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Predict it

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Details
It requires a lot of data to know your assets and predict their maintenance. We are able to predict these needs. We collect the data by adding IoT (Internet of Things) sensors to equipment, which gather large amounts of data. The data is put into our Proactive Maintenance solution that is specifically built to analyse multiple, complex patterns and trends
Release notes ()
Key benefits
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  • Proactive maintenance with IoT and AI

  • Decrease downtime

  • Recognize trends and patterns

  • Minimize unneeded maintenance

  • Optimize the usage of resources

  • Lower costs and improve predictability


Problems Addressed / Key Features
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Regardless of the high volume of assets and numerous locations, the solution will do the job in a matter of seconds. 

With the newest Machine Learning and AI algorithms, all the gathered data is presented in a user friendly dashboard. This dashboard gives you input on usage, downtime, next maintenance term and can be customized to your specific needs and requests.

The solution allows for easy integration with any other running application in your company. Ultimately, allowing you to minimize downtime, optimize your resources, lower your costs and improve your performance.

Technical details
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  • Microservice architecture

    • Loosely coupled

    • Independently deployable

    • Organised around predictive capabilities

  • Integration via REST API

  • Incorporates IoT and machine learning

  • Optimal maintenance based on AI and self-learning algorithms

  • Uses Google Maps, Leaflet/OpenStreetMap/Mapbox for routing and viewing asset locations (e.g. current location of vehicles etc.).

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Tags
Transportation & Logistics
Assets & inventory management