Next IIoT wave: embedded digital twin for manufacturing IRS srl
Next IIoT wave will be a population of digital twin. A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to to implement an embedded digital twin using real-time monitoring, physical models, and machine learning
This document discusses digital twin technology, including its definition, history, importance, enabling technologies, and applications. A digital twin is a virtual representation of a physical object that can dynamically change as the physical object is monitored. Gartner predicts that by 2021, 50% of large industrial companies will use digital twins to gain a 10% improvement in effectiveness. Digital twins are enabled by technologies like IoT, cloud computing, big data analytics, blockchain, and VR/AR. They have applications in customer experience, performance tuning, digital machine learning, healthcare, smart cities, and maintenance. While digital twins allow for improved products, some cons include high costs and a complex infrastructure requirement.
Nurturing Digital Twins: How to Build Virtual Instances of Physical Assets to...Cognizant
To embark on the digital twin jounrey, assess your readiness, define and communicate a vision, set common data management rules and build in flexibility for intelligence.
The document discusses Siemens Digital Industries Software, which provides industrial software and automation solutions. It notes that Siemens is the #1 provider of industrial software and automation in the world. It highlights the company's focus on digital transformation and creating comprehensive digital twins to optimize performance for customers across industries like manufacturing, electronics, and energy. The document also outlines Siemens' strategy to transition software offerings to cloud-based SaaS models and build out its Xcelerator integrated development platform.
Digital twins: the power of a virtual visual copy - Unite Copenhagen 2019Unity Technologies
From buildings and infrastructure to industrial machinery and factories, digital twins are becoming integral revisualization tools across the industrial sector. Learn how Unit040, a company specializing in visualization and simulation, creates digital twins that combine real-time 3D technology with BIM, CAD and CAE systems to add value at all stages of the building and product lifecycle, from the early design phase to predictive maintenance using Internet of Things (IoT) data.
Speakers:
Pieter Weterings - Unit040
Guido van Gageldonk - Unit040
Watch the session on YouTube: https://youtu.be/j4i14p89h_s
The document is a seminar report submitted by Faheem M M to the APJ Abdul Kalam Technological University in partial fulfillment of the requirements for a Bachelor of Technology degree in Mechanical Engineering. The report discusses digital twin technology, providing an introduction, literature review, explanation of how digital twins work and are implemented, steps to create a digital twin, underlying technologies, advantages, disadvantages, applications, and conclusion.
A digital twin is a digital profile of a physical object or system that uses sensor data to help optimize performance. Sensors on physical objects collect data and send it to the digital twin, and the interaction between the physical object and digital twin can optimize performance through predictive maintenance. Digital twins are useful because they bridge the physical and digital worlds by translating real-world sensor data into information that can be processed digitally to help optimize businesses and systems. Examples of applications of digital twins include performance tuning, digital machine building, healthcare, smart cities, and predictive maintenance.
Digital twin technology creates a digital replica of a physical object or system that can be used to gather data, understand past and current behavior, and predict future performance. The digital twin is made possible by sensors that collect data from physical assets and IoT technology. The document discusses the history and development of digital twin technology, how it is used across various industries like manufacturing, healthcare, and aerospace to optimize operations and reduce costs, and the future potential of digital twins including using them to make decisions and interact after death.
Next IIoT wave: embedded digital twin for manufacturing IRS srl
Next IIoT wave will be a population of digital twin. A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to to implement an embedded digital twin using real-time monitoring, physical models, and machine learning
This document discusses digital twin technology, including its definition, history, importance, enabling technologies, and applications. A digital twin is a virtual representation of a physical object that can dynamically change as the physical object is monitored. Gartner predicts that by 2021, 50% of large industrial companies will use digital twins to gain a 10% improvement in effectiveness. Digital twins are enabled by technologies like IoT, cloud computing, big data analytics, blockchain, and VR/AR. They have applications in customer experience, performance tuning, digital machine learning, healthcare, smart cities, and maintenance. While digital twins allow for improved products, some cons include high costs and a complex infrastructure requirement.
Nurturing Digital Twins: How to Build Virtual Instances of Physical Assets to...Cognizant
To embark on the digital twin jounrey, assess your readiness, define and communicate a vision, set common data management rules and build in flexibility for intelligence.
The document discusses Siemens Digital Industries Software, which provides industrial software and automation solutions. It notes that Siemens is the #1 provider of industrial software and automation in the world. It highlights the company's focus on digital transformation and creating comprehensive digital twins to optimize performance for customers across industries like manufacturing, electronics, and energy. The document also outlines Siemens' strategy to transition software offerings to cloud-based SaaS models and build out its Xcelerator integrated development platform.
Digital twins: the power of a virtual visual copy - Unite Copenhagen 2019Unity Technologies
From buildings and infrastructure to industrial machinery and factories, digital twins are becoming integral revisualization tools across the industrial sector. Learn how Unit040, a company specializing in visualization and simulation, creates digital twins that combine real-time 3D technology with BIM, CAD and CAE systems to add value at all stages of the building and product lifecycle, from the early design phase to predictive maintenance using Internet of Things (IoT) data.
Speakers:
Pieter Weterings - Unit040
Guido van Gageldonk - Unit040
Watch the session on YouTube: https://youtu.be/j4i14p89h_s
The document is a seminar report submitted by Faheem M M to the APJ Abdul Kalam Technological University in partial fulfillment of the requirements for a Bachelor of Technology degree in Mechanical Engineering. The report discusses digital twin technology, providing an introduction, literature review, explanation of how digital twins work and are implemented, steps to create a digital twin, underlying technologies, advantages, disadvantages, applications, and conclusion.
