## 6 Discussion and Limitations  
This section provides a brief discussion of the obtained results. Subsequently, certain limitations of the conducted research have been highlighted. **Discussion on WSN platforms:** An analytical comparison of WSN platforms in terms of various performance attributes has been presented in Table 8. The attributes of the comparison include the specifications of the data acquisition subsystem (ADC channel as well as resolution), the specifications of the embedded processor (embedded processor as \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & \multirow{2}{*}{**Voltage (V)**} & \multirow{2}{*}{**Max. Temp. (\({}^{\circ}\)C)**} & \multicolumn{2}{c}{**Performance**} & \multirow{2}{*}{**Rectification**} & \multirow{2}{*}{**Integration**} \\ \cline{3-4} \cline{6-7}  & & & **Max. Power (mW)** & & & \\ \hline
[73] & 1.18 & 33 & 400 & - & AC-DC Converter & Supercapacitor (0.1 F) \\ \hline \hline \end{tabular}
\end{table} 
Table 15: Thermal energy harvesting systems. well as data memory) in the target platforms, and the specifications of the wireless channel (radio transceiver, frequency band, and data rate/outdoor range) in the data communication subsystem. From the results in Table 8, it can be observed that most of the WSN platforms deploy ADC with 12-bit resolution. It is adequate to digitize input analog signals from the sensors with high accuracy. In addition, most of the platforms have eight channels in the data acquisition subsystem. These channels are sufficient to acquire input data from various sensors. Regarding the embedded computing subsystem specifications, the ATmega128 (64 KB SRAM + 48 KB Flash) and the TI MSP430F1611 processors (10 KB SRAM + 48 KB Flash) are the most widely used microcontrollers in recent studies with an adequate size of data and program memory for SHM applications. Regarding the specifications of the wireless channel systems, the CC2420 is the most frequently used RF transceiver. The Zigbee technology is the most frequently used wireless protocol in the selected WSN platforms. Finally, Table 9 presents a summary of the accuracy of WSN systems. It is related to the measurement of different quantities such as acceleration and strain, acoustic emission, and impedance. Only 13 studies (out of 37 selected studies) are included as the accuracy of the proposed system is not mentioned in the other 24 selected studies. From Table 9, it can be argued that most of the proposed WSN systems exhibit reasonable accuracy in measuring different quantities compared to wired or commercial systems. **Discussion on energy harvesting techniques:** This SLR covers the following techniques: vibration, solar, wind, radio frequency (RF), and thermal. The eleven selected studies for vibration energy harvesting techniques are further categorized into six studies for the electromagnetic-based vibration energy harvesting systems and five studies for the piezoelectric material-based vibration energy harvesting systems. Accordingly, a comprehensive analytical comparison of energy harvesting techniques in terms of various performance attributes has been presented in Tables 10-15. The main attributes of the comparison process include the output voltage and power, the rectification process, and the integration process. From the results of this SLR, it can be argued that the output power in electromagnetic-based vibration energy harvesting systems is directly proportional to the volume of the electromagnetic. Furthermore, the output power and voltage in solar energy harvesting systems are directly proportional to the size of the PV module. In wind energy harvesting systems, the output power and voltage are directly proportional to the diameter of the wind turbine. **Discussion on sensor type:** One of the most important considerations when designing an SHM system is the selection of sensors and sensed parameters.