AUTOMATED SYSTEM FOR MONITORING THE ACCURACY OF TECHNOLOGICAL MEASUREMENTS IN THE IOT ENVIRONMENT

Abstract

The architecture of an IoT system for monitoring measurement accuracy in production processes has been developed. Mechanisms for automatic calibration verification and sensor status diagnostics have been implemented. An analytical model of the impact of data transmission errors over wireless networks on measurement results has been presented. Experimental results demonstrate an increase in product quality control reliability to 98%. The system is based on a distributed architecture using cloud services for centralised data processing. To ensure the integrity and reliability of information, algorithms for detecting and compensating for measurement anomalies have been implemented. A comparative analysis of the effectiveness of the proposed approach with traditional accuracy control methods has been carried out. The results confirm the feasibility of integrating intelligent sensors into production lines. The proposed system has a modular structure that provides scalability and flexibility when expanding functionality. The developed solutions can be applied in industries with increased requirements for metrological reliability, in particular in mechanical engineering and electronics.