Innovative real-time pressure monitoring system utilizing Raspberry Pi and IMU for industrial application

Abstract

Abstract This paper presents an innovative IoT-enabled solution for the real-time digitization of traditional chart recorders using a Raspberry Pi and the MPU6050 accelerometer. The proposed system harnesses modern IoT communication protocols to enable accurate pressure monitoring, remote data access, and real-time analysis, addressing the limitations of conventional paper-based systems. A key contribution of this work is the development of the first mathematical model for translating mechanical needle displacement in chart recorders into electrical signals, offering a robust theoretical foundation for precise signal conversion. Experimental results validate the system’s ability to accurately capture rapid pressure changes, demonstrating its suitability for demanding industrial applications, particularly in the oil and gas sector. The system’s performance was evaluated in various scenarios, showcasing its resilience to environmental noise, effective real-time data transmission (with latency as low as 130 ms), and significant noise reduction (up to 95%) through advanced filtering techniques. Furthermore, the system demonstrated a high level of accuracy in pressure measurements, with a maximum error of just 0.3 KPSI after filtering, confirming its reliability for precision monitoring. In addition to its technical capabilities, the proposed system supports paperless operation, significantly reducing operational costs and enhancing environmental sustainability. By eliminating the need for consumables such as paper and ink, the system offers a cost-effective and scalable solution. These results underscore the transformative potential of the system in modernizing industrial pressure monitoring, offering a scalable, precise, and environmentally sustainable alternative to traditional chart recorders. This work also lays the groundwork for future advancements in IoT-based sensing, predictive maintenance, and automation technologies in industrial settings.