A digital twin is a digital profile of a physical object or system that uses sensor data to help optimize performance. Sensors on physical objects collect data and send it to the digital twin, and the interaction between the physical object and digital twin can optimize performance through predictive maintenance. Digital twins are useful because they bridge the physical and digital worlds by translating real-world sensor data into information that can be processed digitally to help optimize businesses and systems. Examples of applications of digital twins include performance tuning, digital machine building, healthcare, smart cities, and predictive maintenance.
Digital twin technology creates a digital replica of a physical object or system that can be used to gather data, understand past and current behavior, and predict future performance. The digital twin is made possible by sensors that collect data from physical assets and IoT technology. The document discusses the history and development of digital twin technology, how it is used across various industries like manufacturing, healthcare, and aerospace to optimize operations and reduce costs, and the future potential of digital twins including using them to make decisions and interact after death.
Digital Twin - What is it and how can it help us?Shaun West
RQ: What services can be provided (by whom and to who) through (or adopting, or developing) the digital twin concepts?
Our focus is long-life capital equipment
Consider the whole life cycle
Apply Service Dominant Logic in the assessment
Consider technical and business hierarchies
The document discusses preparing organizations for digital twins using IoT platforms and technologies like AI, analytics, and cloud services. It emphasizes positioning AI to augment human insights, reinventing operations with new digital data sources, and leveraging proven industrial expertise. Digital twins can provide real-time virtual representations of physical systems to improve decision making across their lifecycles using multiple data sources and models. The document recommends preparing for digital twins as part of an extensible IoT platform.
A digital twin is a virtual representation of a physical object that can be used to help optimize business decisions. The webinar discusses the history and definition of digital twins, how they are enabled by technologies like IoT, and how companies are using them. Digital twins allow a physical object and its virtual counterpart to be connected, providing a closed loop between the simulated and physical worlds to improve conceptualization, comparison, and remote collaboration.
The document discusses the Internet of Things (IoT). It defines IoT as physical objects embedded with sensors that can collect and exchange data over the internet. It describes how IoT works through technologies like RFID, sensors, and wireless connections. It also outlines some applications of IoT like smart homes, manufacturing, healthcare, and more. Finally, it discusses technological challenges and criticisms of IoT, such as issues with privacy, security, and political manipulation.
Digital Twin at-a-glance, Yong @SEMIforteYong Wang
Digital twins are virtual representations of physical objects or systems which are expected to proliferate greatly by 2020. They allow real-time data from sensors to be integrated into virtual models to enable optimization and self-monitoring. For manufacturing, digital twins of products, factories and performance can be created using data from design, building and operations to enable benefits like smart scheduling, preventative maintenance and maximized output. The semiconductor industry is well-positioned to benefit from digital twins as it already collects extensive operational data and has the computing power required.
I. Metaverse Enterprise Platform
Metaverse Enterprise Platform
Metaverse Enterprise Platform System Components
Metaverse Enterprise Use Case - AI Innovation Platform
Metaverse Enterprise Use Case - Digital Twin Retail Store
Metaverse Enterprise Use Case - Global Supply Chain Risk Mitigation
Metaverse Enterprise Use Case – Energy Management Optimization
Immersive 3D Digital Twin Platform Demo
II. ESG Digital Transformation for Profitably Sustainable Business
ESG Sustainability Imperative
How ESGDX Can Create New Revenue Streams?
ESG + Digital Transformation (ESGDX) Business Model
Digital Decarbonization
Climate Risk & Net-Zero Management Automation
Digital Twins for Dynamic Carbon Net-Zero Management
Digital Twins Use Case: A Pulp/Paper Company in S. Korea
Digital Twins for Building Net-Zero Management
Climate Risk & Net-Zero Management Digital Twins Under Development
Industrial/Enterprise Metaverse Forum & ESG DX Forum
III. Digital Twins Design & Development
Digital Twin Types
Digital Twin Models
Digital Twins + IoT + Big Data Analytics + AI
Wind Turbine Metaverse Digital Twin Design & Development
"Industrial Internet IoT bootcamp" meetup, 11-5-2015 hosted by GE Digital at HackerDojo. Discussing topics ranging from IoT architecture to connectivity and protocols, cyber security, data science and industrial UX design.
An introductory video and presentation looking at Internet of Things (IoT) and differences between IoT and #IIoT. Examples are provided to help clarify the understanding.
What is the Digital Twin?
Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.
Watch the video introduction of this keynote presentation from Genius of Things Summit in Munich https://youtu.be/RaOejcczPas
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
The document discusses the origins and definitions of the digital twin concept. Some key points:
- The concept of a digital twin dates back to 2002 when Dr. Grieves presented the idea of real and virtual spaces that are linked and mirror each other throughout a physical system's lifecycle.
- A digital twin prototype contains information to describe and produce a physical version, while a digital twin instance is linked to a specific physical product.
- Digital twins can be used predictively to simulate future behavior and interrogatively to examine current and past states.
- The digital twin concept envisions the physical and virtual systems remaining linked and updated throughout a system's creation, production, usage, and disposal lifecycle phases.
A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to use the NI platform to implement an environmental control device (HVAC) twin using real-time monitoring, physical models, and machine learning.
The document provides an overview of digital twin technology. It defines a digital twin as a virtual representation of a physical system that is updated with real-time data throughout the physical system's lifecycle. The document discusses the history and importance of digital twins, as well as their applications across various industries like manufacturing, aerospace, healthcare, and wind energy. It also covers the underlying technologies, architecture, characteristics, features, and advantages of digital twins. In conclusion, the document states that digital twins can drive value for companies by helping optimize costs, increase productivity, and improve performance and maintenance.
