Abstract—Lossy transmission is a common problem suffered
from monitoring systems based on wireless sensors. Though
extensive works have been done to enhance the reliability of
data communication in computer networks , few of the existing
methods are well tailored for the wireless sensors for structural
health monitoring (SHM) . These methods are generally unsuitable
for resource-limited wireless sensor nodes and intensive
data SHM applications. In this article, a new data coding and
transmission method is proposed that is specifically targeted at
the wireless SHM systems deployed on large civil infrastructures.
The proposed method includes two coding stages, i.e., a source
coding stage to compress the natural redundant information
inherent in SHM signals and a redundant coding stage to inject
artificial redundancy into wireless transmission to enhance the
transmission reliability. Methods with light memory and computational
overheads are adopted in the coding process to meet
the resource constraints of wireless sensor nodes. Specifically,
the lossless entropy compression (LEC) method is implemented
for data compression; and a simple random matrix projection is
proposed for redundant transformation. After coding, a wireless
sensor node transmits the same payload of coded data instead of
the original sensor data to the base station. Some data loss may
occur during the transmission of the coded data. However, the
complete original data can be reconstructed losslessly on the base
station from the incomplete coded data given that the data loss
ratio is reasonably low. The proposed method is implemented
into the Imote2 smart sensor platform and tested in a series of
communication experiments on a cable-stayed bridge. Examples
and statistics show that the proposed method is very robust
against data loss. The method is able to withstand data loss up
to 30% and still provides lossless reconstruction of the original
sensor data with overwhelming probability. This result represents
a significant improvement of data transmission reliability of
wireless SHM systems.