In at present’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 appropriate know-how to face these challenges should drive transformation and ship extra worth in much less time.
Microsoft automotive, mobility, and transportation reference architectures
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 assets assist our accomplice ecosystem help their clients in driving the way forward for mobility throughout analysis and improvement, manufacturing, provide chain and logistics, advertising and marketing, gross sales, and aftersales.
Microsoft mobility documentation
Benefit from 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
- Linked fleets
- Unified view of the client new
- Digital promoting
Microsoft reference architectures are designed to supply construction and steering for undertaking 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 improvement toolchain leveraging sturdy developer tooling companies with further performance particular to automotive. The reference structure covers steady improvement, testing, and supply of high-quality software program.
This plug-and-play method offers the next advantages:
- Reduces the time to onboard new builders and will increase code high quality utilizing generative AI.
- Accelerates improvement, testing, and validation of automotive software program by shifting left—testing earlier and extra typically within the improvement course of to enhance software program high quality and improvement velocity.
- 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 standard infrastructure for deploying software program artifacts from verification by means of software-in-the-loop (SiL) to check fleets and gathering “fascinating information” to drive adjustments to the software program.
The SDV reference structure consists of the next components:
- Improvement tooling utilizing confirmed Microsoft instruments to extend developer productiveness and collaboration corresponding to GitHub, GitHub Copilot, Microsoft Dev Field, and Visible Studio Code. These instruments are extensible with automotive-specific performance from companions.
- The SDV improvement, validation, and integration reference structure offers orchestration companies that mean you can handle deployment environments and goal configurations to speed up your testing and verification on digital ECU and digital HiL options within the cloud.
- Azure companies present foundational capabilities, corresponding to deployment environments, compute virtualization, and information storage. Microsoft Cloth offers information and analytics companies.
- Azure networking offers connectivity to on-premises, HiL validation environments.
- The Azure and GitHub marketplaces simplify integration of accomplice choices for tooling and digital pictures.
Mobility Copilot reference structure
The Mobility Copilot reference structure permits numerous use circumstances throughout the worth chain to extend productiveness, unleash creativity, and drive innovation with AI. The structure helps eventualities in analysis and improvement, manufacturing, advertising and marketing and gross sales, in-vehicle companies, and after-sales or restore with innovative structure constructed on the newest AI fashions with numerous 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 improvement, 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:
- Greatest-in-class AI fashions: Multi-modal enterprise-grade fashions inside Azure primarily based 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.
- Straightforward to plug-in: The structure will 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 situations are remoted from each different buyer—the information is just not 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 corresponding to manufacturing, gross sales and advertising and marketing, and in-vehicle companies. Different {industry} examples embody 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 crew. The answer will be applied inside six to eight weeks, facilitating quick innovation. This method optimizes time to worth and offers a safe atmosphere for single or a number of firms to collaborate with minimal information administration burden. This structure can be utilized for numerous eventualities that require agile collaboration together with accomplice ecosystem enablement, excessive safety environments, short-term high quality investments, quick-deployments, or restricted IT functionality.
This speedy deployment resolution gives the next advantages:
- Turnkey resolution: Prepared-made state-of-the-art infrastructure primarily based on a Microsoft blueprint and atmosphere permits quick roll-out.
- Absolutely managed resolution: To make sure infrastructure is on the market and updated with out taxing buyer assets.
- Safety as a service: Microsoft offers numerous managed safety modules obtainable by means of the platform to service the best safety calls for.
- Outlined governance mannequin: Outlined governance fashions enable trustful collaboration and joint management of the platform to guard property and IP.
- Versatile accomplice collaboration: Enabling onboarding of builders from completely different firms with completely different insurance policies to turn into productive on one joint platform.
- Change built-In: The platform and the managed elements present a versatile change method primarily based on calls for.
- Concentrate on producing worth: Burden of upkeep, change, and administration is low by design by means of an agile collaboration mannequin.
- Cut up billing: The fee incurred will be distributed among the many companions by means of outlined break up.
The Azure innovation accelerator structure consists of the next components:
- Azure IX is clustered in platform infrastructure and the corresponding DevSecOps builds and runs a dynamic Azure-based cloud atmosphere.
- The platform infrastructure consists of the necessary Azure IX Answer Core with embedded processes primarily based on agile ideas for safety and comfort.
- Azure IX offers base packages for operations tailor-made to the client use case.
- Moreover the complete Azure and Microsoft product stack, the DevSecOps crew can run and keep third occasion instruments and even buyer instruments by association. The crew offers rapid help and determination for improvement and operations inside one crew, a key differentiator amongst the competitors.
