# Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review
## 5 Earthquakes
### Reviewed Use Cases for Earthquakes EW
[64] proposed a MEMS accelerometers network that can meet the same performance as a classic dense Earthquake EW network. Each low-cost MEMS Seismograph consists of: the MEMS accelerometer module, TCP/IP module, Power over Ethernet module, and an optional local storage module. Synchronization is achieved using a simplified Network Time Protocol (NTP). The standalone TCP/IP module is able to handle the data communication to the server via Ethernet by itself, so that the sensing unit can be controlled by a simple MCU unit, since it does not have to handle the communication routines. A low-cost seismic sensor array with 10 sensors connected to 3G/4G modems was built for field testing. The records obtained by the low cost sensors have good consistency with the data obtained by the standard seismographs and that they can obtain clear seismic phases to trigger earthquake detection for early warnings, and even earthquakes with smaller magnitude (M 3.1 to M 3.6) were identified within a 20 km range from the sensors. Bigger earthquakes (M 4.7) can be detected at up to 200 km from the sensors. [PERSON] et al. [65] tested the performance of a dense Earthquake EW network of 170 sensors that they were able to deploy in the Sichuan-Yunnan border region, China. The sensor design is better specified in [66] and it is a low-cost, low-energy MEMS accelerometer sensor with the performance of a Class B accelerometer (for comparison, MEMS sensors are usually Class C sensors, such as the unit used in the previously reviewed solution [64]). Each unit also provides data suitable for P-wave detection, early warning parameters computing, and a low-latency data packet transmission. For each station, a 3G/4G router was used to transmit the ground-motion data recorded by the network to a processing server. The records obtained by the sensors were compared with the ones of classic earthquake stations, showing a good consistency, even for sensors at more than 150 km from the epicenter, thus proving that this low-cost solution can be used for dense Earthquake EW system and allows drastic reduction of the investment required to cover the region of interest. The system is also able to produce'shake-maps', which are also useful for post-disaster response. When the seismic network in the earthquake source region is sparse, there are large system biases when computing the shake-map. Moreover, usually more than ten minutes are needed for generating a shake map, while the deployed high density network computed shake-maps with good accuracy and almost in real time. MEMS sensors are installed in most smartphone devices, so the information from a large number of devices can be used to create a widespread seismic network. This is called mobile crowd-sensing paradigm, or MCS. An MCS architecture is the one proposed by [PERSON] et al. [68] which consists of three layers: layer 1 collects data from the low-cost smartphones network, including the users' position using the devices' GPS units, and detects seismic peaks, achieving synchronization between devices with different time references using the NTP; layer 2 determines if there is an actual seismic event to notify and it ensures the global reliability of the system; layer 3 is the control center, and it communicates with emergency management centres. The high heterogeneity of the sensor network also requires standardization of the sensor data and its collection, which is achieved at the second layer by the Sensor Web Enablement framework and specifically by its Sensor Observation Service component. The architecture also takes into account battery saving and memory consumption for the user device, reaching good battery performances thanks to the use of the lightweight MQTT protocol. The seismic detection was also validated using real data, showing that the solution anticipates the seismic peak by 12 s.  
The MyShake Platform is an operational framework that can provide Earthquake EW system using smartphones developed by [PERSON] et al. [69] and that has been working as a phone application since 2016.