# A Hybrid Scheme for Disaster-Monitoring Applications in Wireless Sensor Networks
## 3 Collaborative Disaster-Monitoring System  
Based on WSNs, earthquake information can be collected and delivered to seismic areas. With rapid advances in communication, embedded computing, and sensing techniques, various WSNs have been developed. WSNs can perform collaborative real-time monitoring, sensing, and gathering of data in various environments or surveillance objects. These data are processed to obtain accurate information that is finally delivered to the user. WSNs can obtain massive, detailed, and reliable physical world information at any time or place. However, for a disaster-monitoring system, the primary goal is to transmit alerts and superior information as quickly as possible, even when the network is under a heavy load. The limited computing power, communication ability, and battery energy of the heterogeneous nodes for wireless sensor networks must be considered. A network topology diagram of the collaborative disaster-monitoring system is shown in Figure 1. The system is a three-layered architecture of the Internet of Things. It consists of three parts: the wireless sensor networks as the perception layer, the satellite communication part as the communication layer, and the service center as the application layer. The wireless sensor network contains three types of sensor node: the seismic, picture, and sound nodes. Each node has two wireless communication interfaces. First, all sensor nodes are divided into clusters, and the node with the highest relative energy in a cluster is selected as the cluster head. Subsequently, in-cluster communication is performed using a hybrid superior node token ring scheme with one communication interface. Sensor nodes transmit data to the cluster head via a one-hop transmission. Communication between the cluster heads and the base station follows the TDMA mode with another communication interface. Seismic monitoring nodes gather seismic information using a seismometer. Picture-monitoring nodes capture pictures of a scene, and sound-monitoring nodes capture sound signals. These nodes then transmit information to the base station. Different types of nodes are equipped with batteries of different capacities. The base station contains a satellite transceiver and a battery rechargeable with solar energy. The satellite communication part is responsible for the long-distance transmission of information. It does not rely on the ground-based infrastructure. The base station delivers the collected information to the service center via satellites, satellite ground stations, and internal networks. The server of the service center can process all kinds of information both in time and effectively. Thus, based on the satellite link, disaster information can be obtained and processed even when the ground-based communication infrastructure in the earthquake zone is destroyed. Seismic data can be treated as continuous variables in disaster-monitoring applications in WSNs. Continuous values are collected from spot observations; hence, each piece of data collected is important and indispensable. However, this may result in an excessive burden on the small nodes of the WSNs. Benefiting from advances in information technology, the method of compressed sensing for WSNs is effective for reducing this burden. Assuming that the distribution of data is sparse in a certain domain, this type of data collection with sensor nodes can be compressed using the compressed sensing method. In a collaborative disaster-monitoring system based on the compressed sensing method, seismic data can be obtained in an energy-efficient manner. This system provides real-time and efficient ground vibration data, events, and alerts through satellite links. First, the seismic monitoring nodes perform compressive sampling of seismic variables and then deal with the compressive sampling data, alert them to network packets, and send them to the base station. The base station has a higher computing power and a larger solar energy supply than the sensor nodes.