Multi-agent System for Monitoring Temperature in Sensing Surfaces including Hard and Soft Sensors

In the digital transformation era, the collection of data assumes a crucial relevance. In some applications, the use of real sensors to measure the target parameters is constrained by technical or economical limitations. In such situations, it is required to use alternative techniques based on soft sensors that acquire data by estimating the measurement of a variable through the correlation of the data acquired by the neighbouring sensors. However, the co-existence of real and soft sensors requires a computational infra-structure that integrates these heterogeneous data sources and supports the synchronisation of the monitoring system based on the inputs of different measurement nodes. Multi-agent systems provide this distributed infra-structure for the data collection, ensuring modularity, scalability and reconfigurability capabilities. This paper introduces a multi-agent system approach to create a modular and scalable sensing system, based on a diversity of real and soft sensors, to support the monitoring of temperature in thin-film sensing surfaces. The proposed approach was experimentally tested in a plastic injection process, presenting promising results in terms of accuracy and response time, and allowing to obtain more sampling points through the use of computational techniques to complement the real data.