Internet of things (IoT)- Introduction, Utilities, ApplicationsTarika Verma
The document discusses Internet of Things (IoT). It defines IoT as a platform where everyday devices become smarter through intelligent processing and informative communication, creating a connection between the digital and physical world. The document outlines the key functional blocks of IoT including devices, communication, services, management, security, and applications. It also discusses the utilities of IoT and provides examples of domain-specific IoT applications in areas like wireless sensor networks, aquaculture, distributed sensor networks, smart societies, and location-aware services. The document concludes by noting that IoT has added new potential to the internet by enabling communications between objects and humans to make a smarter planet.
In this presentation, Divya introduces IoT and associated trends. Natasha is interested in IoT applications in the domains of smart cities and pollution reporting.
Integration of Things (Sam Vanhoutte @Iglooconf 2017) Codit
To build an overall IoT solution, a lof of different technologies and skills are needed and the role of an architect is crucial to combine all the different services into a solid solution. In this presentation, you will understand more about the DNA of a typical IoT solution, based on Microsoft Azure. You will see the different pitfalls that come with implementing Industrial IoT solutions.
Digital Twin - What is it and how can it help us?Shaun West
RQ: What services can be provided (by whom and to who) through (or adopting, or developing) the digital twin concepts?
Our focus is long-life capital equipment
Consider the whole life cycle
Apply Service Dominant Logic in the assessment
Consider technical and business hierarchies
The document discusses preparing organizations for digital twins using IoT platforms and technologies like AI, analytics, and cloud services. It emphasizes positioning AI to augment human insights, reinventing operations with new digital data sources, and leveraging proven industrial expertise. Digital twins can provide real-time virtual representations of physical systems to improve decision making across their lifecycles using multiple data sources and models. The document recommends preparing for digital twins as part of an extensible IoT platform.
A digital twin is a virtual representation of a physical object that can be used to help optimize business decisions. The webinar discusses the history and definition of digital twins, how they are enabled by technologies like IoT, and how companies are using them. Digital twins allow a physical object and its virtual counterpart to be connected, providing a closed loop between the simulated and physical worlds to improve conceptualization, comparison, and remote collaboration.
The document discusses the Internet of Things (IoT). It defines IoT as physical objects embedded with sensors that can collect and exchange data over the internet. It describes how IoT works through technologies like RFID, sensors, and wireless connections. It also outlines some applications of IoT like smart homes, manufacturing, healthcare, and more. Finally, it discusses technological challenges and criticisms of IoT, such as issues with privacy, security, and political manipulation.
Digital Twin at-a-glance, Yong @SEMIforteYong Wang
Digital twins are virtual representations of physical objects or systems which are expected to proliferate greatly by 2020. They allow real-time data from sensors to be integrated into virtual models to enable optimization and self-monitoring. For manufacturing, digital twins of products, factories and performance can be created using data from design, building and operations to enable benefits like smart scheduling, preventative maintenance and maximized output. The semiconductor industry is well-positioned to benefit from digital twins as it already collects extensive operational data and has the computing power required.
I. Metaverse Enterprise Platform
Metaverse Enterprise Platform
Metaverse Enterprise Platform System Components
Metaverse Enterprise Use Case - AI Innovation Platform
Metaverse Enterprise Use Case - Digital Twin Retail Store
Metaverse Enterprise Use Case - Global Supply Chain Risk Mitigation
Metaverse Enterprise Use Case – Energy Management Optimization
Immersive 3D Digital Twin Platform Demo
II. ESG Digital Transformation for Profitably Sustainable Business
ESG Sustainability Imperative
How ESGDX Can Create New Revenue Streams?
ESG + Digital Transformation (ESGDX) Business Model
Digital Decarbonization
Climate Risk & Net-Zero Management Automation
Digital Twins for Dynamic Carbon Net-Zero Management
Digital Twins Use Case: A Pulp/Paper Company in S. Korea
Digital Twins for Building Net-Zero Management
Climate Risk & Net-Zero Management Digital Twins Under Development
Industrial/Enterprise Metaverse Forum & ESG DX Forum
III. Digital Twins Design & Development
Digital Twin Types
Digital Twin Models
Digital Twins + IoT + Big Data Analytics + AI
Wind Turbine Metaverse Digital Twin Design & Development
"Industrial Internet IoT bootcamp" meetup, 11-5-2015 hosted by GE Digital at HackerDojo. Discussing topics ranging from IoT architecture to connectivity and protocols, cyber security, data science and industrial UX design.
An introductory video and presentation looking at Internet of Things (IoT) and differences between IoT and #IIoT. Examples are provided to help clarify the understanding.
What is the Digital Twin?
Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.
Watch the video introduction of this keynote presentation from Genius of Things Summit in Munich https://youtu.be/RaOejcczPas
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
The document discusses the origins and definitions of the digital twin concept. Some key points:
- The concept of a digital twin dates back to 2002 when Dr. Grieves presented the idea of real and virtual spaces that are linked and mirror each other throughout a physical system's lifecycle.
- A digital twin prototype contains information to describe and produce a physical version, while a digital twin instance is linked to a specific physical product.
- Digital twins can be used predictively to simulate future behavior and interrogatively to examine current and past states.
- The digital twin concept envisions the physical and virtual systems remaining linked and updated throughout a system's creation, production, usage, and disposal lifecycle phases.
A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to use the NI platform to implement an environmental control device (HVAC) twin using real-time monitoring, physical models, and machine learning.
The document provides an overview of digital twin technology. It defines a digital twin as a virtual representation of a physical system that is updated with real-time data throughout the physical system's lifecycle. The document discusses the history and importance of digital twins, as well as their applications across various industries like manufacturing, aerospace, healthcare, and wind energy. It also covers the underlying technologies, architecture, characteristics, features, and advantages of digital twins. In conclusion, the document states that digital twins can drive value for companies by helping optimize costs, increase productivity, and improve performance and maintenance.
