Reliable and Proven Industrial IOT Use cases—
Enhance Visibility, Reliability and Efficiency across the Processes
.png)

Electronic Logbook
Replace the traditional paper-based log books with digitized information. Simple and Intuitive GUI to capture the valuable non-automated data in a structured form, manage events, issue instructions and create audit trails. Minimize human errors and improve data reliability for Compliance.

Condition Based Maintenance
Machine or equipment’s data is acquired and monitored on real time basis and rules are applied to find exceptions or thresholds that are exceeded. In case of a deviation, trigger actions in a timely manner. The action could be as simple as an alarm or SMS or email or as advanced as the automatic creation of a maintenance order in an Enterprise Management system.

Predictive Maintenance
Analyze real time data from equipment and devices, detect anomalies send alerts and automatically trigger appropriate maintenance processes. Leverage historical data to recognize patterns and predict failures before they actually happen. Optimize operations and quality with the root cause analysis module and best next action workflow.

Predictive Operations
Build a Smart Factory with horizontal integration of all assets and subsystems of various operations coupled with deep analytics, to improve operational efficiency and quality using AI, machine learning and device connectivity. Save cost and increase Return on Investment with higher asset performance, increased quality and optimized energy consumption.

Utilities & Energy Management
Measure and analyzes Energy consumption and energy quality parameter data e.g power frequency, supply voltage, voltage interruptions etc. to optimize Energy consumption and increase Efficiency. With analytics feature, develop energy consumption patterns, detect abnormality in Consumption and predict future energy needs.

Remote Monitoring
Connect multiple devices and systems through protocols and APIs and monitor the critical assets. Track real time KPIs using custom dashboards that provide performance insights. Configure events and triggers based on deviating sensor values. Leverage historical data to develop custom models, build a foundation for predictive maintenance and explore new revenue streams.