# Automated Real-Time Assessment of Stay-Cable Serviceability Using Smart Sensors
## 3 Automated Real-Time Cable Serviceability Assessment System Using Wireless Smart Sensors  
In this study, an automated real-time monitoring system for cable serviceability assessment is developed using wireless smart sensors (Figure 2). Note that the smart sensors are expected to provide the functions of wireless communication and on-board computation with small size, low cost, and low power consumption [29]. The system is designed to measure the structural acceleration response using a MEMS accelerometer and conduct on-board processing for the estimation of displacement and subsequently evaluate the serviceability. It should be noted that the proposed system in this study is a prototype for realizing the autonomous operation of assessing cable serviceability, and thus a more optimized hardware and software system considering wireless communication and power management shall be required for real-world applications. The system consists of two types of nodes: a gateway node and a leaf node, as shown in Figure 2. The gateway node is connected to the leaf node through wireless communication and remotely controls it to monitor the serviceability (Figure 2). The leaf node, installed in the mid-span of the cable, assesses the serviceability after the command from the gateway node is received, and features embedded on-board processing using smart sensors that measure the acceleration of the cable and estimate the displacement from the measured acceleration and assess the serviceability of the stay-cable. The system is composed of hardware and software in both the gateway and the leaf nodes. A When it comes to the hardware of the gateway node, Bluetooth device is used to implement the wireless system. Other wireless communication modules such as LoRa, WiFi, and Zigbee can also be applied to implement wireless communication between the gateway and leaf nodes. Among the various devices that consist of the Bluetooth module, a smartphone was selected--an efficient, user-friendly portable device to check the serviceability condition of the stay-cable. A Samsung Galaxy S10 smartphone equipped with Bluetooth version 5, which can communicate with other devices wirelessly up to 100 m, was selected as the gate node. As the main hardware of the leaf node, a single-board platform, the Raspberry Pi 3 Model B+, was selected for on-board processing (Figure 2). This low-cost and low-power single-board computer is equipped with a 1.4 GHz Quad-Core 64-bit ARMv8 CPU and 1 GB  
Figure 1: Displacement estimation scheme using overlapping time window. LPDDR2 SDRAM, which demonstrates the capability to carry out the entire embedded processing, from acceleration measurement to serviceability assessment. Furthermore, this hardware possesses HDMI, four USB 2.0 ports, 5 V/2.5 A DC power input, extended 40-pin GPIO headers, 2.4 GHz wireless LAN, Bluetooth 4.2, and a micro SD port for loading the operating system and storing data. Users can access and control the Raspberry Pi 3 Model B+ easily using a keyboard, mouse, and display through HDMI and USB ports. As this single-board computer is equipped with a Bluetooth module, the gateway node can be wirelessly connected to the leaf node, the main hardware of which is the Raspberry Pi 3 Model B+. Further, extended 40-pin GPIO headers aid the single-board computer to control and monitor the external sensors, such as the accelerometer through connections with the electronic circuits. To measure the acceleration, an ADXL335 smart sensor--a small tri-axial MEMS-based analog accelerometer with low cost and low power consumption (Figure 2)--is selected. This MEMS accelerometer is known to measure accelerations up to 3 \(g\) (270 mV/g sensitivity) with sampling rates of 0.5-1600 Hz for the \(X\)- and \(Y\)-axis and 0.5-550 Hz for the \(Z\)-axis. With the analog-based ADXL335 accelerometer, an ADS1115--a 16-bit analog-to-digital converter (ADC)--is used to convert analog acceleration into digitalized acceleration because the Raspberry Pi 3 Model B+ is equipped with GPIO headers with digital input only (Figure 2).