Internet of things (IoT)- Introduction, Utilities, ApplicationsTarika Verma
The document discusses Internet of Things (IoT). It defines IoT as a platform where everyday devices become smarter through intelligent processing and informative communication, creating a connection between the digital and physical world. The document outlines the key functional blocks of IoT including devices, communication, services, management, security, and applications. It also discusses the utilities of IoT and provides examples of domain-specific IoT applications in areas like wireless sensor networks, aquaculture, distributed sensor networks, smart societies, and location-aware services. The document concludes by noting that IoT has added new potential to the internet by enabling communications between objects and humans to make a smarter planet.
In this presentation, Divya introduces IoT and associated trends. Natasha is interested in IoT applications in the domains of smart cities and pollution reporting.
Integration of Things (Sam Vanhoutte @Iglooconf 2017) Codit
To build an overall IoT solution, a lof of different technologies and skills are needed and the role of an architect is crucial to combine all the different services into a solid solution. In this presentation, you will understand more about the DNA of a typical IoT solution, based on Microsoft Azure. You will see the different pitfalls that come with implementing Industrial IoT solutions.
1. The document discusses AIoT and edge computing.
2. It introduces Microsoft's Azure IoT platform and services for connecting, processing, analyzing and acting on IoT data.
3. Edge computing with Azure IoT Edge is described which analyzes data locally on IoT devices to reduce latency and cloud requirements.
Azure iot edge and AI enabling the intelligent edgeMarco Dal Pino
Marco Dal Pino presented on Azure IoT Edge and AI capabilities at the edge. He discussed Microsoft's IoT product portfolio including Azure Sphere, IoT Edge, IoT Hub, and Edge appliances. Dal Pino also covered built-in AI capabilities like anomaly detection on IoT Edge as well as cognitive services containers. Finally, he demonstrated Nvidia Deepstream running computer vision models on IoT Edge and discussed resiliency, observability, and storage options for IoT Edge deployments.
This document discusses the partnership between Microsoft Azure and GE's Predix platform for industrial IoT. For Microsoft, the partnership will help existing industrial customers build and operate IIoT solutions using Azure's capabilities in artificial intelligence, data analytics, and security. For GE, Predix will benefit from Azure's large global footprint and hybrid cloud capabilities. The combination of Predix and Azure aims to bridge the gap between operational technology and information technology for industrial customers worldwide.
IoTSummit: Create iot devices connected or on the edge using ai and mlMarco Dal Pino
This document summarizes an IoT presentation about Azure IoT Edge. It discusses Azure IoT Edge's capabilities including running AI models and containers at the edge, deploying cognitive services containers, adding resiliency with Kubernetes, and monitoring edge devices. It also previews new IoT Edge certified edge servers and gateways from Nvidia and demonstrates logging device data in real-time.
AWS re:Invent 2016: IoT: Build, Test, and Securely Scale (GPST302)Amazon Web Services
With the rapid adoption of IoT services on AWS, how do partners and organizations effectively build, test, scale, and secure these highly transaction-data laden systems? This session is a deep dive on the API, SDK, device gateway, rules engine, and device shadows. Consulting and Technology Partner customers share their experiences as we highlight lessons learned and best practices to increase audience efficacy.
Hoe het Azure ecosysteem een cruciale rol speelt in uw IoT-oplossing (Glenn C...Codit
The document discusses how the Azure ecosystem plays a crucial role in IoT solutions. It outlines key Azure services for connecting devices, processing streaming data, implementing business logic, enabling connectivity, and providing insights. These services include IoT Hub for device connectivity, Stream Analytics for real-time analytics, Service Fabric for business logic, Logic Apps for connectivity, and Time Series Insights for streaming insights. The document also presents the Azure IoT reference architecture and recommends starting with preconfigured solutions like IoT Central to get up and running quickly.
IoT Update Oktober 2019 | Jan Depping @Microsoft | The next step in IoTIoT Academy
This document provides an overview of Microsoft's Internet of Things (IoT) solutions. It discusses how digitization is enabling new opportunities through innovations like the billions of connected devices coming online by 2020. It summarizes Microsoft's approach to IoT including Azure IoT Central for simplified IoT app development, Azure IoT Hub for device connectivity, Azure IoT Edge for edge computing, and Azure Digital Twins for modeling physical environments. It also addresses cross-industry challenges like security, analytics, integration and managing the full device lifecycle that Microsoft's IoT platform aims to address. Resources for learning more about Microsoft's IoT offerings are provided at the end.
The document discusses using ambients and service-oriented architecture (SOA) approaches to address challenges in cloud computing architectures. It proposes an Ambient-SOA modeling language that allows developers to design ambient-aware models and generate executable code. This approach represents different cloud resource types as ambients and allows applications to be dynamically reconfigured across cloud boundaries when resource demands change.
Adopting an IoT solution is not easy for a customer. Azure IoT Hub is great, powerful, but challenging to adopt. Why not evaluate Azure IoT Central as a starting point? As it is implemented on IoT Hub and all Azure IoT family of services, it can be a good starting point for a long term adoption to preserve the most of the initial effort. And then there is also IoT Plug and Play that give to all Azure IoT family the functional structure to be a great enterprise-grade solution.
The fascinating world of Internet of Things is so huge that it cannot be fully described in one session. But you can start your adventure. Presentation of IoT Hub, reference architecture, fast review of a few ready solutions and interaction with MXChip IoT DevKit.
