams of visual programming initially developed by IBM to connect hardware devices, APIs, and online services [20].  
In Node-RED, an MQTT Input is in a node that reads the submitted data to the TTN in real time, as shown in Figure 1, and one such node is connected to the _apptesttemp_ application and _lorattigo1_teste_ device. Thus, whenever data are submitted, their values can be analyzed in real time in the debug window or the dashboard application. Furthermore, the nodes are connected by flows, where the terminal nodes output can be a graphical representation, data in text, or registered in a database.  
The authors of [21; 22] present models of low-consumption and long-range networks for homes and industry automation, respectively, using LoRa (Long Range) communication technologies. These communication networks are essential if data are to be disseminated and analyzed, without necessarily resorting to the internet, collecting data from various sensors, and maintaining their activity for an extended time. As a result, the consumption of devices and sensors is reduced.  
In work [23], the authors have evidenced the potentialities to monitor wind farms, using the LoRa and LoRaWAN (Long-range Wide Area Network) networks. The authors have shown that the use of LoRa networks allows efficient communication over long distances when monitoring non-critical situations. In addition, the connection to an external IoT platform produces some delay, and its use for real-time monitoring is somewhat compromised.  
Work [24] proposes an advanced architecture, combining Edge computing, Fog computing, LoRa, and other IoT-based technologies to monitor patients in hospital settings. The proposed architecture can help overcome the limitations of existing IoT-based physical integrity monitoring systems, e.g., in detecting falls, evidencing the functionality of the architecture for this purpose.  
In the context of smart cities--an area in which LoRa communications know a significant space of use--the authors of [25] show the efficient way to monitor urban buses, using the LoRa and LoRaWAN networks to estimate, in real time, the approach of the bus to the stop, allowing a global GPS view of the movement of the vehicles in their fleet.