Macroscale Molecular Communication in IoT-based Pipeline Inspection and Monitoring Applications: Preliminary Experiment and Mathematical Model

Today, pipeline networks serve as critical infrastructure for transporting materials such as water, gas, and oil. Modern technologies such as the Internet of Things (IoT), sensor nodes, and inspection robots enable efficient pipeline monitoring and inspection. They can help detect and monitor various conditions and defects in pipelines such as cracks, corrosion, leakage, pressure, flow, and temperature. Since most pipelines are buried underground, wireless communication links suffer from significant attenuation and noise due to harsh environmental conditions. In such systems, communication links are required between the sensor nodes as well as between the external control/monitoring unit or sensor node and the inspection robot inside the pipeline. In this paper, we propose a macroscale molecular communication (MC) system in the IoT-based pipeline inspection and monitoring networks to address this challenge. We develop a mathematical model and implement a preliminary experimental testbed to validate the system and demonstrate its feasibility by transmitting and reconstructing binary sequences using volatile organic compound (VOC) as an information signal. We examined the impact of various system parameters including airflow carrier velocity, released VOC velocity, emission duration, and bit duration. Results indicate that these parameters significantly influence the received molecular signal, emphasizing the need for optimal configuration. This work serves as a preliminary step for further research on the application of MC in IoT-based pipeline inspection and monitoring systems.