Sajeetharan Sinnathurai is a cloud solution architect with over 10 years of experience as a full stack developer specializing in Angular and Azure. He has made over 10,000 contributions to Stack Overflow and maintains 140 code repositories on StackBlitz. Sinnathurai regularly shares his expertise in developer communities and has received numerous Microsoft certifications and awards for his open source contributions.
This document provides an overview of the Microsoft IoT platform and its capabilities including creating an IoT hub, ingesting telemetry and device data, device provisioning and security, cloud-to-device messaging, the device twin capability, and IoT Edge. It also discusses Azure IoT services like IoT Hub, Device Provisioning Service, IoT Central, IoT Edge and how they provide device connectivity and management, data ingestion and command/control, stream processing, workflow automation, dashboards and visualization.
Discover existing customer stories from various industries such as manufacturing, logistics and construction. No theoretical use cases, but in-depth insights that will help you on how to get started with IoT.
Building Modern Platforms on Microsoft Azure by Steef-Jan WiggersCodit
Agility is everything. To keep up with ever-changing customer demands, disruption and fierce competition, you want to invent, develop and deploy new ideas quickly and efficiently. If you want to explore new business models, build new applications, make them mobile or integrate with partners, choosing the right platform is crucial.
Codit believes that Microsoft Azure is the right platform. It enables you to quickly develop and deploy new applications. This growing, agile platform gives you the freedom to explore and experiment without financial risks.
Seeing opportunities in IoT but finding it hard to define its value for your business? Codit helps you explore new business models, increase business efficiency or optimize your processes with IoT. Disover it all in this presentation about Azure IoT
Using Modern Tools and Technologies to Improve Your Software ArchitectureEran Stiller
This document discusses modern software architecture approaches and tools. It provides examples of how CodeValue has used microservices, serverless computing, and containers to architect solutions for clients. Specific technologies highlighted include Azure Functions, Docker, Kubernetes, and Service Fabric. The talks cover topics like breaking monoliths into microservices, mobile/web architecture, and using cloud-native approaches to future-proof applications.
Power BI Streaming Data Flow e Azure IoT CentralMarco Parenzan
Since 2015, Power BI users have been able to analyze data in real-time thanks to the integration with other Microsoft products and services. With streaming dataflow, you'll bring real-time analytics completely within Power BI, removing most of the restrictions we had, while integrating key analytics features like streaming data preparation and no coding. To see it in action, we will study a specific case of streaming such as IoT with Azure IoT Central.
Similar to Metaverse and Digital Twins on Enterprise-Public.pdf (20)
Project AI-Care for COVID-19 prevention湯米吳 Tommy Wu
This document describes Project AI Care, a thermal image smart healthcare solution using one Microsoft team. The solution uses an ESP32 Cam, M5Stack Core, and AMG 8833 thermal sensor to collect real-time thermal data and leverage Azure Custom Vision AI for mask detection. The system architecture includes training a mask detection AI model using Custom Vision, deploying the model as an IoT Edge module for edge inference, monitoring devices and results using an IoT Central dashboard, and integrating BOT services for multi-channel notifications. The solution aims to help with epidemic prevention by detecting mask-wearing in public areas.
This document discusses machine learning and robotics, specifically deep reinforcement learning using the Robot Operating System (ROS). It provides an overview of deep Q-learning and how it can be used to play Atari games or control a robotic arm. It also describes using ROS packages like Gazebo, SLAM, and Rviz for simulation and navigation. Motion detection with cameras in ROS is demonstrated. Finally, an autonomous system architecture on ROS using AI services like computer vision, speech recognition and natural language processing is presented.
How to create your Smart Toy with bluemix & 7688 Duo board湯米吳 Tommy Wu
This document provides instructions for creating a smart toy using an MTK 7688 Duo board connected to IBM Bluemix. It includes a list of prerequisites, architecture diagrams showing the device publishing data to cloud services and receiving responses, and steps for setting up accounts on Bluemix and registering a device. The device code logic and Node-RED flows for simple question and answering on the cloud are also outlined. Resources for further information are provided at the end.
This document provides an overview of how to quickly build intelligent application systems using IBM Bluemix and Watson services. It discusses how Bluemix is an open PaaS platform for building, managing, and deploying various types of apps. Developers can choose languages and runtimes, and apps can be deployed from zero to production with one command. A variety of IBM, third party, and open source APIs and services are available on Bluemix. Examples of apps that can be built include a chat app using Node-RED, real-time analytics using DashDB and R scripts, and facial recognition using Watson services. The document encourages readers to leverage these capabilities creatively to build innovative systems and solutions.
The document discusses Rational Mobile Suite's model for mobile application development. It has three layers: the UI layer uses Dojo Mobile, the logic layer uses Ajax, and the data access layer uses storage mechanisms like LocalStorage, IndexedDB, and WebSQL. It provides details on Dojo Mobile widgets and components for building the UI, making Ajax calls and REST API calls in the logic layer, and using various offline storage options in the data access layer. It also discusses performance techniques like minimizing reflows and using JSON over XML for data exchange.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Generative AI leverages algorithms to create various forms of content
Metaverse and Digital Twins on Enterprise-Public.pdf
1. Metaverse & Digital Twins
在企業的應用與建置
Tommy Wu (吳志忠) , IoT Solution Architect
Microsoft , Global Partner Solutions
2. Consumer Metaverse Enterprise Metaverse Industrial Metaverse
Microsoft Enterprise & Industrial Metaverse
Different use cases target different domains
Facebook Focus
Microsoft Mesh Focus
Azure IoT & Customer Innovation Team
4. Physical World
Azure IoT
Azure Digital Twins
Azure Maps, Indoor
Azure Synapse Analytics
Azure AI & Microsoft Project Bonsai
Power Platform
Microsoft Mesh & HoloLens
Metaverse technology stack
5.
