# Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review
## 6 Tsunamis
### Systems Requirements and Constraints for Tsunami EW Systems  
An underwater acoustic network needs to be both reliable and energy-efficient. Accurate energy budgets/lifetime estimations are necessary since sensors replacement is more difficult, and energy harvesting techniques (wave motion harvesting, microbial fuel cells [89]) are suggested to enhance the life of the sensors deployed underwater [78]. The  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Article** & **Perception Layer** & **Communication Layer** & **Application and Edge Layer** & **Edge/Fog Computing** \\ \hline
[79] & Pressure Sensors. & Acoustic communications. & Not yet implemented, the goal is to use the optimized network for real-time detection. & No. \\ \hline
[80] & Methodology independent of the type of sensor & Not specified & Tsunami forecasting based on ”Inversion for initial sea-Surface Height” method to determine tsunami source & No. \\ \hline
[81] & Optic Communications & Pressure Sensors. & Classification of sensor nodes at central server & No. \\ \hline
[82] & Magnetic sensors, tide gauge, count sensors and motion sensors & GSM & Machine Learning model at central server & No. \\ \hline
[83] & Autonomous underwater vehicles & Acoustic signals processing; Satellite communications & Warning support decision platform able to work offline & No \\ \hline
[84] & Ultrasonic Sensor & GSM & Threshold-based SMS alarm system at sensor level & Yes. \\ \hline
[85] & Satellite Communications & GNSS system, acoustic sensors & Coordinates estimation at buoy level; buoy data processing and dissemination at central station; web server user interface & No. \\ \hline
[86] & Gyroscope, accelerometer & LoRa & Fuzzy logic algorithm at sensor level; data processing and storage at central server & Yes. \\ \hline \hline \end{tabular}
\end{table}
Table 6: Technologies and solutions used for each layer by the reviewed papers for Tsunami EW.  
correct positioning of the sensors can help reduce costs and increase accuracy of predictions. The positioning of the central hub and terrestrial receivers is also important, since they could be compromised by earthquakes or tsunamis [85].  
While the acoustic channel is a better solution for UWSN than the radio channel, it also comes with its own limitations: frequency dependent attenuation, multipath and high and variable delays. Specific modulation schemes are also suggested for the acoustic channel to enhance the overall communications and reduce multipath effects [89]. Routing protocols also play an essential role in UWSNs since acoustic communications are very energy consuming and therefore they require energy optimized routing, which has often been achieved at the expense of higher delays [78]. In IoUT, data aggregation is made more difficult by the fact that the overlap of multiple routing paths will increase packet collisions in the area and it will require re-transmissions, increasing energy consumption, and decreasing reliability [76]. When making use of mobile sensor nodes, such as underwater vehicles or sea gliders, further challenges in terms of routing, node localization and synchronization, and energy consumption are introduced [78].  
Like for UWSN, buoys solutions for wave detection come with challenges compared to on-land deployments, since the connectivity between neighboring nodes can be affected by wave height, and as such dedicated routing protocols and processing algorithms are required [90], and the tilting of the buoys can also degrade the communications.