## 3 Classification Based on Function
### Seismic Monitoring Sensors
The earthquake early warning system in Mexico City (SAS) is composed of four main components. (1) There is an earthquake detection system that employs 12 digital seismometers spaced 25 km apart within a 300 km coastal area of Guerrero. Each station is equipped with a microcomputer capable of determining the magnitude of an earthquake within 10 s. (2) There is a communication system with a very-high-frequency (VHF) central radio relay station and three ultra-high-frequency (UHF) radio relay stations that transmit seismic information to Mexico City within just 2 s. (3) The central control system, located in Mexico City approximately 320 km from the Guerrero Coast area, continuously receives seismic signals and automatically processes them to determine the magnitude and decide whether to issue an alarm. (4) The alarm issuance system issues warnings via commercial radio, and relevant departments are equipped with special receivers where trained personnel are responsible for receiving and coordinating disaster prevention activities [39]. A change in magnetic field can be taken as a precursor of an earthquake because the huge accumulations of crustal pressure may change the properties of the rock layer. This phenomenon affects its electrical conductivity, and the trapped gas accumulated in the formation will also produce an electric current to affect the geomagnetic activity [40]. Therefore, it is sometimes controversial to regard electromagnetic motion as an earthquake precursor. It is not clear yet, but the reasons might be as follows: (1) the signal is too weak and easily mixed with background noise to distinguish it, such as noise from nearby vehicles or small changes in solar activity that can be mistaken for geological disturbance signals; (2) accurate measurement equipment at a fixed position with enough statistical recordings are required to resolve reliable signals [41]. A number of researchers have used artificial noise signals for seismic wave velocity monitoring [42]. Artificial seismic noise is usually dominated by high-frequency body waves, providing a high spatial resolution. In addition, the location of artificial noise sources is often fixed (e.g., industrial operations) or moves along a fixed trajectory (e.g., trains and cars), which is easy to track and simulate the movement of noise sources [43]. Micro-electromechanical systems (MEMS) are devices or systems that combine microstructures, micro transducers, and micro-actuators with signal processing and control circuits [44]. Nowadays, these are commonly found in smartphones and laptops. These sensors are inexpensive and can be used to construct ultra-dense arrays. Additionally, MEMS sensors are known for their high accuracy, low power consumption, and robustness, which makes them ideal for use in harsh environments [45; 46]. Distributed Acoustic Sensing (DAS) is another effective technique to measure strain rate that consists of two parts, namely, a demodulator and sensing fiber optic cable (Figure 1). This fiber optic is deformed by the movement of the Earth's crust, which causes the refractive index of the cable to change the phase of the back-scattered light [47]. The demodulator can detect seismic activity by analyzing the coherent Rayleigh scattered light phase information of the fiber [48]. Since 2017, DAS has emerged as a novel technology to obtain numerous seismic sensors at a relatively low cost. The concept of DAS was proposed in the 1990s, followed by being applied in various fields. However, its applicability in earthquake seismology has only recently been considered. Post-earthquake monitoring is being carried out using audio signals to locate human targets in a hidden way [41; 49], and it can be strengthened by using Wi-Fi and Long-Term Evolution (LTE) in future [50]. This sensor is small and monitors the environment in a narrow space by sensing different physical characteristics such as temperature, humidity, pressure, and vibration.