# Satellite-Based Wireless Sensor Development and Deployment Studies for Surface Wave Testing
## 5 Results  
As we can see, the plain text received from the RockBLOCK 9602 was encrypted by a random linear measurement matrix. To decrypt the data transmitted on the server, \(l_{1}\)-norm optimization algorithm was employed to reveal the seismic wave acquired by the accelerometer. After the decryption, a comparison between the raw time-history signals recorded by the accelerometer (backup data) and the signal reconstructed from the encrypted SBD transmitted by the satellite device is shown in Figure 5. The encrypted data is shown in Figure 5a, and the original acceleration data recorded in the embedded SD memory card and the reconstructed acceleration data extracted from the cloud server are respectively shown in Figure 5b,c. As we can see, the recovered data has a good agreement with the backup data (the reconstructed errors are demonstrated in Figure 5d, which endorses the functionality of both the hardware architecture and the coding program of the wireless sensing node.  
All of the data packages were numbered sequentially for sending, although data package loss seems unstoppable for wireless sensing resulting from multiple reasons, such as weather, environmental interaction, and unclear sky. In one case of the outdoor field testing for sensor 5, one of the six encrypted packages was lost (Figure 6a). Thanks to the CS-based encryption strategy, the original acquired accelerometer data can be preserved through the random coding measurement matrix. As demonstrated in Figure 6a, the data received from the server has one packet lost from the satellite  
Figure 5: Data recovery results of the measured acceleration by sensor 4: (**a**) Encrypted data; (**b**) original measurements extracted from backup file; (**c**) recovered data from SBD data transferred via satellite communication; and (**d**) comparison and reconstruction error.  
communication. After reassembling the remaining packets by their UTC tags, the data was recovered (as show in Figure 6c) by the \(l_{1}\)-norm optimization algorithm with a limited error (Figure 6d maximum error of 19.1%). The optimization approach yielded good data recovery results when compared with the backup data (Figure 6b) saved in the SD memory card, which proves the CS-encrypted data is robust even with lost data packets.  
The acceleration data recovered from all the five sensors are shown in Figure 7. Meanwhile, GPS information was also transmitted from the wireless sensing node to the server via satellite communication, which provides the possibility of the deployment of a wireless geophone array for large-area site surface wave testing. The GPS information of the wireless sensing node was extracted from the satellite communication and stored in a separate output variable in the database. Based on the longitude and latitude information, the location of this proof-of-concept test was visualized in the map as shown in Figure 8.  
Figure 6: Recovered results of sensor 5 from SBD data loss: (**a**) Received data packets with 16.7% data loss; (**b**) original acceleration extracted from backup file; (**c**) recovered data from the remaining SBD data packets; and (**d**) comparison and reconstruction error.