## 3 SENDI: System for Detecting and Forecasting Natural Disasters Based on IoT  
This section provides an overview of SENDI, a fault-tolerant system based on IoT and ML for the forecasting and detection of natural disasters. SENDI is formed of 3 tiers, as illustrated in Figure 1. The first tier consists of a WSN, which is responsible for collecting and disseminating data from the monitored environment. The second tier (fog computing) is responsible for concentrating the data in the sensor nodes, as well as carrying out the distribution and processing of the data collected from the first tier. In addition, it should be noted that the second tier is based on the fog computing paradigm, which leaves the computing resources (processing and storage) closer to the end-user so that it can improve the latency of the service. Finally, the third tier consists of _Cloud_ where all the data of the system are concentrated and provides processing power and data storage in an abstract form. In this way, the _Cloud_ obtains a general view of the monitored environment and is able to combine the data gathered by the sensors with data available on the Internet and make more accurate forecasts, as well as issuing online alerts to the people in the locality.  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{1}{c}{**Synthesis**} \\ \hline [PERSON] et al. [9] & Use IoT and Crowdsourcing to disaster response, also presenting a case study \\ [PERSON] et al. [6] & Present a IoT environment assisted by social network to help disaster management \\ [PERSON] et al. [10] & Propose the use of IoT DfPL to enable users to be located and disaster management \\ [PERSON] et al. [11] & Combine WSN and _Cloud_ computing to forecast natural disasters \\ [PERSON] et al. [13] & Present an WSN, IoT and ML approach for flood forecast \\ [PERSON] et al. [14; 15] & Propose, present and discuss the results of alternative approaches to address the energy \\  & limitation problem \\ [PERSON] et al. [12] & Present a survey and an approach focusing on the evaluation of _Cloud_ datacenters performance \\ \hline \hline \end{tabular}
\end{table}
Table 1: Papers summary.  
Figure 1: Architecture of the SENDI system viewed from the tier.  
The conception of this solution arose from the E-Noe project, which was installed in the town of Sao Carlos and involves flood forecasting and detection and issuing warnings of a possible flood to the residents in the region. For this reason, the main aim of SENDI is to improve the forecasting of natural disasters, while at the same time, providing a fault-tolerant scheme to the system. In the case of this last point, it is essential to ensure that the system is operating, whatever the situation.  
The way each tier works is shown in Section 3.1 for a better understanding of SENDI. Following this in Section 3.2, there is an explanation of how the communication took place between the nodes and the dispatch of data to the Internet. After this, the fault-tolerance mechanism is outlined in Section 3.3. Finally, there is an explanation in Section 3.4 of the main features of the data collected by the WSN installed in Sao Carlos--SP, Brazil and how these data are used to create the model for disaster forecasting (flash floods in this case).