Robots: Control using Audinos for several applications in SHM and Railways. 

Our work has encompassed a multidisciplinary approach to developing advanced monitoring and control systems, particularly for applications in Structural Health Monitoring (SHM) and railways. A core component of this work has involved the extensive use of Arduino boards. These versatile microcontrollers have served as the backbone for various projects, providing the processing power and I/O capabilities necessary to interface with sensors and actuators.

We have developed expertise in integrating and utilizing diverse communication modules with Arduino. This includes setting up both wired and wireless communication protocols to enable data transmission from remote sensing nodes to central processing units or user interfaces. The ability to reliably transmit data is crucial for real-time monitoring and control.

A significant effort has been dedicated to developing Arduino applications (sketches). These applications, written in the Arduino IDE, define the logic for data acquisition, sensor control, signal processing, and communication. This involves programming various input/output operations, implementing control algorithms, and managing data flow efficiently within the limited resources of the Arduino platform.

Beyond the embedded programming of Arduino, our work has heavily leveraged Python for various functionalities. Python has been instrumental in developing desktop applications for data visualization, analysis, and post-processing of sensor data collected by Arduino systems. It has also been used for creating user interfaces, managing data storage, and potentially for higher-level control logic or machine learning applications that interact with the Arduino systems.

A specialized area of our development has been creating animations for railway applications. This likely involves using software tools (potentially integrated with Python) to visualize railway operations, sensor data overlays on railway infrastructure, or simulated scenarios. These animations serve as powerful tools for understanding complex data, demonstrating system behavior, or training purposes.

A key focus of our robotic work has been the control of robots using Arduinos for several applications in SHM and Railways. This involves designing and implementing robotic platforms equipped with sensors (e.g., for inspection, defect detection) that are controlled by Arduino boards. Examples could include mobile robots for track inspection, aerial drones for bridge inspection, or fixed robotic manipulators for material handling or localized measurements. The Arduino acts as the brain, interpreting commands and executing precise movements.

The article "Annamdas V. G. M and Soh C. K (2019) A perspective of non-fiber-optical metamaterial and piezoelectric material sensing in automated structural health monitoring" provides a foundational context for our work in SHM. While the article itself focuses on advanced sensing materials (metamaterials and piezoelectrics), it directly supports the rationale behind our efforts in developing automated SHM systems. The integration of such advanced sensing technologies, once matured, would naturally feed into our Arduino-based data acquisition and robotic inspection platforms, further enhancing the capabilities of our SHM solutions. The work on Arduino and communication modules is precisely what would be needed to interface with and extract data from these advanced sensors.

Articles:

Annamdas V. G. M and Soh C. K (2019) A perspective of non-fiber-optical metamaterial and piezoelectric material sensing in automated structural health monitoring, Sensors 19 (7), 1490,  https://www.mdpi.com/1424-8220/19/7/1490