TESEIN

The project involves developing an advanced IIoT and Artificial Intelligence solution for Tesein, designed to optimize the monitoring and maintenance of its industrial fire control systems. By integrating a data concentrator into the OT network and a cloud platform, the system enables continuous monitoring and early detection of operational anomalies through AI models trained on historical data. This proactive architecture not only automates decision-making and significantly reduces costs associated with false alarms and unnecessary deployments but also offers a scalable and efficient prototype capable of improving technical reliability across multiple installations.

Objectives:

• Technology Consulting: Identify and evaluate the most advanced IIoT monitoring and Artificial Intelligence techniques, selecting those with the greatest potential to optimize industrial fire control systems.
• IoT Ingestion Module: Develop a data collection component that ensures efficient, low-latency communication, enabling the ingestion and standardization of signals from protection control panels.
• Predictive Analytics and Anomaly Detection Engine: Implement Deep Learning algorithms and time series analysis for failure prediction and the identification of atypical behavior.
• Data Analysis and User Interface: Validate the quality of industrial data to ensure model reliability and deploy a web application that facilitates continuous monitoring.