Predictive maintenance

Predictive maintenance is a technique used in companies and factories that employ IoT sensors and systems to collect real-time data from their machines and devices. This allows them to remotely monitor operational processes or make predictions about future events, thus contributing to optimization and efficiency. Opposite to this are the not data-driven companies and factories that follow a predefined maintenance schedule (not knowing when it is actually needed) in the hopes of preventing malfunctions. This leaves them at a disadvantage compared to their counterparts who will not suffer from inefficiencies and costly equipment failures.

Use cases

These use cases highlight the ways in which IoT helps companies gain insight into the conditions and performance of their machines and become data driven.

Other IoT-solutions

Asset tracking

Monitor and track the exact location, status, fuel consumption and other relevant information of your assets.

Energy management

Gain insight into energy usage by collecting real-time data and optimizing usage accordingly.

Wearables

Continuously monitor patients’ health, and ensure the safety of soldiers, firefighters, industrial workers, and more.

Condition monitoring

Measure parameters and monitor performance to detect whether equipment operates at its full potential.

Environmental monitoring

Reduce emissions and minimize your carbon footprint to achieve your sustainability goals.