## 4 IoT-Cloud-Based EWS
The architecture of the system was designed to be regionally spread, which allows for both brisk processing and resistance to disruptions in some aspects of the underlying infrastructure. To be more specific, these systems combined GPS and seismic data in order to enhance earthquake detection, which led to the creation of an efficient EEWS. [PERSON] [189] used vibration sensors for earthquake detection according to some threshold values. If an earthquake has been detected via the vibration sensors, a warning system takes place. In this warning system, there is a Wi-Fi module for Internet connection to send a tweet by means of the ThingSpeak IoT analytics platform service. There is also a sound alarm via a buzzer for the people staying around the earthquake area. Thus, the electronic part of this study covers an Arduino card, Wi-Fi module, Inertial Measurement Unit sensor, vibration sensor card, and buzzer. The software part involves the codes of Processing with Arduino to obtain the sensor data normalization and the difference between sequential sensor values for monitoring the threshold level. [PERSON] and [PERSON] [190] have studied an IoT solution that alerts for a flood or earthquake detection before they happen and living beings being searched for during the disasters. Sensors are connected to a microcontroller, RF transmitter, and receiver. Their values are analyzed in real-time via ThingSpeak IoT analytics platform service [190]. The authorities are notified by GSM messages during a flood or earthquake disaster using the IP protocol. A water level sensor has been used for flood detection, and four color bulbs represent the danger levels. A rain sensor has worked to determine whether there is rain. Additionally, a vibration sensor has been used for an earthquake. The system and the mobile phones are charged with solar energy as a secure option for flood environments. ESP Wi-Fi module is the gateway as the fundamental processing and storage part between the RF receiver-transmitter-bulb system and ThingSpeak cloud server for sensor data transmission. This data can be followed using a ThingSpeak API that is used for mobile phones, laptops, or any other internet-connected device. Wireless communication, especially GPS, is used for living being searches. [PERSON] et al. [191] proposed a high-fidelity vibration sensor consisting of a MEMS accelerometer with high sampling frequency and digital filtering. During the sensing process, Short-Term Average/Long-Term Average trigger is compared with a threshold value. Over the threshold, data acquisition, low-pass filtering, and downsampling to a frequency are performed. After this procedure, if an earthquake is detected with the proposed algorithm, the system notifies it through a Bluetooth Beacon. The authors mentioned that the hardware platform was Adafruit nRF52840 Feather Express developed based on nRF52840 (Nordic, 2019) board having fast computing and high storage attributes provided by CPU, RAM, and flash parts. Additionally, the nRF52840 module has Bluetooth 5 and Arduino IDE support. [PERSON] et al. [192] mentioned that the literature studies could not separate any other vibrational noise properly from that of earthquakes. They proposed a new method by using IoT to eliminate this drawback. A Micro Electro-mechanical system sensor is set inside a building after finding the most suitable place via structural analysis with the information on seismic shear walls. Inside this sensor, there is an accelerometer and a gyroscope. The gyroscope saves the ground's shaking pattern, representing a distinctive nature during an earthquake. IoT I\({}^{2}\)C Communication Protocol is used between the devices in the network. Arduino Uno microcontroller board and NodeMCU Dev Kit firmware have interfaces with the sensor node. The sensor data is sent by Arduino inbuilt WiFi to the ML side. In this part, Logistic Regression, Support Vector Machine, and Convolutional Neural Networks have been used for modeling. [PERSON] et al.