Industry guide: Aerospace and satellite
This guide highlights sessions at re:Invent 2024 that help aerospace and satellite professionals reimagine how to design, launch, operate, and maintain space systems; derive insights to make better decisions faster; and accelerate innovation by using the AWS Cloud and advanced space technologies.
Clint Crosier
Director, Aerospace and Satellite Solutions, AWS
We have a lot in store for aerospace and satellite professionals at AWS re:Invent this year, as evidenced by the breakout sessions, chalk talks, workshops, and a builders’ session we’ve curated below that are designed to inspire and educate.
Join the following sessions to hear how the transformative power of the cloud is empowering organizations across the industry to design, launch, operate, and maintain space systems, derive insights to make better decisions faster, and accelerate innovation. You’ll hear directly from AWS technical leaders, customers, and AWS Partners who will share the latest innovative technologies, immersive demo experiences, and interactive workshops. You’ll also learn from experts who are illuminating new paths with AWS, and get key insights that can help you continue to push boundaries and reimagine the art of the possible.
In the meantime, be sure to keep an eye out for re:Invent updates on the AWS Public Sector Blog as well as on LinkedIn and X. See you in Las Vegas.
Breakout session
AES301 | Scepter, Inc. uses big data to reduce methane emissions
Trace gases including methane and carbon dioxide contribute to climate change and impact the health of millions of people across the globe. Discover how Scepter, Inc. aggregates vast datasets, pinpoints emissions, and helps customers like ExxonMobil monitor and mitigate methane releases. Learn how the ScepterAir data fusion platform uses advanced AWS Cloud services to analyze and extract insights from ground-based, airborne, and in-orbit data sources with low latency. These atmospheric monitoring capabilities help governments, energy companies, agriculture, waste management, healthcare, retail, and transportation industries monitor methane, carbon dioxide, and airborne particulates to help them reach their sustainability goals and meet regulatory requirements.
AES309 | ULA accelerates innovation by lowering cloud compliance risk at scale
Heavily regulated cloud environments are required for mission-critical operations like launch services but can impede innovation. Explore how United Launch Alliance (ULA), a leader in the aerospace industry, maintains least privilege at scale in regulated cloud environments while ensuring rigorous security and compliance across AWS GovCloud (US). This “functional privilege” approach, developed by ULA and AWS Professional Services, combines least privilege ideology with a cross-functional community of practice and ULA-architected robust security compliance controls and guardrails. This lets users, developers, and engineers innovate freely, enhances ULA’s security posture, and helps support 100% mission success while maintaining high security standards.
Chalk talk
MFG308-R1 | Build a seamless network between the factory shop floor and the cloud [REPEAT]
In the world of modern manufacturing, the concept of a ubiquitous network has emerged as a game-changer, promising to revolutionize the way we connect, process, and leverage data across production systems. Imagine an environment where computing and communication capabilities are seamlessly embedded into every aspect of your manufacturing operations, enabling real-time access to information and services, anytime and anywhere. This chalk talk explains how to build such a network on AWS and accelerate various manufacturing use cases such as predictive maintenance, quality control, supply chain optimization, and energy management, while addressing best practices and considerations for a successful implementation.
MFG308-R | Build a seamless network between the factory shop floor and the cloud [REPEAT]
In the world of modern manufacturing, the concept of a ubiquitous network has emerged as a game-changer, promising to revolutionize the way we connect, process, and leverage data across production systems. Imagine an environment where computing and communication capabilities are seamlessly embedded into every aspect of your manufacturing operations, enabling real-time access to information and services, anytime and anywhere. This chalk talk explains how to build such a network on AWS and accelerate various manufacturing use cases such as predictive maintenance, quality control, supply chain optimization, and energy management, while addressing best practices and considerations for a successful implementation.
AES303-R1 | Degas uses generative AI on AWS to help smallholder farmers in Ghana [REPEAT]
Degas Ltd., a Japanese agri-fintech startup, uses generative AI to help 65,000 smallholder farmers in Africa. In this chalk talk, learn how Degas developed a geospatial foundation model on Amazon SageMaker to tackle climate change and improve life on earth. Discover how Degas leveraged SageMaker to build their geospatial foundation model which, using only small fine-tuning datasets, can be customized to solve a variety of common earth observation problems using satellite imagery, such as flood and drought detection, wildfire prediction, land cover segmentation, building change detection, and deforestation detection.
