Analysis of dynamic path loss based on the RSSI model for rupture location analysis in underground wireless sensor networks and its implications for Earthquake Early Warning System (EEWS)

Abstract

Sensors deployed in underground tunnels found that radio frequency signals suffer significant signal strength attenuation which can result in considerable variation of link quality on the receiving end. This study analyzes the received signal strength index (RSSI) based on the development of a theoretical wireless sensor model for data collection by enabling sensors to determine the location from which each data packet is obtained. To improve positioning accuracy, the complex radio wave propagation environment requires the use of a voronoi cell to minimize signal attenuation. A relatively simple calculation is used to predict the intensity and perception range of the received wireless signals to measure the extent of signal reduction in the attenuating rock medium. Simulation results show that RSSI-based localization and wireless network lifetime and throughput measurements are more accurate when the node concept is applied to the self-locating rupture zones than the maximum likelihood estimation method. The proposed minimum energy relay routing technique based on beacon node chain deployment is found to help correct localization errors resulting from interference caused by the underground tunnel environment. The extent of localization and power of the sensor nodes are determined based on the beacon node chain deployment of tunnel wireless sensor networks. The algorithm accounts for the distance and the corresponding RSSI between adjacent beacon nodes to calculate the actual path loss parameter in the tunnel. The proposed model can serve as the theoretical basis for locating ruptures in underground wireless sensor network nodes, thus maximizing the monitoring range of large scale tectonic environments while minimizing equipment cost. We recommend that this model can be field tested through a series of experiments by researchers and engineers working in seismology, telecommunication, and information technology.

Quality of Service and Power Consumption Optimization on the IEEE 802.15.4 Pulse Sensor Node based on Internet of Things

“…So that if distance (d) gets bigger, the value of L Free Space (-dB) will increase. So that the frequency of Zigbee is 2.45 GHz, from equation 4 becomes equation (5).…”

“…Assuming the antenna gain for both transmitter and receiver is 0 dB (1 mW) on the Zigbee specification, on free space propagation is formulated in equation (8). And for indoor propagation condition is shown in equation 9.…”

“…4, from this communication system traffic data, can be analyzed from End Device Node, Router Node and Coordinator Node, this data traffic includes Quality Of Services (QoS) i.e. Throughput, Packet Loss and Delay, and Radio Frequency (RF) capabilities in sending data indicated 21`y Radio Signals Strength (RSS) or Radio Signals Strength Indicator (RSSI) [2,3,4,5,6]. at previous research testing the performance of Raspberry Pi 3 in capturing radio waves with the Master-Slave system using an RF Bluetooth RN-42 device in sending multi LM35 sensor data, accordingly in this research study the RSSI value is different from the environment can be monitored, from this study obtained the value of precise RSSI [7,8,9,10], furthermore, the next research will be developed of sensor node using a multi-sensor (pulse and blood Pressure sensor).…”

A new rapid positioning strategy for the impact-point using dynamic mode decomposition and time difference of arrival *

“…(1) DOA uses the directional angle of the target to locate and has a wide range of applications in the field of spatial stereo positioning. In plane positioning, the positioning precision is poor due to angular resolution [23], multipath effect [24,25], and noise; (2) RSSI takes advantage of signal attenuation law to locate, which can overcome the problem of inaccurate time synchronization [26]. But it is not so simple to acquire the laws of attenuation; (3) TDOA estimates the source coordinates by measuring arrival time difference, with a high degree of accuracy.…”