Big Data Industry 4.0

Optimize production processes through Big Data

The Big Data and Industry 4.0 solutions offered by DataRiver are based on Web and Mobile platforms that exploit the most advanced technologies in the fields of Industrial IoT, Big Data, Artificial Intelligence (AI) and Machine Learning to:
• Ensure the efficient collection and management of Big Data generated by sensor networks and machines
• Enable continuous monitoring of production lines and warehouses
• Provide real-time analysis of production performance and product quality
• Learn from experience and implement preventive maintenance policies, optimize production processes and reduce energy consumption

Who is it for?

Ceramic, Mechanical, Logistics, Farmaceutical and Biomedical sectors

DataRiver’s Big Data and Industry 4.0 solutions enable Production Managers, Logistics Managers, Quality Managers and Security Officers of client companies to achieve the following competitive advantages:
• Developing Industry 4.0 innovative products and services to be supplied to the market
• Improving the quality of products and production processes by integrating and analyzing Big Data produced by machines
• Optimizing maintenance services to customers through timely alarms on  the operating state of machines
• Reducing production costs by reducing failures and unexpected malfunctions
• Optimizing energy consumption and reducing production costs thanks to the implementation of “energy saving” policies

Automated data collection

Big Data Integration

Automated collection and efficient management of Big Data from machines, sensor networks, mobile devices, and integration with company information systems (ERP, DW, WMS, MES) as well as data sources external to the company.


Continuous monitoring

Real time analysis

Continuous monitoring of performance in production lines, warehouses and product quality.
Real time analysis of operating parameters of machines for the prompt generation of alarms and notifications to the supervisors.


Big Data Analysis

Machine Learning Algorithms

Advanced analysis of the historical data of production processes using Machine Learning algorithms to learn from experience, implement preventive maintenance policies, improve both production lines efficiency and product quality, optimize energy consumption and reduce production costs.



Case studies


Smart Mould: an Industry 4.0 web platform for collecting, analysing and monitoring ceramic moulds


Cyber ​​Doctor: an Industry 4.0 web platform for the automation and monitoring of tests in the production of dialysis machines


Cosmoline Monitor: an Industry 4.0 web platform for monitoring and preventive maintenance of cosmetic machines


i-Tile Analytics: an Industry 4.0 web platform to optimize warehouse management and freight transfer flows

Engineering Company

Smart Tool: Industry 4.0 web platform for remote monitoring of devices installed on mechanical production lines (Smart Tool)

Engineering Company

Energy Monitor / e-Maintenance: Industry 4.0 web platform for monitoring energy consumption and for preventive maintenance of production lines



IoT platform for the optimization of production processes, through the analysis of Big Data generated by sensors and machines


MOMIS enables the integration of Big Data from machines, sensors and mobile devices with corporate information systems and data sources external to the company


Web and Mobile application for real-time monitoring of machines and advanced analysis of production processes through Machine Learning algorithms