## 5 Summary and Discussion
### Future Research Directions for Port Crane Monitoring  
To further enhance the integration of vibration and AE sensors with IoT for the remote monitoring of port cranes, the following several research directions should be prioritized:  
* Development of next-generation sensors--Research on nano-enabled, self-powered, or bioinspired sensor materials could yield devices with enhanced sensitivity, environmental resistance, and energy efficiency.
* Hybrid NDT frameworks--Integrating vibration and AE sensors with complementary NDT techniques (e.g., thermal imaging and guided wave testing) may provide a holistic and redundant diagnostic framework for critical crane components.
* AI-driven predictive maintenance--Continued exploration of AI models for anomaly detection, pattern recognition, and lifecycle prediction enhances system autonomy and decision accuracy.
* Self-sustaining monitoring systems--The incorporation of energy harvesting technologies, such as piezoelectric or thermoelectric generators, could eliminate the need for manual sensor recharging or replacement, thereby improving system sustainability.
* Standardization and interoperability--Establishing international standards for RNDT sensor calibration, data formats, and IoT communication protocols would accelerate technology adoption and cross-system integration in global port operations.  
To provide a clear overview of the current limitations and prospective advancements in the field, Table 6 summarizes the key research gaps identified in this review, along with recommendations for future research directions. These gaps span sensor integration, data processing, durability in marine environments, and adoption of intelligent systems for predictive maintenance. Addressing these areas is essential to accelerate the deployment of robust, IoT-enabled remote NDT frameworks for port crane infrastructure.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Traditional NDT** & **IoT-Based NDT** & **Reference** \\ \hline Inspection Mode & Periodic, manual & Continuous, remote & [73; 114] \\ \hline Coverage Scope & \begin{tabular}{c} Localized, \\ point-based \\ \end{tabular} & \begin{tabular}{c} Wide area, \\ sensor-networked \\ \end{tabular} & [104; 121] \\ \hline Detection Accuracy & \begin{tabular}{c} Operator- \\ dependent, variable \\ \end{tabular} & \begin{tabular}{c} Algorithm- \\ enhanced, \\ consistent \\ \end{tabular} & [105; 122] \\ \hline \begin{tabular}{c} Personnel \\ Dependency \\ \end{tabular} & \begin{tabular}{c} High (skilled \\ inspectors needed) \\ \end{tabular} & \begin{tabular}{c} Low (remote \\ monitoring and \\ AI-assisted) \\ \end{tabular} & [70; 102] \\ \hline \begin{tabular}{c} Cost Efficiency \\ \end{tabular} & \begin{tabular}{c} High labor and \\ equipment costs \\ \end{tabular} & \begin{tabular}{c} Higher setup cost, \\ but reduced \\ long-term O\&M \\ costs \\ \end{tabular} & [120; 123] \\ \hline Safety & \begin{tabular}{c} Risky for inspectors \\ (e.g., heights) \\ \end{tabular} & \
\begin{tabular}{c} Safe (less need for \\ physical access) \\ \end{tabular} & [72; 113] \\ \hline
\begin{tabular}{c} Real-Time \\ Capability \\ \end{tabular} & No & Yes & [119; 124] \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparative analysis of traditional NDT and IoT-based NDT for port cranes.