6. Digital Twin applications in manufacturing
Configuration
Management
Asset
Management
Process
Control
Performance
Management
Simulation
Modeling
Priority Scenarios
Product
[Connected Product
Innovation]
Factory
[Factory of the Future]
Supply Chain
[Intelligent Supply Chain]
Spaces
[Smart Buildings]
ISV Partners SI Partners
7. Process Control
Digital Capabilities across the Enterprise
Turbine 3 Power Plant
Turbine 1 Turbine 2
Performance Mgmt
O SN #44
BSN #7
H
K
L
R
S
A
Q SN #71
O SN #44
SN #6
H
K
L
R
S
Q SN #71
A
O SN #AB
H
K
L
R
S
SN #8
Q SN #71
A
Configuration Mgmt
Simulation
Configuration Mgmt
Asset Mgmt
Process Control
Performance Mgmt
Service change
J
C
D
G
T
J
C
D
G
T
C
D
G
T
J
F
Simulation
F
Fuel Pump
Asset Mgmt
SN #97
F SN #98
F SN #99
F
11. Model any environment, connect sensors and business systems to the model.
Control the present, track the past and predict the future.
Azure Digital Twins
13. Azure Digital Twins
REST
API
External Compute
Handles business logic and data processing
Client Apps
Manage models and the digital twins graph
Digital Twins
Definition
Language
A Z U R E D I G I T A L
T W I N S G R A P H
IoT Hub
Workflow integration
(e.g. Logic Apps)
Business systems/services
integration via REST APIs
Workflow integration
(e.g. Logic Apps)
Cold Storage
Azure Data Explorer
Analytics
Create next generation IoT solutions that model the real world
14. Open Modeling
Language
Live Execution
Environment
Input from IoT &
Business Systems
Output to TSI,
Storage & Analytics
{
"@id": “dtmi:example:Station;1",
"@type": "Interface",
"extends": “dtmi:example:Room;1",
"contents": [
{
"@type": "Property",
"name": “isOccupied",
"schema": "boolean“
},
{
"@type": “Property",
"name": “hasAVSystem",
"schema": “boolean“
},
{
"@type": "Property",
"name": “capacity",
"schema": “integer“
}
],
"@context": "dtmi:dtdl:context;2"
}
Azure Digital Twins
Model any environment, connect sensors and business systems to the model.
Control the present, track the past and predict the future
▪ Create custom domain models using “Digital Twins Definition Language” (DTDL)
▪ Models describe twins in terms of
▪ Telemetry
▪ Properties
▪ Commands
▪ Relationships
▪ Components
▪ Models define semantic relationships to connect twins into a knowledge graph
▪ Models can specialize other twins using inheritance
▪ Digital Twins Definition Language is aligned with
▪ IoT Plug and Play
▪ Time Series Insights data model
ADX,
15. Open Modeling
Language
Live Execution
Environment
Input from IoT &
Business Systems
Output to TSI,
Storage & Analytics
Azure Digital Twins
Model any environment, connect sensors and business systems to the model.
Control the present, track the past and predict the future
▪ Create a live execution environment from the DTDL models in
Azure Digital Twins
▪ Twin instances and relationships form a live graph representation
of the environment
▪ Use a rich event system to drive business logic and data
processing. Use external compute such as Azure Functions
▪ Extract insights from the live execution environment with a
powerful query API
▪ Query using rich search conditions, including property values,
relationships, relationship properties, type information and more
DTDL
Azure Digital Twins
Azure Digital Twins Graph
Zone 1
Track 1 Track 2 Track 3
Station 1
Region 1
Train 1
Switch 1
Access
Gate 1
Access
Gate 2
ADX,
16. Open Modeling
Language
Live Execution
Environment
Input from IoT &
Business Systems
Output to TSI,
Storage & Analytics
Azure Digital Twins
Model any environment, connect sensors and business systems to the model.
Control the present, track the past and predict the future
▪ Use IoT Hub to connect to IoT and IoT Edge devices to keep the live
execution environment up to date
▪ Use a new or an existing IoT Hub (IoT Hub is no longer internal to
Azure Digital Twins)
▪ Drive ADT from other data sources using REST APIs or create a Logic
Apps connector
Azure Digital Twins Graph
Zone 1
Track 1 Track 2 Track 3
Station 1
Region 1
Train 1
Switch 1
Access
Gate 1
Access
Gate 2
REST
API
ADX,
Azure Digital Twins
17. Open Modeling
Language
Live Execution
Environment
Input from IoT &
Business Systems
Output to TSI,
Storage & Analytics
Cold Storage
Historical
Actions
Analytics
Azure Digital Twins
Model any environment, connect sensors and business systems to the model.
