In immediately’s period of AI, accelerated innovation is an ever-present problem for companies. They’re concurrently going through finances and time-to-market constraints whereas buyer expectations proceed to mature and evolve, significantly in automotive, mobility, and transportation. The correct know-how to face these challenges should drive transformation and ship extra worth in much less time.

To help companies in assembly these objectives, Microsoft introduced three mobility reference architectures at CES 2023. In 2024, we’re including 4 new reference architectures to our {industry} portfolio. These new sources assist our companion ecosystem help their prospects in driving the way forward for mobility throughout analysis and growth, manufacturing, provide chain and logistics, advertising and marketing, gross sales, and aftersales.

Microsoft mobility documentation

Take advantage of mobility with docs and supported reference architectures

Microsoft reference architectures for mobility

• Software program outlined automobile toolchain ^new
• Mobility Copilot ^new
• Azure Innovation Accelerator ^new
• Autonomous automobile operations
• Related fleets
• Unified view of the client ^new
• Digital promoting

Microsoft reference architectures are designed to supply construction and steerage for challenge managers, enterprise architects, and IT managers to ship agile enterprise outcomes. Options using the mobility {industry} reference architectures can be found by means of certified companions and Microsoft {industry} options.

The software program outlined automobile (SDV) toolchain reference structure permits a contemporary cloud-native software program growth toolchain leveraging robust developer tooling providers with further performance particular to automotive. The reference structure covers steady growth, testing, and supply of high-quality software program.

This plug-and-play method supplies the next advantages:

• Reduces the time to onboard new builders and will increase code high quality utilizing generative AI.
• Accelerates growth, testing, and validation of automotive software program by shifting left—testing earlier and extra usually within the growth course of to enhance software program high quality and growth pace.
• Reduces reliance on in-vehicle silicon with extremely configurable and versatile digital digital management unit (ECU) and virtualized {hardware} within the loop (HiL) environments on Microsoft Azure.
• Helps compatibility with edge and in-vehicle silicon by providing equal compute on Azure.
• Helps the validation course of by having a typical infrastructure for deploying software program artifacts from verification by means of software-in-the-loop (SiL) to check fleets and accumulating “fascinating information” to drive adjustments to the software program.

The SDV reference structure consists of the next parts:

• Improvement tooling utilizing confirmed Microsoft instruments to extend developer productiveness and collaboration resembling GitHub, GitHub Copilot, Microsoft Dev Field, and Visible Studio Code. These instruments are extensible with automotive-specific performance from companions.
• The SDV growth, validation, and integration reference structure supplies orchestration providers that permit you to handle deployment environments and goal configurations to speed up your testing and verification on digital ECU and digital HiL options within the cloud.
• Azure providers present foundational capabilities, resembling deployment environments, compute virtualization, and information storage. Microsoft Material supplies information and analytics providers.
• Azure networking supplies connectivity to on-premises, HiL validation environments.
• The Azure and GitHub marketplaces simplify integration of companion choices for tooling and digital photographs.

Mobility Copilot reference structure

The Mobility Copilot reference structure permits varied use circumstances throughout the worth chain to extend productiveness, unleash creativity, and drive innovation with AI. The structure helps eventualities in analysis and growth, manufacturing, advertising and marketing and gross sales, in-vehicle providers, and after-sales or restore with leading edge structure constructed on the most recent AI fashions with various UX paradigms for optimum buyer and worker journeys.

• Copilots for engineering necessities: AI-based assistant to empower engineers to optimize automobile efficiency and design from aerodynamics and gasoline effectivity to security and aesthetics.
• Copilots for manufacturing high quality and effectivity: AI-based assistant that will increase manufacturing effectivity by analyzing high quality information from growth, buyer expertise, manufacturing, and different sources to detect high quality points.
• Digital buyer assistant: Conversational engagement for advertising and marketing, gross sales, and customer support channels to reply product-or-concern-related questions, qualify leads, drive gross sales, and enhance effectivity by means of automation.
• Onboard AI assistant: In-vehicle voice assistants to enhance pure language understanding and increase the vary of driver and operation interplay.
• Copilots for automobile diagnostics and restore: AI assistant for automotive restore workshops to enhance automobile diagnostics, streamline upkeep duties, and supply real-time insights to mechanics.

Mobility Copilots allow the next distinctive worth propositions:

• Finest-in-class AI fashions: Multi-modal enterprise-grade fashions inside Azure based mostly on Azure OpenAI Service, for instance GPT 3.5 Turbo, GPT-4, and DALL-E know-how.
• One-base structure: The versatile base structure addresses a wide-array of use-cases for optimum effectivity and flexibility.
• Simple to plug-in: The structure could be seamlessly built-in into present architectures, offering swift deployments.
• Unified information sourcing: Seamlessly combine a number of information sources together with structured and unstructured information.
• Accountable and safe: Azure OpenAI Service cases are remoted from each different buyer—the information will not be used to coach the AI mannequin and is protected by complete enterprise compliance and safety controls.

