Connected Vehicles: Accelerate Automotive Innovation With MongoDB Atlas and AWS

Rahul Khandelwal and Rayed Benbrahim

Capgemini's Trusted Vehicle Solution heralds a new era in driver and fleet management experiences. This innovative platform leverages car-to-cloud connectivity, unlocking a world of possibilities in fleet management, electric vehicle charging, predictive maintenance, payments, navigation, and consumer-facing mobile applications. Bridging the gap between disparate systems, Trusted Vehicle fast-tracks the development of software-defined vehicles and ushers in disruptive connectivity, autonomous driving, shared mobility, and electrification (CASE) technologies.

In this post, we will explore how MongoDB Atlas and AWS work together to power Capgemini's Trusted Vehicle solution.

What is Trusted Vehicle?

Capgemini’s Trusted Vehicle solution accelerates time-to-market with a secure and scalable platform of next-generation driver and fleet-management experiences. Trusted Vehicle excels in fleet management, EV charging, navigation, and more while also accelerating software-defined vehicle development. By seamlessly connecting disparate systems, it paves the way for disruptive advancements in automotive technologies.

AWS for Automotive empowers OEMs, mobility providers, parts suppliers, automotive software companies, and dealerships to effectively utilize AWS, providing them with tailored solutions and capabilities in many areas such as autonomous driving, connected mobility, digital customer engagement, software-defined vehicle, manufacturing, supply chain, product engineering, sustainability, and more.

Based on its cloud mobility solution expertise and immense experience in successfully implementing Trusted Vehicle for its clients, Capgemini has developed repeatable and customizable modules for OEMs and mobility companies to accelerate their connected mobility journey. These quick-start modules can be swiftly customized for any organization by adding capabilities. Here are a few examples of the modules:

  • Diagnostics trouble-code tracker for fleet maintenance that bolsters safety and efficiency

  • Fleet management software with keyless vehicle remote control for convenience and security

  • Predictive maintenance for connected vehicles to detect anomalies and ensure proactive interventions

For automotive OEMs, innovation through digitization of their products and services is of paramount importance. The development of connected and smart vehicles requires cutting-edge technologies. Capgemini recognizes the significance of robust data platforms in shaping the future of connected vehicles. At the core of the Trusted Vehicle solution lies the MongoDB Atlas developer data platform. This strategic partnership and integration ensures that automotive OEMs can harness the power of a modern, scalable, and secure data platform, enabling efficiency, secure and robust connectivity, and seamless user experiences.

Benefits of MongoDB Atlas for Capgemini Trusted Vehicle solution

Faster time-to-market and developer velocity

MongoDB Atlas’ core value proposition is to offer a unified data platform for developers to build applications. With MongoDB Atlas, Capgemini built the core data processing, from sensor data to valuable business insights, with one API.

Limiting the number of infrastructure components helps developers spend less time writing orchestration code and the corresponding automated tests, setting up the infrastructure with all the disaster recovery requirements, and monitoring that stack.

Absolving developers from those responsibilities allows them to deliver more features, bringing business value to the customers rather than spending precious time on technical plumbing.

Cloud agnosticism and customized Trusted Vehicles for customers

MongoDB Atlas is a fully managed database as a service that offers features like multi-cloud clusters, automated data tiering, continuous backups, and many more. With a multi-cloud cluster in MongoDB Atlas, customers can:

  • use data from an application running in a single cloud and analyze that data on another cloud without manually managing data movement.

  • use data stored in different clouds to power a single application.

  • easily migrate an application from one cloud provider to another.

Multi-cloud enables improved governance by accommodating customers who require data to be stored in a specific country for legal or regulatory reasons. It also allows for performance optimization by deploying resources in regions nearest to where users are located.

Implementing Atlas for the Edge

Atlas for the Edge provides a solution that streamlines the management of data generated across various sources at the edge, including connected cars and user applications. Two key components of this solution are Atlas Device Sync and SDKs. Together, they provide a fully managed backend that facilitates secure data synchronization between devices and the cloud. This also includes out-of-the-box network handling, conflict resolution, authentication, and permissions.

