# Wireless Sensor Network-Based Rockfall and Landslide Monitoring Systems: A Review
## 3 Rockfall and Landslide Monitoring Based on WSNs
### WSN-Based Monitoring Systems  
In the past, researchers have carried out surveys on warning systems for geohazards [23; 72; 73], analyzing several works and methodologies available in the state of the art. However, new systems have been developed in recent years. Early prototype systems were proven to be able to gather useful information using relatively low-cost hardware using microcontrollers, commercial sensors, and low-power wireless transmitters [74]. In [75], the authors use a camera-based system and deep learning to identify the locations of possible landslides in a mountainous region of Thailand. The sensor nodes that were deployed used ZigBee [76] and Long Range (LoRa) [77; 78] low-power radio technologies. The authors aimed to investigate techniques that could be used to generate a representative image of daily slope condition from many images captured in one day. To this extent, different data fusion methods were taken into consideration. MEMS sensors are cheap and can successfully be used to detect movements on rock or soil slopes, as many research studies successfully report. A disaster prevention system based on multiple radio technologies was tested in a sloped area around Taiwan in [79]. The equipment was installed on the protection structure, aiming to display the quantitative data of rockfall events. The nodes used accelerometers and wired vibration sensors. The prototypes were built on commercial electronic circuits and encapsulated in plastic enclosures. We could distinguish three types of nodes based on transmission technology. The first was based on LoRa, while the second used narrowband-IoT (NB-IoT) [80] and the third exploited long term evolution (LTE) M1 [81; 82]. The LoRa unit communicated data to a Raspberry Pi [83] unit, which transmitted over Wi-Fi to a MySQL [84] server. The barriers can offer differing sensitivities to rockfall with  
Figure 3: Monitoring mechanisms for rockfall and landslides. respect to the observation point; therefore, the placement of the sensors is crucial. In the implementation of this system, the authors had to choose appropriate anchorage locations for the nodes on the steel barriers. The inertial measurement unit (IMU)-based WSNs are used to measure the accelerations and rotations of the installation frame. Based on this, there have been important research efforts made to distinguish the different types of slope movement. In [85], the authors presented a sensing system to recognize a rock fall event and to monitor the structural parameters of a protection mesh or concrete barrier. The architecture was divided into blocks, organized with a central LoRaWAN [86] gateway unit and sensing nodes disposed on the installation site. The elements gathered information about the vibrations and the relative inclination of the protection barrier using MEMS accelerometers and transmitted them to the sink using the LoRa modulation technique. All the data were collected on a web server used for storage and automatic alerting through messages in the case of critical events. A dashboard showed the summary reports and the collected data. The system is currently active in Pantelleria, Sicily, Italy. The paper describes in detail the hardware and firmware structure of the WSN. The authors faced difficulties in the availability of radio coverage for all the nodes, which, in the case of some elements of the network, gave poor results. Sensor fusion is the main topic in [87] where the authors presented a WSN for rock mass movement monitoring in Aachen, Germany. Tilt sensor data wads fused with MEMS accelerometer data to detect small rock movements and possible variations in inclination angle. The authors use an ISM band radio communication for the link between nodes and gateway and serial communication for data exchange between the gateway and a control server. The latter was connected to the internet for remote access using GPRS in the outdoor version and using cable in the indoor version. The nodes adopted an adaptive routing pattern to ensure the correct transmission of the packet.