## 3 AIoT Architecture for Structural Testing
### Implementation Methodology  
The process of implementing the AIoT architecture for structural testing involves the efficient integration of sensors, IoT platforms and artificial intelligence algorithms. The proposed methodology not only facilitates real-time monitoring and analysis but also optimizes decision-making processes, increasing safety and efficiency in structural engineering applications. The implementation of the proposed AIoT architecture can be systematized in five key stages:  
1. Capture of requirements. Definition of mechanical load parameters, monitoring variables, measurement accuracy, sampling frequency, and test duration. 2. Design of the AIoT acquisition system. Specification of sensors, actuators, IoT platform, communication QoS, power supply, and system calibration and tuning. 3. Real-time analysis of test data. Implementation of appropriate AI techniques for data preprocessing, model training, validation, and real-time prediction. 4. Leverage the results of the real-time analysis. Execution of test alerts, automated shutdowns, data storage for client access, and offline result interpretation. 5. Delivery of final test results. Provision of test data, applied procedures, test history, and compliance certificates. These stages ease the effective integration of sensors, artificial intelligence algorithms and IoT platforms for real-time structural test monitoring and analysis (Figure 2). This modular and scalable implementation approach can be adapted to different scenarios and test types. The capture of requirements stage begins with the identification of the fundamental structural test parameters. This stage is critical to ensure that the AIoT system meets the specific needs of the specific application. Key structural test characteristics include, among others, the types and levels of mechanical loads to be applied to the test specimen; the load application limits; the variables to be monitored during the test, such as deformations, vibrations, temperature, or applied forces; the accuracy required for the measurements, considering system limitations and test objectives; the sampling frequency needed to capture dynamic phenomena with sufficient resolution; the duration of the test, considering both the continuous monitoring requirements and the specific events to be evaluated. These parameters determine the technical requirements for the subsequent phases of implementation. In the design of the AIoT acquisition system stage, the system is designed to acquire data during the structural test, based on the requirements identified in the previous stage. This stage involves the selection of sensors and actuators that meet the parameters of accuracy, operating range and robustness; the calibration of the sensors to ensure reliable and reproducible measurements; the tuning of the actuators so they can be commanded quickly and accurately; the choice of the IoT hardware platforms, such as microcontrollers and communication equipment, that facilitate the processing and data communication; the configuration of the QoS parameters of the communications system to ensure efficient and secure data transfer; the implementation of a power supply scheme, in order to  
Figure 2: Flowchart of the generic implementation of the proposed AIoT architecture in structural testing. guarantees the continuous operation of the IoT devices, whether by batteries, solar power or other sources. The third stage involves the real-time analysis of the acquired test data. A distinctive feature of the AIoT architecture is the ability to accommodate the processing of artificial intelligence algorithms in order to analyze the data obtained from the test in real time.