- The primary 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 companies together with SDV, Mobility Copilots, and autonomous automobile improvement. Certainly one of Azure IX’s first profitable use circumstances has been in advancing autonomous driving improvement. Superior driving help techniques (ADAS) know-how wants sturdy collaboration between numerous stakeholders within the improvement of recent features that require a extremely versatile, safe atmosphere 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 authentic gear producers (OEMs) and sellers in journey, aviation, and in mobility-as-a-service. The shopper 360 blueprint units the inspiration for a unified buyer information platform (corresponding to information integration, pipelines, and consent handing) to mix related information sources into one single view of the client.
A number of the advantages of this structure embody:
- Improved buyer expertise: The structure offers 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 resolution making: The structure permits companies to achieve deep perception into buyer conduct and preferences, which can be utilized to make data-driven choices.
- Elevated income: By delivering customized experiences and bettering buyer satisfaction, companies can enhance buyer loyalty and income.
- Safe perception: A personalised 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 relies on a harmonized information mannequin utilizing Microsoft Cloth to supply buyer core information together with unified buyer id. The structure illustrates how dwell 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 Cloth. 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 proposals utilizing Microsoft Dynamics 365 Buyer Insights.
Prospects like Amadeus are leveraging buyer centric options to create extra alternative for his or her clients, higher high quality service, and smoother journey experiences.
Linked fleets reference structure
The Linked fleets reference structure permits sooner, decrease price, increased worth fleet administration options—corresponding to asset administration and subject service—by simplifying worth extraction from linked automobile information, streamlining integration with enterprise techniques, and facilitating specialised analytics.
The Linked fleets integration framework permits companions to construct value-added options with distinctive capabilities, whereas additionally enabling the client to reap the benefits of key options corresponding to Microsoft Cloth, Microsoft Dynamics 365, and Azure OpenAI Service. This eliminates the necessity for fractured and costly options constructed from a number of sources, permits sooner improvement 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 linked automobile options, OEM feeds, or information exchanges as applicable. This flexibility helps to extend scope and cut back price of auto information acquisition.
The Linked fleets reference structure is enabled by the next companions: Accenture, Cognizant, Linked Automobiles, DSA, Hitachi Zero Carbon, HCL Applied sciences, Luxoft, Mojio, Netstar, STZRE, and TomTom. A dwell instantiation of the facility of composing a number of accomplice options collectively is now obtainable 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 offers an built-in, end-to-end workflow for growing, verifying, and bettering ADAS and autonomous automobiles (AVs).
Business-leading Microsoft Azure cloud companies are offered to combine along with your device chain, whereas our companions full a powerful, industry-vetted international, safe, and hyper-scale cloud-based improvement platform that spans improvement, validation, runtime deployments, and suggestions loops.
No matter stage of autonomy, growing 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 take a look at 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 pricey—delivering on time and inside finances is difficult.
- How do you precisely validate and take a look at efficiency?
AVOps offers a templatized digital testbed that may be spun up on demand, shared throughout the whole worth chain, and used to shorten time-to-market. This method helps our automotive clients remodel themselves into software program and AI firms.
The structure additionally helps optimize operational ADAS and AV workflow coordination and have improvement, 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 power to precisely simulate software program and AI updates throughout all edge circumstances.
How generative AI may help
The white paper “Enhancing effectivity in AVOps with Generative AI” explores how generative AI may help cut back the complexity, price, and time of growing and testing autonomous driving techniques throughout simulation, validation, optimization, and personalization. Use circumstances embody producing artificial eventualities, validating sensor information, optimizing driving conduct, and personalizing person expertise.
The AVOps reference structure offers a collaborative, open framework constructed on widespread 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 atmosphere that reaches a wider vary of shoppers.
The reference structure permits distinctive, environment friendly, and immersive methods to have interaction with shoppers by unlocking the facility of the metaverse to enhance communications, gross sales, and operations. Enhanced by accomplice capabilities, focus areas embody digital advertising and marketing, e-commerce, high-fidelity 3D rendering, and industry-specific techniques. By integrating disparate information from the client, subject service, and supplier administration techniques, improved visibility, collaboration, and information insights can drive extra customized, multi-channel buyer experiences. Via the digital promoting reference structure, cloud and accomplice capabilities, OEMs, sellers, and mobility, service suppliers now have the pliability to reinforce in-person interactions together with enabling new digital buyer engagement fashions.
The next announcement by Fiat highlights the transformative impression 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 embody: Sitecore, Adobe, Touchcast, Annata, and Stella Automotive AI.
Reinventing the client journey
Microsoft in mobility and manufacturing 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 companies suppliers.
