Structural Health Monitoring by Payload Compression in Wireless Sensors Network: An Algorithmic Analysis

Abstract

Structural health monitoring is the fact of estimating the state of structural healthor detecting the changes in structure that affect its performance. The traditional approach to monitor the structural health is by using centralized data acquisition hub wired to tens or even hundreds of sensors, and the installation and maintenance of these cabled systems represent significant concerns, prompting the move toward wireless sensor network. As cost effectiveness and energy efficiency is a major concern, our main interest is to reduce the amount of overhead while keeping the structural health monitoring accurate. Since most of the compression algorithm is heavy weight for wireless sensor network with respect to payload compression, here we have analyzed an algorithmic comparison of arithmetic coding algorithm and Huffman coding algorithm. Evaluation shows that arithmetic coding is more efficient than Huffman coding for payload compression.

Sensifi: A Wireless Sensing System for Ultra-High-Rate Applications

“…Since processors' energy consumption is usually lower than that of wireless transceivers, data compression is another method used by the existing works to reduce the amount of data sent by each node and enhance energy efficiency. Considering the small packet sizes allowed by the 802.15.4, Islam et al [38] argued that providing IP compatibility by using the 6LowPAN adaptation layer requires compression. They proposed a payload compression method using an arithmetic coding algorithm and evaluated efficiency by comparing the data compression ratio, memory consumption, and compressed data size against Huffman coding.…”

“…Compared with the existing works that rely on TinyOS [8], [30], [35], Linux [36], [37], or theoretical performance analysis [28], [38], we use the two widely-used Real-Time Operating Systems (RTOSs) targeting resource-constrained devices: FreeRTOS [39], [40] and ThreadX [41], [42]. Also, we use the network stacks available for these RTOSs, namely, LwIP [43], NetX [44], and NetXDuo [45].…”

Addressing the detection capability for scalable energy consumption using primary data acquisition system of embedded ultrasonic sensors in SHM

“…The suitable data communication system needs to be selected. Typical SHM system has either the Wide Area Network (WAN) or Local Area Network (LAN) [7]. Large systems are operated with a backbone of fibre optic networks that allow for redundant systems with no data loss [8].…”