Rationale for the Applicability of the PULSE Data Transfer Protocol for Use in Predictive Diagnostic Systems for Complex Technical Equipment

The article considers modern tasks of collecting and interpreting data on the state of technical equipment, prospects for integrating various types of sensors and protocols into a single information network within the framework of the Internet of Things (IoT) and Industrial Internet of Things (IIoT) technologies, as well as features of using predictive analytics methods to ensure operating regulations based on the actual state. The key technical difficulties associated with differences in polling speed, data volumes and protocol incompatibility are presented. The developed Pulse protocol and the Signalogic platform are described, providing efficient data processing, process automation and the ability to create a digital layer of the enterprise. The results of comparative tests of the performance of the Pulse protocol with MQTT are presented, demonstrating its superiority in signal processing speed. Examples of successful application of the developed solutions in industry are considered, including control systems for mining and processing equipment, as well as hazardous waste disposal. Particular attention is paid to the potential of predictive analytics in IoT and IIoT for predicting malfunctions, optimizing production processes and increasing equipment reliability. The paper describes the prospects for using machine learning technologies, real-time data analysis, and virtual stands for developing and testing systems. The paper highlights the importance of an interdisciplinary approach for the further development of IoT integration technologies that combine analytical, UX design, and engineering solutions.