Automotive Data Transformer

During my internship at a company providing automation tools and database platforms for Eicher automobiles, I worked on a project integrating Bosch Automotive Data Transformer for automation and testing. Eicher automobiles is an Indian manufacturer of tractors, trucks, cars, and motorbikes. The project involved using Bosch Automotive Data Transformer to capture vehicle details and monitor vehicle status. Several parts were covered by Bosch Automotive Data Transformer during my internship period, including radar, GPS, steering angle, vehicle wheel alignment, and RPM.

The biggest advantage of Bosch Automotive Data Transformer is that it provides the necessary information about vehicles for security and health purposes. When testing vehicles in the production line or when users deploy vehicles in the garage, engineers can obtain better information through the tool. Bosch Automotive Data Transformer extracts data from the vehicle's motherboard and provides necessary data to the garage manager, enabling proper repairs or helping manufacturers produce more efficient products.

Bosch Automotive Data Transformer is not ETL friendly. Most of the integration of this tool is AWS-centric, so if we are using Google Workspaces, we have to purchase AWS subscriptions as well. Additionally, for data generation, it only supports MDF file formats, so we need to use a converter and a specific Bosch Automotive Data Transformer feature to convert to the desired JSON format.

The installation process is quite IoT friendly, but I would say it is not so simple. Bosch Automotive Data Transformer provides many features around the APIs and integrates easily across service providers and vehicle projects. It is not overly complex, but it is not beginner-friendly.

I started using Bosch Automotive Data Transformer around two years back.

Bosch Automotive Data Transformer is quite stable, with a stability rate around 99%. It builds its environment around a few features and services, and it works well with them, such as AWS Cloud and pipelines. The integration functions effectively due to the closed nature of its environment.

Bosch Automotive Data Transformer is highly scalable since it provides several services to connect with multiple software solutions, making it quite scalable.

I implemented the interoperability feature with IT infrastructure, but I have not used the tool extensively. For the implementation purpose, I only used it sparingly.

I can approximately quantify that it saves around 20 to 30% of time and money, as it provides useful data from the ESP of the vehicles and improves the efficiency of the working methods of the organization.

Regarding the price, I believe it is only available on the AWS marketplace. I do not have detailed information because the third-party company has purchased it, and I have not looked into the pricing of this product as it falls outside my scope.

Regarding real-time data processing, when the system generates data, mechanical sensors generate it in raw form. Bosch Automotive Data Transformer converts the data into a human-readable or machine-readable form, such as converting MF, NDF, and MDF files to CSV or JSON files. These converted signals are used for computer-readable and usable formats.

Bosch Automotive Data Transformer helps identify data patterns as it tracks individual patterns regarding the vehicle's behavior over certain time periods or in certain scenarios, such as engine backfiring or incorrect wheel alignment. These issues are automatically detected through the data, and if something is missing, the system automatically notifies the user that something is wrong with the vehicle.

I would agree that the solution is worth buying, especially for customers with large vehicle facilities, as it is very helpful for users. I would rate this product an 8 out of 10.