Cognecto's solution for shift-wise smart asset allocation involves the use of its data science model and an innovative user experience. With the help of Cognecto's telematics devices and sensors, real-time data is collected on the location, status, and utilization of all assets.

This data is then processed by Cognecto's data science engine, which uses machine learning algorithms to predict asset requirements for each shift. The predictive model considers various factors, including asset availability, utilization patterns, and maintenance schedules, to allocate the right assets to the right shift at the right time.

To simplify the allocation process, Cognecto has developed an intuitive user interface that provides a single view of all assets and their availability. Shift managers can easily view the status of all assets in real-time, including their location, utilization, and maintenance schedule. They can then make informed decisions on asset allocation for their shift.

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