### Literature Review on Available Solutions  
In order to face the above problems, several approaches have been proposed. Among them, noteworthy examples of Internet of Things Wireless Sensor Networks (IoT -WSNs), monitoring platforms and recommender systems are reported in the following (Table 1), also exploiting the use of machine learning (ML) in IoT systems [8]. Importantly, the applicability of the WSNs mainly depends on the lifetime of the sensor nodes, and, for this reason, it is important to design this type of system while bearing in mind this crucial aspect and selecting the more convenient energy efficient routing protocol [9; 10; 11]. Other important design parameters are [10; 12; 13]: (i) the limited storing and computational resources of each sensing nodes, (ii) the costs (i.e., cheap sensors are prone to failure, while expensive sensors need good housing and cannot be used for dense deployments), (iii) the position of each sensing node, which cannot be predetermined and depends on the accessibility of the point where the node should be placed, (iv) the sensing nodes' deployment (to collect the needed data, to have the required coverage and connectivity, to extend the network lifetime, and to minimize energy consumption), and (v) the minimum number of time slots required to aggregate data along the edges of a data-gathering tree spanning all the nodes in a WSN (a.k.a., minimum aggregation delay), if the gathered data are aggregated before the transmission to the control center. The solution presented in this paper was designed while bearing in mind all the design parameters mentioned above, focusing, in particular, on maximizing the exploitation of the nodes' storing and computational resources, on minimizing the system cost and on optimizing the system deployment. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Reference** & **Main Characteristics** & **Limitations** \\ \hline \multirow{4}{*}{[14]} & WSN based on energy-efficient wireless sensor nodes & Buildings only; Ultrasonic sensor \\  & equipped with an ultrasonic sensor, which were tested in a & only; Explosion emergency only; \\  & field experiment (explosion in a building) to confirm & Does not consider the \\  & functionality and reliability in terms of collision-free data & overcrowding. \\  & transmission during the emergency. & \\ \hline \multirow{4}{*}{[15]} & WSN based on the idea of monitoring the earthquake & \multirow{4}{*}{Earthquake emergency only; Does not consider the overcrowding.} \\  & precursors (e.g., unusual movement of animals, ground water & \\ \cline{1-1}  & pressure, radon emission, etc.), which was designed for early & not consider the overcrowding. \\ \cline{1-1}  & earthquake warnings and disaster management. & \\ \hline \multirow{4}{*}{[16]} & WSNs used together with Unmanned Aerial Vehicles (UAV) & \multirow{4}{*}{Does not consider the overcrowding.} \\  & for monitoring, forecast, early warning, information fusion & \\ \cline{1-1}  & and sharing, logistics, evacuation, search and rescue mission, & \\ \cline{1-1}  & damage assessment. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Examples of Wireless Sensor Networks (WSN) and Internet of Things (IoT)-WSN solutions for emergency and disaster management. Another group of solutions for the problems mentioned above is represented by software platforms (Table 2).