Control the present, track the past and predict the future
▪ Use event routes to send data to downstream services
via Event Hub, Event Grid or Service Bus
▪ Connect Azure Digital Twins to Azure Data Explorer to
track time series history of each node
▪ Store data in Azure Data Lake, analyze data with Azure
Synapse and other Microsoft data tools for analytics,
integrate workflow with Logic Apps
Azure Digital Twins Graph
Zone 1
Track 1 Track 2 Track 3
Station 1
Region 1
Train 1
Switch 1
Access
Gate 1
Access
Gate 2
REST
API
ADX,
Azure Digital Twins
20. Babylon.js includes updated support for WebXR. This
exciting new standard allows developers to easily
create compelling cross-browser AR/VR web
experiences
Babylon.js: Powerful, Beautiful, Simple, Open - Web-Based 3D At Its Best (babylonjs.com)
22. UI Modeling with Babylon.js – Azure Digital Twins Model
• Model your data as Digital Twins Graph • Update Model Properties by IoT Sensors
23. UI Modeling with Babylon.js – WebXR in Hololens
You can view WebXR experiences in Windows Mixed Reality with the new Microsoft Edge and Firefox Reality
const xr = await scene.createDefaultXRExperienceAsync({
floorMeshes: [env.ground]
});
Render your App in Hololens 2
XR Support
Rendering Effect in Hololens 2
26. Connected Highway
Coffs Harbour Roadway in Australia
Need: Access to sensor data to monitor
health of roadway infrastructure
Problem: Large amounts of unstructured data
from disparate systems
Solution: Digital twin to visualize streaming
data and alert operators when
actions need to be taken
Benefits: Safer roadways with lower cost and
more efficient maintenance
28. Smart Buildings: Real Estate Core
▪ Partnered with RealEstateCore (OSS)
▪ https://github.com/Azure/opendigitaltwins-
building
Smart Cities: ETSI NGSI-LD
▪ Extend through community contribution
▪ github.com/Azure/opendigitaltwins-smartcities
Domain-specific Ontologies to get started
Open-Source RDF/OWL to DTDL sample converters
29. Digital Twins Consortium
Founders and Groundbreakers
Founders
Air Force Research Laboratory CodeData Healthskouts LUNO UAB Systems Analytics Solutions
Animated Insights Connector Geek Ltd IIMBE Lux Modus Ltd. Transforma Insights
Asset Management Lab, LLC ConstruWise, Inc. IOTA Foundation Monash University Trendspek
Association of Asset Management Professionals CumuloCogitus Inc. IOTIFY NSW State Government Twin Building GmbH
Autiosalo Ltd Cybertwin Idun Real Estate Solutions AB Neural Concept University of Melbourne
BEC - Blockchain Engineering Council DIGIOTAI ieLabs Padi LLC UrsaLeo Inc.
BIM6D Consulting DataCities IoT Management Piprate WSC Technology
Bandora Systems e-Magic Inc. imec PropTechNL Willow
Bentley Systems Executive Development Itus Digital Resonai Ynomia
Building 4.0 CRC Gafcon, Inc. Jitsuin, Inc. Ricardo YoGeo, Inc.
Chain Technology Development Co. Limited Geminus.AI LINQ Ltd. Slingshot Simulations
Groundbreakers
31. Scaleand secure your privatemap data usingAzure Maps Creator as yourcopy of record
Azure Maps Creator
API and SDK in support of indoor
map data owners and smart building
applications
Mapping as a Service: automated
CAD processing, multiple level of
details, built-in map styles and
dynamic styling options for IoT
Map Services: render, spatial query
API and more
SDK: integrate indoor with multiple layers and indoor-outdoor experiences
In Public Preview
32. Indoor Map Data Management Experiences
Transform CAD data to maps
Georeference facilities, Categorize rooms and
additional metadata properties
Review CAD data
errors
Create maps with multiple facilities
Author Maps
Point of interest, logical spaces and more
Bulk Import of fixture data
33. Examples of supported Smart Building Solution Experiences
Facility Managers
Queries (show all mid-size meeting rooms, ramps)
Replay IoT data, aggregate, monitor live
Asset Tracking/Guests/VIP experiences
Use indoor asset location to track assets, define and
monitor geofences and trigger business logic
Help users find and reach
point of interest
(not in public preview)
34. Linking reference and operational data
Correlate space with other related systems’ live data
Devices
(Occupancy, Temperature, …)
Microsoft Graph
Free/Busy, Book Now, …
Vision Modules
People Count, People
Tracking, …
Location
COSINE 802.11mc, Beacons, …
Azure Maps
Azure Digital Twins
Thigs-Topology, Ontology,
…
Customer solutions
Other Sources
Live Maps
Asset Tracking/geofencing/…
Spatial Queries
Device - space relationships,
augment and aggregate data
38. Azure AI
Sense. Plan. Act.
• Perceive and asses the system’s state
• Create intelligent recommendations
• Activate autonomous systems across
processes and equipment
39. Azure Spatial Analysis AI Service
The spatial analysis container enables you to analyze real-time streaming video to understand spatial relationships
between people, their movement, and interactions with objects in physical environments
• Counts people in a designated zone in the camera's field of view
• Tracks when a person crosses a designated line in the camera's field of view.
• Tracks when a person crosses a designated line in the camera's field of view.
• Tracks when people violate a distance rule.
