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AutoPi > Blog > Data storytelling with AutoPi

Data storytelling with AutoPi

Updated at 31 Mar, 2022

— Since the beginning of times, we humans has been telling stories to make sense of our world and to share that understanding and knowledge with others.

Data storytelling with AutoPi
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Data storytelling shows up in many places and in many forms, which can confuse some people, so we will help you better understand why it matters, and how the AutoPi TMU device can help you generate all the needed data.

Finally, how you can utilize this data to create a story that helps you take data-driven decision-making.

What is Data storytelling?

Data storytelling is an effective way to put data insights into context and create new knowledge and new decisions or actions.

It is an integrative practice that incorporates the ability to effectively communicate insights from a dataset using narratives and visualizations. It is practiced across many fields and is used to address a variety of challenges. For instance, to communicate the need for optimization in industries with fleets, based on the data.

The story is meant to explain the data and why it matters.

Data is collected and shared to help us see patterns and have insights we wouldn’t otherwise. E.g., you can look at your electric vehicle’s performance to determine how well your vehicle is working.

It’s important to remember, that numbers and data alone are not meaningful to us and needs to be put into context for us to understand it. That is, because we want to use the data to help us make better decision.

Telling a story with data will help your team get from point A to point B.

How to data story with

In this article, you will find out how the AutoPi IoT Platform functions. The prior three steps (data, sorted & arranged and presented visually) are essentially analysis steps and are accomplished by the AutoPi TMU device.

The final step (data with a story) enters the storytelling realm by connecting all the gathered data and visualization in one dashboard, and then tell you through a story how your fleet is doing.

In this workflow, we gather as many data as requested, sort them into priority levels and apply certain criteria to differentiate for optimization.

For the example below, we will assume that the data will be sent to the AutoPi Management Cloud.

To make it short, the AutoPi TMU device is a IoT device that connects to your vehicle through the OBD-II port, and J1939 for trucks. The device is then able to extract all data within the vehicle.

Click here to learn more about

Click here to learn more about the AutoPi TMU device.

Click here to learn more about the AutoPi Management Cloud.

Step 1) Extracting data

Vehicles generate data and AutoPi TMU extracts this data

Every time your vehicle’s engine is turned on, the Controller Area Network communication (CAN bus) system allows the Electronic Control Units (ECUs) to communicate. Depending on the type of vehicle, it can have up to 70 ECUs and each of them needs to be shared with other parts of the network.

E.g., ECUs can be battery, engine control unit, airbags, etc.

Try to look at it this way, the vehicle works as a human body and the nervous system is the CAN bus, the nervous system communicates through the human body to move arms and legs, that is the ECUs.

The communication happens instantly and generates millions and millions of data, also known as Big Data. With an AutoPi TMU device, you will be able to extract (log), all the data that happens on the CAN bus.

Step 2) Sort & arrange the data

The AutoPi TMU device logs all the generated data

The logged data is then time stamped in real-time inside the AutoPi TMU device. However, at this point it's still just a big chunk of numbers, better known as raw data.

Raw data is rather useless to us mere humans. So, once the data has been logged into the device, the device will by default, process the data by sorting, arranging, and filtering the data, in order to transform the raw data into actionable data insights. The sorting and arranging is based on the loggers, that has been set-up in the cloud.

The data will then be sent to AutoPi Management Cloud.

Alternatively, as the owner of the device, you're capable of configurate the device's workflow as you want it. Because the AutoPi TMU device is built on top of the Raspberry Pi, it is essentially a computer by itself.

For more information, you can check out our documentation site on this matter.

Step 3) Visually present the data

The AutoPi Management Cloud transform the data into visualized datasets

With so much information being collected through your vehicle, we must have a way to paint a picture of that data so we can interpret it.

As the vehicle data is logged, sorted, arranged, and filtered in the device and sent to the cloud, you are then fully capable of configuring the cloud to visualize the data through maps, graphs, tables, etc., in any way you want. By visualizing the data, it will give you a clear idea of what the information means by giving it visual context.

Step 4) Explain the data with a story

Fleet managers utilize the data from graphs to optimize fleet performance

Visual contexts are delightful to gaze at and will give you meaning to the data, however, the advantageous lies in connecting each of the visualized data in one spot, and let the data tell you how your fleet is doing with a story.

Through the story, you will get relevant insights into each vehicle in the fleet, and make it easier to identify trends, patterns, and outliers within large data sets.

The AutoPi Management Cloud comes with a comprehensive dashboard that displays a wide range of data. It contains everything from the number of trips each day to the amount of time and distance traveled per car, as well as fuel usage, idle time, and driving behavior.

These insights may be utilized to:

  • Ensure operational efficiency, with the result that your fleet is operating to its fullest potential.

  • Monitor the financial management and understand the total cost of ownership for each vehicle and your fleet’s overall ROI.

  • Employ optimal vehicle health, by incorporating data and best practices into your maintenance program.

  • Discover optimization possibilities, allowing you to make data-driven decisions that boost efficiency while saving money on fuel.

Interested in knowing more? Feel free to contact us on or visit our website

Article by

Philip Hundevad Nymann

Business Developer / Sales

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