AES303-R | Degas uses generative AI on AWS to help smallholder farmers in Ghana [REPEAT]
Degas Ltd., a Japanese agri-fintech startup, uses generative AI to help 65,000 smallholder farmers in Africa. In this chalk talk, learn how Degas developed a geospatial foundation model on Amazon SageMaker to tackle climate change and improve life on earth. Discover how Degas leveraged SageMaker to build their geospatial foundation model which, using only small fine-tuning datasets, can be customized to solve a variety of common earth observation problems using satellite imagery, such as flood and drought detection, wildfire prediction, land cover segmentation, building change detection, and deforestation detection.
AES306 | Deliver accurate all-weather Earth observation data with gen AI on AWS
Synthetic-aperture radar (SAR) satellites capture detailed images of Earth in light-obscured conditions and let customers consistently monitor changing conditions. Learn how to use a deep learning-based algorithm, combined with Amazon SageMaker, to reconstruct optical imagery from SAR data and create synthetic cloud-free images up to four times resolution for agriculture and utility infrastructure monitoring. Find out how customers use Amazon SageMaker and data lakes on Amazon S3 for near real-time data retrieval and analysis.
MFG310 | Deploying an MES in the cloud or at the edge on AWS Outposts
Manufacturers today are looking at how the cloud can provide flexibility and resilience, as well as reduce cost for their production critical systems. Manufacturing execution system (MES) can be deployed in the cloud or for manufacturers who need low latency or have limited bandwidth on an AWS Outpost running at the edge. In this chalk talk, deep dive into the architectural patterns for deploying a MES system on AWS and on an AWS Outpost, including network topology and connectivity. This talk also walks through the reference architecture for running Siemens Opcenter Execution on AWS in general and on AWS Outposts in particular.
MFG315 | Edge-to-cloud robotic solutions for optimizing manufacturing processes
Within manufacturing, the integration of robotics has revolutionized operations. However, successful implementations require careful planning. Robotic simulation is a powerful tool to virtually test and validate robotic systems before physical deployments, minimizing risks and optimizing processes. This chalk talk presents architectural patterns and a demonstration of robotic simulation with AWS IoT Greengrass and AWS IoT Core, enabling edge-to-cloud connectivity for manufacturers. This approach facilitates a validation of robotic systems using real-world data from Open 3D Engine (O3DE) simulators and AWS IoT Core, enabling manufacturers to simulate the entire manufacturing process including robotic systems, conveyors, and other equipment before physical implementation.
MFG311-R | Engineer and develop innovative products faster with generative AI [REPEAT]
In this session, learn how generative AI can be used in product engineering and development, from responding to a Request for Proposal (RFP) to generating new concepts and developing digital threads. Watch how to extract the key functional, technical, compliance, and user experience requirements from multiple document types including 2D technical drawings. Explore how to share data across engineering disciplines in various languages and how to enrich generative design for new product ideas. This session showcases some of these generative AI product engineering use cases with live demos and code samples.
MFG311-R1 | Engineer and develop innovative products faster with generative AI [REPEAT]
In this session, learn how generative AI can be used in product engineering and development, from responding to a Request for Proposal (RFP) to generating new concepts and developing digital threads. Watch how to extract the key functional, technical, compliance, and user experience requirements from multiple document types including 2D technical drawings. Explore how to share data across engineering disciplines in various languages and how to enrich generative design for new product ideas. This session showcases some of these generative AI product engineering use cases with live demos and code samples.
MFG312 | Managing value-chain product carbon emissions data with generative AI
Manufacturers face increasing demand from customers and public authorities to accurately model, calculate, and report on their product-based carbon emissions. A credible assessment requires internal data management capabilities and the efficient exchange of high-trust information with suppliers. For larger manufacturers this may involve scaling to thousands of suppliers and/or products. Learn how connectivity, trust, and information exchange come together in the value chain, and about the mechanisms behind the modeling and calculation of product-based carbon emissions — and how it all can be accelerated using generative AI services on AWS.
