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SMART ANALYTICS

Mobility Atlas

Cars as mobility sensors

Drivers’ cluster analysis

This telematics Atlas is the result of vehicle flow analysis, for both incoming and outgoing traffic, within a specific geographic area. These vehicles are tracked in relation to the business goal that a company wishes to achieve.

Understanding how to analyze a single driver behaviour may pass through a cluster analysis: cars as “mobility sensors” play a crucial role in the IoT of the city. They are adaptable sensors, right where there’s a need to survey a mobility phenomenon. The adaptive concept is related to traffic, which activates data collection. In some sense it is like cars were leaving tracks by themselves, producing “digital crumbs”.

Drivers’ behaviour under a microscope

Mobility data represents society-wide proxies of human mobile activities. It’s a social microscope of individual, collective, and global behaviours, where data achieves a different perspective, from individual to collective mobility towards the smart cities, e.g., to understand how much traffic is possible to reduce with a car sharing service.

This type of data generated from a Mobility Atlas is crucial for utilities, mobility sharing operators (in order to know where to place the vehicles station), and to overlap different maps of a city area.

Smart Analytics is also

Analytics as a Service

The ability to influence the value chain concerning data management and to adapt them to specific market needs.

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Geographic Vehicle Flows

The knowledge of traffic status, based on real-time traffic and forecasting, is fundamental to implement the urban mobility policies.

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Engine Data Reporting

A technology that allows the collection of useful data from the ODB car port, through an easy to install device, to be used in Fleet Management and Vehicle Sharing realms.

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Vehicle Utilization Data

One of the most important services for car makers. This data, linked to the driving style, provides the insight needed for predictive maintenance.

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Data Driven Score

This risk scoring is calculated connecting the driving behaviour on a sample related to a crash index amongst the same sample, resulting in a risk index.

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