Analyze React Optimize



Condition monitors are mounted on the asset in scope and collect high-precision vibration and temperature measurements which are sent to the cloud.


Sensor data is analyzed by the gateway and the cloud platform using algorithms powered by AI and machine learning to determine asset health.

React / Visualize

Using our platform, data can be visualized and status reports from each asset can be reviewed. Alarms are raised automatically if the assets pattern changes outside of the normal operating scope.


BSS Analytics is an advanced platform for condition monitoring of rotating machine components, which provides both a simple overview and in-depth understanding of data.

Product description
BSS Analytics ensures lower costs, less risk, and increased efficiency by:

    • Increasing the uptime of machines
    • Using pattern recognition to predict errors
    • Reducing direct and indirect operating costs
    • Streamlining capacity management
    • Providing insightful risk management
    • Remote control of critical functions
    • Ensuring quality control in machines with fine tolerances

BSS Analytics is a standalone system that can be integrated with existing data collection devices, e.g. data from a machine condition monitor. BSS Analytics is connected to BSS Gateway and BSS IoT Sensor.


User interface with integrated data analytics, and integration to third party tools and programming frameworks that allows the user to use his favorite tool for data analytics.


Rich library of statistical tools and machine learning algorithms for predictive maintenance, data analytics, and automation.


Workflow and data automation combine data collection with statistical tools and machine learning algorithms, for secure fully automated surveillance of your assets.


Alert functionalities with configuring alarms on email, event logs, or to third-party SCADA systems and data-management platforms using HTTPS.

Sensor configuration

Userinterface that allows to set up gateways and sensors in minutes from a single endpoint and configure data-automation workflow in a few steps.


Timeseries database for storage of sensor data for training purposes and data analytics in case of failure.



Vibration and temperature measurements are collected using high-precision sensors and condition-monitors mounted on the asset in scope.


Sensor data is analyzed by the gateway and the cloud platform. When a fault has been detected, an alarm is raised to the operations team.


The signal is analyzed in collaboration with a highly specialized team through the platform’s UI or by third-party software with integration through a generic rest-API.


Eliminate unplanned downtime

Your assets are monitored twenty-four-seven by high precision vibration sensors combined with advanced AI and data automation that notifies you when a defect has been detected.

Optimize your assets

Optimize the performance of your assets with data analytics. Identify unused potential using vibration analysis and compare the performance of your assets across facilities as well as wear over time.

Condition based maintenance

Transform your maintenance from time-based to condition-based maintenance and reduce costs due to lengthy downtime and failures caused by reassembling healthy parts of your system.


Use data analytics to identify vulnerabilities in your production line and eliminate risk before it causes breakdown and expensive downtime.


Optimize the maintenance process by collaborating remotely where teams in different locations can collaborate on the same data and make a better decision together.


Achieve consistent surveillance of your assets every time. With automatic machine health analysis and fault detection, you are sure to get a uniform and reliable performance report every time.


BSS Analytics is a non-invasive solution that gives you total control over your data. You can either use our AI-enabled predictive maintenance algorithms or extract the data from the BSS Analytics platform using our API. The platform offers services like automated intelligence for maintenance (AiM), Remote management of Gateways and sensors, event management, error logging, data analytics, AI functions, data automation and various types of alerts.