Firms like Mercedes-Benz have already began to implement Microsoft AI-based options throughout the worth chain resembling manufacturing, gross sales and advertising and marketing, and in-vehicle providers. Different {industry} examples embrace GM, Amadeus, CarMax, and Air India.

Azure innovation accelerator reference structure

The Azure innovation accelerator (Azure IX) is an end-to-end cloud resolution offering trendy, versatile, and safe Azure-based IT infrastructure that’s constructed and maintained by a extremely expert DevSecOps group. The answer could be applied inside six to eight weeks, facilitating quick innovation. This method optimizes time to worth and supplies a safe surroundings for single or a number of corporations to collaborate with minimal information administration burden. This structure can be utilized for varied eventualities that require agile collaboration together with companion ecosystem enablement, excessive safety environments, short-term high quality investments, quick-deployments, or restricted IT functionality.

This speedy deployment resolution provides the next advantages:

• Turnkey resolution: Prepared-made state-of-the-art infrastructure based mostly on a Microsoft blueprint and surroundings permits quick roll-out.
• Totally managed resolution: To make sure infrastructure is obtainable and updated with out taxing buyer sources.
• Safety as a service: Microsoft supplies varied managed safety modules out there by means of the platform to service the best safety calls for.
• Outlined governance mannequin: Outlined governance fashions permit trustful collaboration and joint management of the platform to guard belongings and IP.
• Versatile companion collaboration: Enabling onboarding of builders from completely different corporations with completely different insurance policies to develop into productive on one joint platform.
• Change built-In: The platform and the managed parts present a versatile change method based mostly on calls for.
• Deal with producing worth: Burden of upkeep, change, and administration is low by design by means of an agile collaboration mannequin.
• Cut up billing: The associated fee incurred could be distributed among the many companions by means of outlined cut up.

 The Azure innovation accelerator structure consists of the next parts:

• Azure IX is clustered in platform infrastructure and the corresponding DevSecOps builds and runs a dynamic Azure-based cloud surroundings.
• The platform infrastructure consists of the obligatory Azure IX Answer Core with embedded processes based mostly on agile rules for safety and comfort.
• Azure IX supplies base packages for operations tailor-made to the client use case.
• Apart from the complete Azure and Microsoft product stack, the DevSecOps group can run and keep third get together instruments and even buyer instruments by association. The group supplies quick help and backbone for growth and operations inside one group, a key differentiator amongst the competitors.
• The principle constructing blocks of Azure IX are proven within the diagram under.

Throughout the automotive {industry}, Azure IX can be utilized as a base platform to rapidly advance all mobility providers together with SDV, Mobility Copilots, and autonomous automobile growth. One among Azure IX’s first profitable use circumstances has been in advancing autonomous driving growth. Superior driving help techniques (ADAS) know-how wants robust collaboration between varied stakeholders within the growth of latest features that require a extremely versatile, safe surroundings constructed for change.

Unified view of the client reference structure

The Microsoft unified view of the client reference structure brings all sources of buyer information collectively, enabling deep insights and hyper-personalized mobility use circumstances for automotive and industrial unique tools producers (OEMs) and sellers in journey, aviation, and in mobility-as-a-service. The client 360 blueprint units the muse for a unified buyer information platform (resembling information integration, pipelines, and consent handing) to mix related information sources into one single view of the client.  

Among the advantages of this structure embrace:

• Improved buyer expertise: The structure supplies a 360-degree view of the client, enabling companies to ship customized experiences throughout channels and touchpoints.
• Elevated effectivity: By consolidating buyer information sources, companies can cut back the effort and time required to entry and analyze buyer information with “zero extract, remodel, and cargo (ETL)” integration and “zero-data transfer”.
• Higher choice making: The structure permits companies to achieve deep perception into buyer habits and preferences, which can be utilized to make data-driven choices.
• Elevated income: By delivering customized experiences and enhancing buyer satisfaction, companies can enhance buyer loyalty and income.
• Safe perception: A customized ID guards buyer insights making certain consent is dealt with clearly and seamlessly and insights are on the contact of the client’s digital fingertip.

Unified view of the client is predicated on a harmonized information mannequin utilizing Microsoft Material to supply buyer core information together with unified buyer id. The structure illustrates how reside buyer interactions are processed by means of occasion stream and real-time analytics, then built-in with advertising and marketing content material to create a complete buyer 360-degree profile by means of Microsoft Material. This profile is enriched with information from third-party advertising and marketing clouds and central advertising and marketing channels, which is then analyzed for insights and suggestions utilizing Microsoft Dynamics 365 Buyer Insights.

Clients like Amadeus are leveraging buyer centric options to create extra selection for his or her prospects, higher high quality service, and smoother journey experiences.

Related fleets reference structure

The Related fleets reference structure permits quicker, decrease value, larger worth fleet administration options—resembling asset administration and subject service—by simplifying worth extraction from related automobile information, streamlining integration with enterprise techniques, and facilitating specialised analytics.