MFG313 | Transforming manufacturing operations: AWS e-bike smart factory demo
In this session, dive deep into how manufacturers can leverage AWS services and partner solutions to optimize their manufacturing operations. This chalk talk uses the story of a fictitious e-bike company and a purpose-built e-bike smart factory demo. Through an architectural walk through, explore the use of AWS industrial IoT, generative AI, AI/ML, and analytics services that were used to build the demo for the use case. This includes real-time visibility of production metrics, detection of equipment anomalies, automated quality inspection and defect detection, and a generative AI assistant that provides contextual insights and guided troubleshooting.
MFG309 | Use generative AI to transform product R&D docs into MBSE models
In this chalk talk, learn how generative AI can transform product R&D documentation into actionable model-based systems engineering (MBSE) models. Organizations developing highly complex, safety-critical products like aircraft, space systems, and medical equipment require extensive collaboration across engineering disciplines and global stakeholders. Traditionally, this has relied on using documents for R&D specification and design. Explore how users can leverage generative AI to migrate from document-based to model-based systems engineering approach to help reduce design cycle times and improve operational readiness.
Workshop
MFG306 | A connected & optimized supply chain with AWS Supply Chain & gen AI
Supply chain-related processes and solutions usually rely on complex environments made by homegrown applications, several siloed execution systems, and point-to-point integrations. This can lead into a lack of visibility and consequent inefficiency in making the right decisions at the right time. AWS Supply Chain is able to mitigate risks, lower costs, improve visibility, and accelerate the decision-making process thanks to ML- and LLM-powered connectors, ML-powered insights and recommendations, generative AI–powered insights and analysis. In this workshop, learn how to set up the application, ingest the data, generate a demand forecast and supply plan, and use generative AI fine-tuned for supply chain to extract insights. You must bring your laptop to participate.
MFG305 | Building a smart factory with Amazon Q Business
Learn how to build and deploy an AI assistant that seamlessly integrates with AWS services, enabling interaction with your industrial data in real time. Imagine an assistant that can answer questions like “What is the OEE for this line?” or compose maintenance requests. This workshop walks through the process of deploying an API to interface with industrial IoT services and creating a custom plugin in Amazon Q Business. Coding experience isn’t required, but some API design and industrial automation knowledge is helpful. Leave this workshop with a functional AI assistant that can be tailored to your factory’s needs. You must bring your laptop to participate.
IOT316-R1 | Unleash edge computing with AWS IoT Greengrass on NVIDIA Jetson [REPEAT]
In this workshop, walk through the process of loading AWS IoT Greengrass onto an NVIDIA Jetson server via NVIDIA JetPack SDK, remotely logging in to the edge server, and deploying an AWS IoT Greengrass component to the edge device. Gain practical experience using AWS IoT Core and AWS IoT Greengrass to orchestrate and manage edge runtime devices from the cloud. Through a step-by-step, interactive format, learn how to build solutions that extend cloud functionality to edge devices with processing, management, and AI microservices capabilities, while addressing real-world use cases. You must bring your laptop to participate.
IOT316-R | Unleash edge computing with AWS IoT Greengrass on NVIDIA Jetson [REPEAT]
In this workshop, walk through the process of loading AWS IoT Greengrass onto an NVIDIA Jetson server via NVIDIA JetPack SDK, remotely logging in to the edge server, and deploying an AWS IoT Greengrass component to the edge device. Gain practical experience using AWS IoT Core and AWS IoT Greengrass to orchestrate and manage edge runtime devices from the cloud. Through a step-by-step, interactive format, learn how to build solutions that extend cloud functionality to edge devices with processing, management, and AI microservices capabilities, while addressing real-world use cases. You must bring your laptop to participate.
MFG307 | Use ML for CAE simulation to morph geometries and predict flow fields
Jump into the role of a simulation engineer who is redesigning a vehicle’s exterior and has to show critical metrics to leadership. Learn how to deploy the AWS machine learning (ML) for simulation toolkit, and prepare a generative AI–enabled engineering environment to see how fast simulation can be. You can upload your own vehicle geometry or choose one that’s provided for you, morph it using generative AI, get aerodynamic flow field and KPI predictions, and experience how to exceed leadership expectations by delivering engineering data days ahead of schedule. Get hands-on with advanced product engineering techniques. You must bring your laptop to participate.