Alset is a multi$-$national top end electric vehicle manufacturer and a market leader in

providing autonomous driving features. No other car manufacturer in the world is

anywhere near Alset in the autonomous driving space. Being at the forefront comes

with its challenges.

Alset$$s top management heard about its software not being able to differentiate

between $2-$wheelers, i$.$e$.,$ motorcycles and bicycles. Which caused an erroneous speed

estimation of those $2-$wheelers and led to some non$-$fatal accidents. The organization

wants to avoid this. For which, it needs a lot of data to train the model. But it$$s not

storing any data from their cars. Some of the users agreed to share the image$/$video data

from their cars but Alset doesn$$t have a data collection or storage or processing

methodology in place because all the processing thus far has been on the on$-$board units

$($OBUs$).$ To solve this the firm consults and gives you the responsibility to design their

pipeline. They don$$t have any historical data on any kind of $2-$wheelers.

How do you approach this problem holistically using both big data and business

analytics concepts? Explain the big data component for storage and processing, and

analytics component of approaching this use case and what would you do in each of the

stages. Goal is to help company collect, store, process data and better predict and

classify between different kinds of $2-$wheelers.