The Related fleets integration framework permits companions to construct value-added options with distinctive capabilities, whereas additionally enabling the client to benefit from key options resembling Microsoft Material, Microsoft Dynamics 365, and Azure OpenAI Service. This eliminates the necessity for fractured and costly options constructed from a number of sources, permits quicker growth and time to worth, and makes use of the Microsoft Cloud to scale back prices. With versatile, standards-based information ingestion, the structure helps present related automobile options, OEM feeds, or information exchanges as acceptable. This flexibility helps to extend scope and cut back value of car information acquisition.

The Related fleets reference structure is enabled by the next companions: Accenture, Cognizant, Related Automobiles, DSA, Hitachi Zero Carbon, HCL Applied sciences, Luxoft, Mojio, Netstar, STZRE, and TomTom. A reside instantiation of the facility of composing a number of companion options collectively is now out there and underpins a brand new demo proven first at CES 2024, as illustrated within the following graphic:

Autonomous automobile operations reference structure

The autonomous automobile operations (AVOps) reference structure supplies an built-in, end-to-end workflow for creating, verifying, and enhancing ADAS and autonomous automobiles (AVs).

Business-leading Microsoft Azure cloud providers are supplied to combine together with your device chain, whereas our companions full a robust, industry-vetted international, safe, and hyper-scale cloud-based growth platform that spans growth, validation, runtime deployments, and suggestions loops.

No matter stage of autonomy, creating a self-driving software program stack and bringing a brand new automobile to market presents a sequence of workflow challenges:

• Environment friendly ingestion of terabytes and even petabytes of knowledge each day generated by fleets of check automobiles.
• Software program and AI replace requires validation by means of simulation with large quantities of computing energy.
• Petabytes of knowledge and peta-scale computing is dear—delivering on time and inside finances is difficult.
• How do you precisely validate and check efficiency?

AVOps supplies a templatized digital testbed that may be spun up on demand, shared throughout all the worth chain, and used to shorten time-to-market. This method helps our automotive prospects remodel themselves into software program and AI corporations.

The structure additionally helps optimize operational ADAS and AV workflow coordination and have growth, verification, and validation by means of:

• DataOps: From edge to cloud, the orchestration of petabytes of knowledge to help parallel workstreams.
• DevOps: Scaling the continual integration (CI) and steady supply (CD) pipeline.
• MLOps: Scaling machine studying pipelines and integrating with CI and CD pipelines.
• ValidationOps: The flexibility to precisely simulate software program and AI updates throughout all edge circumstances.

How generative AI might help

The white paper “Enhancing effectivity in AVOps with Generative AI” explores how generative AI might help cut back the complexity, value, and time of creating and testing autonomous driving techniques throughout simulation, validation, optimization, and personalization. Use circumstances embrace producing artificial eventualities, validating sensor information, optimizing driving habits, and personalizing person expertise.

The AVOps reference structure supplies a collaborative, open framework constructed on frequent processes that helps automate, handle, and intently monitor the validation processes for software program and {hardware} deployment. The next Microsoft companions present further value-added capabilities to this framework: Ansys, Akridata, Utilized Instinct, Cognata, dSPACE, and Linker Networks.

Digital promoting reference structure

The digital promoting reference structure permits reinvention of the normal buyer journey by remodeling real-life areas into an immersive and interactive digital surroundings that reaches a wider vary of shoppers.

The reference structure permits distinctive, environment friendly, and immersive methods to interact with customers by unlocking the facility of the metaverse to enhance communications, gross sales, and operations. Enhanced by companion capabilities, focus areas embrace digital advertising and marketing, e-commerce, high-fidelity 3D rendering, and industry-specific techniques. By integrating disparate information from the client, subject service, and vendor administration techniques, improved visibility, collaboration, and information insights can drive extra customized, multi-channel buyer experiences. By the digital promoting reference structure, cloud and companion capabilities, OEMs, sellers, and mobility, service suppliers now have the flexibleness to boost in-person interactions together with enabling new digital buyer engagement fashions.

The next announcement by Fiat highlights the transformative affect of digital promoting.

A gaggle of curated professional companions will drive innovation whereas offering excellence in omnichannel success, immersive and digital person experiences, and end-to-end course of protection. These companions embrace: Sitecore, Adobe, Touchcast, Annata, and Stella Automotive AI.

Reinventing the client journey

Microsoft in mobility and manufacturing industries

John Reed

Options Chief, Manufacturing and Mobility Industries

John Reed serves as Options Chief for the Manufacturing and Mobilities industries. He’s liable for Microsoft’s international portfolio of cloud, edge & AI pushed options and partnerships in: Automotive; Discrete, Course of & Excessive-Tech Manufacturing; Aerospace; and Transportation & Logistics. With greater than 20 years of expertise within the Automotive {industry}, he is been concerned within the evolution of mobility applied sciences and options throughout producers, distributers, retailers, and mobility providers suppliers.

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