Industrial IoT (IIoT) is one of the fastest and largest topic for the application of IoT concept for industry to increase the usage of process data. Tremendous number of connected machines with PLC systems create a big comparative advantage for the companies that are investing for the future. Industry 4.0 becomes a major factor for the manufacturing companies which bring factory automation on the center of the circle.
"As the IoT becomes prevalent in industry and manufacturing, these worlds will combine especially with predictive maintenance from thousands of factory and production machines to deliver an unprecedented amount of data to private and public cloud infrastructure. "
Internet of Things for Architects by Lea Perry
Data storage is a critical process for the safety and data processing efficiency. This is why we are working with the best cloud data warehouse providers.
IIoT technologies need a different approach to data storage perspective. It is obvious that without the data storage technologies IIoT systems can not exist. We are using relational and non-relational database systems for the best system performance.
Data analytics and visualization is very critical to understand the relation between the thousands of sensors which are collected by the IIoT systems. Clarification of the sensor data is directly related with the decision that have been made by the system.
We are analyzing the patterns on the data sets where the whole system interacts with each other. Understanding the paths tells us the secrets about the machines. Our data scientist team will add value to your production with analytical methods.
On the other hand data visualization is the key to success for companies to see the real time performance values of their production.
IoT generates an enormous amount of data; presently,
90% of the data generated isn't even captured, and out of the 10% that is captured, most is
time-dependent and loses its value within milliseconds. Manually monitoring this data continuously is both cumbersome and expensive. This necessitates a way to intelligently
analyze and gain insight from this data; the tools and models of AI provide us with a way
to do exactly this with minimum human intervention. The major focus will be on understanding the various AI models and techniques that can be applied to IoT data. We'll be using both machine learning (ML) and DL algorithms.
We are improving your production efficiency with our Process Learning and Predictive Maintenance tools. Teaching your machines to optimize themselves.
We are providing below solutions for industrial IoT applications:
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