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Truck and Driver data can be analyzed for prediction

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30 Oct 2019CPOL 2.1K  
Describes how HANA and SageMaker can be used to analyze the truck and driver data for ML predictions

This article is part of the Cloud AI Challenge with SAP HANA and Amazon SageMaker. This entry is not meant to be a full article - it's purely just an outline of an idea - and will be removed once the contest has concluded.

Introduction

This article explains on how the truck and driver information can be stored as ML model and can be used for analysis and predictions

Topic

This idea can be useful for organizations that do delivery using trucks.  We can store the truck location information and driver mileage data and use the charting capabilities of HANA and SageMaker to come up with statistics and predictions

Data structures

Truck location data can have the following fields for example:

Truckid, DriverId, Latitude, Longitude, Event, Velocity

Driver data can have the following fields:

DriverId, TotalMilesdriven

 

Then we can see who is the most risky driver and most safe driver by using the above data.  Most risky could be the drivers who have more number of abnormal events per miles driven and safe driver would have the less

abnormal events.

Points of Interest

SAP HANA and Amazon SageMaker can be used to build in the data models and charts for the above.

History

Keep a running update of any changes or improvements you've made here.

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


Written By
Architect Aspire Systems India(Pvt) Ltd
India India
Technical expertise in working with microsoft technologies such as VC++, C#, ASP.NET, SQL Server, SharePoint, BizTalk. Currently working in middleware tools such as: Informatica Cloud, Mule Soft, Dell Boomi

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