# Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review
## 6 Tsunamis
### Reviewed Use Cases for Tsunami EW
Already existing national underwater stations or sensor networks (both wireless and wired) can be used to collect data (for example, about ocean bottom motion) and use it for predictions and to issue warnings. S-net is a dense cabled underwater observation network deployed along the Japan trench. It consists of 150 observation units, including both seismometers and bottom pressure sensors, connected by cables at 30 km intervals. All the data arrive to land in real time using optic fiber communications [87]. [PERSON] et al. [81] developed a method for near-real time tsunami forecasts using the S-Net sensor network data, observing the wave-forms obtained from the pressure sensors. The method is able to classify the sensors of the S-Net in terms of distance from the uplift region of the earthquake by observing the registered pressure wave-forms, and, by observing which sensors are near, outside or far from said region, it is able to compute the area of the uplift region. This technique can be used to estimate both the source region of the tsunami and the earthquake magnitude. Since earthquake waves and hydro-acoustic waves are also detected by the network, filtering is required to obtain only the pressure data. The considered time-window for computing the estimation is of about 500 s after the initial earthquake, and only 1 min is required to classify the sensors, and about 10 min to compute the source area of the tsunami after the earthquake, without the need of complex simulations. The technique was successfully validated on two past large earthquakes in that region. [PERSON] et al. [82] propose a framework and a prediction algorithm for Tsunami Early Warning in the Pacific Ocean that measures different kinds of parameters that are effected by tsunamis and monitors marine wildlife behaviour. Since changes in the magnetic field are generated by a tsunami wave, magnetic sensors can be used to detect said changes as precursors of tsunami waves; the wave itself exhibits particular waveform patterns that can be measured by a Tide Gauge; count sensors and motion sensors are used to monitor wildlife which is also affected by changes in magnetic fields from tsunamis. This data would be sensed by a WSN on the sea bed, then transmitted to a base station, and then processed at the main server. Predictions are computed by a Machine Learning Algorithm (logistic model trees) and the study had shown that the most relevant features for the prediction are tide levels changes and migration pattern changes. [PERSON] et al. [83] propose a model for Tsunami EW to improve some aspects of existing warning systems, especially for what it concerns the cost of the solution (which can be prohibitive for certain countries) and the communication in compromised situations. The proposed solution includes both an EW system (based on autonomous underwater vehicles), a platform that acts as a 'Warning Decision Support System' and is able to work offline (when disastrous events cut off standard internet communications), and an alert distribution system. The EW system makes use of low cost vehicles (which were produced and designed by one of the authors) that are characterized by low mobility, a mostly passive operational mode with very low power consumption (1 Watt, allowing weeks of operation before recharge) and the possibility to sense tsunamis remotely using acoustic detection (hydrophones). The vehicles network can also cooperate with traditional fixed tsunami sensors and they are equipped with a GPS unit and satellite connectivity. Satellite communications are also used in the Alert Distribution and Support System for the aforementioned possibility of standard IP based connections failing during the disastrous events. Underwater sensor networks are not the only available solution for Tsunami EW. [PERSON] et al. [84] designed an IoT device for wave height monitoring using an ultrasonic sensor. The device is supposed to be installed on the shore line, directly above water.