Machine monitoring

Mirai4Machine is Miraitek' tool for data collection and remote monitoring of industrial machinery. Designed to be easily integrated with assets of different type and age, Mirai4Machine is safe, scalable and extremely flexible.

Mirai4Machine enables machine to machine communications and provides real time information about machine's status to the user.

Mirai4Machine is a web application: alerts can be shown through browsers from every device (e.g. smartwatches, laptops, tablets, smartphones) connected to the internet.

Mirai4Machine allows extremely precise monitoring of faults, alarms, stops: events are communicated in real time to the operator who is able to intervene remotely, avoiding losses and costs of non-production due to prolonged machine stops.


Machine's operating data collection

Real time display of machine's status. The dashboards are set up according to the user needs.

Real time notifications of events, such as alarms and stops.

Access and visualization of historical data about machine status.

Analysis of historical data to realize predictive maintenance.


Mirai4Machine collects real time operative data of machines on production and displays them through dynamic dashboards, set up according to the user needs (operator, factory manager, maintenance technician etc). It allows the user to export reports in .PDF and .xls format.

As a modular system, Mirai4Machine offers optional modules for historical data analysis: it is possible to obtain performance indicators (plant availability, efficiency and production quality) constantly updated. OEE can be calculated as well as machineries residual life.

Mirai4Machine can be integrated in a scalable way on different machines, even if managed by diverse controllers; Mirai4Machine communicates with machines with standard protocols such as OPC-UA; data are sent via MQTT protocol.

Mirai4Machine is flexible and is designed to be quickly deployed: it is possible to set the system up in a few days.







Designed to monitor machines different by type and age. Machine's operating data are collected through the main communication protocols.

Data are storaged on local or cloud servers; users can acces the information from any device connected to the web.

Different parameters can be monitored for each machine.


Data are presented through dynamic dashboards configured according to the user (operator, maintainer, production manager, CEO).

Each user is identified by credentials that provide access only to the information allowed.