- This usecase is to analyse various parameter of a truck fleet.
- Each truck has been equipped to log location and event data.
- These events are streamed back to a datacenter where we will be processing the data.
- The company wants to use this data to better understand risk.
- Collected geo-location and truck data has been provided.
- Truck data is small and can be stored in RDBMS – to be imported from sqoop.
- Geo-location data will be stored on HDFS
- Load the captured sensor data into Hadoop (HDFS)
- Load truck data from RDBMS to HDFS/Hive
- Run Hive, Pig scripts that compute truck mileage and driver risk factor.
- Access the refined sensor data with Microsoft Excel
- Visualize the sensor data using Excel Power View / Pivot Table /Graphs.
The business objective is to better understand the risk the company is under from fatigue of drivers, over-used trucks, and the impact of various trucking events on risk.