Industrial IoT applications refer to the deployment of Internet of Things (IoT) technologies and the utilization of industrial IoT platforms to enhance various aspects of industrial operations. These platforms enable the connection and integration of diverse devices, sensors, and machinery within industrial settings. 

By leveraging real-time data collection and analysis, industrial IoT applications aim to improve production efficiency, enable predictive maintenance, improve safety and security, optimize energy consumption, and more. 

Industrial IoT applications play a crucial role in transforming traditional industries by harnessing the power of connectivity and data-driven decision-making to drive operational excellence.

By connecting legacy/modern, productive/auxiliary machinery, you can obtain a holistic view of your entire factory and access  all the extracted KPIs. This way you can eliminate inefficiencies, unlock new business models and improve the safety of construction sites and factories.

With an industrial IoT app you can increase the efficiency of your production processes and gain valuable insights.This allows you to improve the OEE, accurately monitor product quality, and reduce costs.

With Industrial IoT applications you can monitor all machines and extract consumption data remotely, 24/7. 

Achieving production efficiency with an industrial IoT platform is simple: you can control machine performance in real-time, reduce energy and maintenance costs, minimize downtime and manage maintenance operations. 

You can also calculate the cost and total consumption of your machines, analyze phase imbalance in your cabinets and the electrical connection parameters.

By collecting all the relevant data, you can make informed, data-driven decisions. A suitable industrial IoT application allows you to choose and design the most effective strategies for optimizing your performance. 

Industrial IoT applications can help you to make data-driven decisions, resulting in enhanced production efficiency, increased machinery availability through failure prediction, and reduced operating costs.