To successfully implement MongoDB’s Atlas for the Edge solution, AWS Greengrass was used to facilitate over-the-air updates and manage the software deployment onto the vehicles, while Device Sync and SDKs handled the transmission of data from the car back to the cloud. Greengrass allows executing code through lambda functions, utilizing data received via MQTT or from the connected device. Device SDKs, however, overcome AWS Lambda's temporary file system storage limitation by offering a significantly enhanced data storage capacity. Greengrass can now locally store the telematics data in the database provided by the SDKs. Therefore, the data will be stored even if the device is offline. Following the restoration of network connectivity, the locally stored telematics data can be synchronized with the MongoDB Atlas cluster. The storage capabilities of the Device SDKs help ensure that processes run smoothly and continuously.

Syncing telemetry data to Atlas

Dynamic queries with flexible sync

Device Sync lets developers control exactly what data moves between their client(s) and the cloud. This is made possible by flexible sync, a configuration that allows for the definition of a query in the client and synchronization of only the objects that match the query. These dynamic queries can be executed based on user inputs, eliminating developers' need to discern which query parameters to assign to an endpoint. Moreover, with Device SDKs, developers can integrate seamlessly with their chosen platform, directly interfacing with its native querying system. This synergy streamlines the development process for enhanced efficiency.

Data ingest for IoT

Data ingest, a sync configuration for applications with heavy client-side insert-only workloads facilitates seamless data streaming from the Trusted Vehicle software to a flexible sync-enabled app. This unidirectional data sync is useful in IoT applications, like when a weather sensor transmits data to the cloud. In the case of vehicles, information specific to each car — such as speed, tire pressure, and oil temperature — is transmitted to the cloud. Data ingest is also helpful in writing other types of immutable data where conflict resolution is unnecessary. This includes tasks like generating invoices through a retail application or logging events in an application.

Data lifecycle management with Device Sync

Atlas Device Sync completely manages the lifecycle of this data. Data ingest and flexible sync handles the writing and synchronization processes, including removing data that is no longer needed from devices. On-device storage, network handling, and conflict resolution ensure that clients retain data even when offline. Once reconnected to a network, data seamlessly and automatically synchronizes with MongoDB Atlas.

Processing and accessing data with aggregation pipelines

The raw data gathered from individual vehicles, like metrics such as speed, direction, and tire pressure, lacks meaningful interpretation on its own. MongoDB’s aggregation pipeline transforms these individual records into contextualized information like driver profiles, usage patterns, trip specifics, and more, yielding actionable insights. For optimal storage and performance efficiency, MongoDB automatically archives individual records after they are processed, ensuring they remain accessible for future retrieval.

Overview of Atlas for the Edge - AWS architecture

The implementation of Atlas for the Edge for Trusted Vehicle’s solution shifts the responsibility of collecting, syncing, and processing data from AWS components to Atlas Device Sync and SDKs.

  1. The Device SDK for Node.js is used in the lambda function, which runs as soon as the Greengrass core device boots up and stores the vehicle telematics data every two seconds in the Realm DB.

  2. Using flexible sync with data ingests, the vehicle will automatically sync the telemetry data from the device to the MongoDB Atlas cluster on AWS into a time series collection.

  3. An aggregated document representing the vehicle’s or drivers’ data can be computed with the aggregation pipeline and stored in a collection or as a materialized view and accessed via an API endpoint.

  4. Historical telemetric data that gets cold can be automatically archived into cold storage using Online Archive, native to the time series collection. This archived data is still accessible if needed on a specific API endpoint using the federated query feature of MongoDB Atlas.

Trusted Vehicle with AWS and MongoDB Atlas

MongoDB Atlas offers a trifecta of benefits when utilized within Capgemini's Trusted Vehicle solution. First, it accelerates time-to-market and enhances developer efficiency by streamlining and simplifying the technology stack. Second, MongoDB Atlas proves to be more cost-effective as the fleet of vehicles expands. The reduction in cost per vehicle, especially as scale reaches 1,000 and 10,000, results in a substantial decrease in the total cost of ownership. Keeping efficiencies of scale in mind, the OEMs running millions of cars on the road will certainly benefit from this solution. Third, MongoDB's cloud-agnostic components pave the way for a more flexible and adaptable implementation, breaking free from the constraints of specific cloud environments. Ultimately, MongoDB Atlas not only expedites development and reduces costs but also provides a more versatile solution catering to a wider range of clients.

For more information on our partnership with Capgemini, please visit our partner webpage. Additionally, visit our MongoDB in Manufacturing and Automotive page to understand our value proposition for the automotive industry and take a look at our connected vehicle solution video.