40. Classified as Microsoft Confidential
Azure Percept
Audio
Azure Percept
Vision
Azure Percept
Trust Module
41. Classified as Microsoft Confidential
Delightful onboarding
Integrated experiences
No code flow
Advanced flow
Prototype and deploy
Seamlessly build and manage edge AI solutions
42. Automotive /
Transportation
Factory automation
Cabin intelligence
Driver distraction
Passenger detection
Conversational AI
Command & control
Sensor data efficiency
Manufacturing
Predictive
maintenance
Field service
Worker safety & loss
prevention
Factory automation &
defect detection
Incident response
Automated supply
chain & assembly
Retail
Space & assortment
Traffic patterns
Personalization
Inventory
management
Shrinkage reduction
Optimal product
placement
Smart City/
Buildings
Security & surveillance
Access control via
custom command
Energy management
Transportation &
traffic management
Utilities management
Monitoring &
workplace safety
Healthcare
Patient recognition &
monitoring
Supply chain &
operational efficiency
Identification of
patient issues
Waiting room
prioritization
Scheduling &
reminders
43. Time spent in a queue Vehicle detection with parking stall alerting
Dangerous zone detection
Security and surveillance
46. Most comfortable and
immersive mixed reality
experience available
Largest ecosystem of 1st & 3rd
Party mixed reality solutions
The reliability, security, and
scalability of cloud and AI
services from Azure
47. Vision
Hearing
Speech
Mobility
Blind on one or both eye, amblyopia, color blind,
low peripheral vision, low contrast, limited field of
view in progressive lenses
Deaf or decreased hearing on one side or both,
limited hearing in certain frequencies
Mute, language/accent, speech aid like
electrolarynx user/voice amplifier, speech disorder
Wheelchair user, neck injury
Permanent
Missing or damaged Rx glasses, device display
issues (brightness, color), injury
Blocked by other communication device or ear
protection, muted audio volume
Face mask, sore throat, post dental surgery
Injury, fatigued, arthritis, surgery recovery
Temporary
Low visibility environment (factory or exhibition hall
that is too bright), outdoor, distracted, fog, dirty
lens
Noisy environment, broken headset speaker, quiet
location
Noisy environment, quiet location, broken mic
Tight environment, environmental changes
Situational
Cognitive Dementia, ADHD, Mild Cognitive Impairment Injury, stressed, fatigued, medicated state Multi-tasking, instructor in classroom, demo in
crowded environment
Mixed Reality Persona Spectrum
Hand Missing arms or fingers Injury, fatigued, arthritis, surgery recovery Hands are occupied, broken input device,
gloves/hand protection
48. Multi-user construction visualization
Building Mixed Reality Experiences
Immersive marketing and communications 3D Mapping and planning with geospatial data
IOT data visualization Mixed reality training systems Interactive installation design
49. Design Monitor Operation
Mixed Reality Metaverse Application Design Flow
Microsoft Mesh Azure Digital Twins Remote Assist
Azure IoT Data Explorer
Spatial Anchor
Teams
Spatial Map
Holographic Guides
Vision AI
50. Here can be anywhere
Feel presence Connect from anywhere
Experience together
51. Accelerate development of collaborative
Mixed Reality solutions with AI powered
tools.
Reach users on multiple platforms and
devices.
Scale apps confidently by benefitting
from Azure’s global infrastructure that
powers Mesh.
Immersive Presence Spatial Maps
Holographic Rendering Multiuser sync
Core Capabilities
56. Azure Spatial Anchors
56
Azure Spatial Anchors
Azure Spatial
Anchors SDK
(Android,
iOS,
Hololens,
Linux (new!))
Session:
Image features,
image poses
Query Returns:
relative anchor
6 DoF pose
Query: anchor ID
Create Anchor:
desired relative pose
Create Anchor Returns:
anchor ID
Images,
poses from
AR
Image
features,
poses from
Head
Tracking
Undistorted
images,
poses from
own SLAM
system
57. Robots of the Future
Now: mostly logistics
(move from A to B) Future: robots with spatial intelligence
Warehouse Search and Rescue
Construction
Future: humans and robots working together
58. Retail Store Scenario
• Store Shelf Design
• Virtual Interior Design
• Retail IoT Monitoring
• Warehousing
60. MR AI Model Training and Identification
Model Training
Custom vision
Object Anchor
Label&Training
MR Toolkit UI Render
Object Detect + Object Tracking
IoT Edge
Inference
61. NVIDIA Isaac Sim
Azure Digital Twins
A Z U R E D I G I T A L
T W I N S G R A P H
Data Model Twin
IoT Hub
with Digital Twins in Simulation
63. MRTK – Mixed Reality ToolKit for MR development
• Provides the cross-platform input system and
building blocks for spatial interactions and UI.
• Enables rapid prototyping via in-editor
simulation that allows you to see changes
immediately.
• Operates as an extensible framework that
provides developers the ability to swap out
core components.
• Supports a wide range of platforms,
microsoft/MixedRealityToolkit-Unity: Mixed Reality Toolkit (MRTK) provides a set of components and features to accelerate cross-platform MR app development in Unity. (github.com)
65. MRTK Pre-built UI Block - Prefabs
• The MRTK Toolbox is a Unity
editor window utility that makes
it easy to discover and spawn
MRTK UX prefab components
into the current scene.
• Items can be filtered in view by
using the search bar at the top of
the window.
• The toolbox window is designed
to spawn MRTK out-of-box
prefabs into the current scene
68. Dynamics 365 Business Applications
Empower employees and optimize operations with
Technicians solve problems in real-time with the
help of remote experts
Managers walk the job site without being on site
Remote Assist Guides
More quickly train/upskill employees
with hands-on learning
Analyze data to optimize business processes
71. Customer use cases
EDGE creates a new
generation of innovative,
healthy and sustainable
buildings.
The EDGE software platform
delivers advanced data
analytics through simple user
interfaces.
The Wizata Platform
empowers the manufacturing
industry to drive its digital
transformation.
It brings together Digital Twin,
Data Explorer and AI Solution
Builder functionality.
Bosch delivers Smart
Solutions and Services for
commercial buildings
By applying semantic models
in the Digital Twins service,
Bosch gains powerful insights
cross domains for a wide
range of building types
WillowTwinTM enables owners
and operators of infrastructure
to manage with greater
efficiency.
It drives operational
improvements at scale and
provide their occupants or
users with an enhanced
experience.
72. Partner use cases
Twin Builder: Physics-Based
Digital Twins
Ansys used Azure Digital
Twins to make it even easier
to deploy physics-based
Digital Twin models for
enhanced predictive and
prescriptive maintenance of
physical assets and
equipment.
iTwin: Infrastructure Digital
Twins
Benefiting from Microsoft
Azure Digital Twins, Bentley’s
iTwin users can now rapidly
process and make sense of
huge amounts of sensor data,
produce critical insights, and
gain quick decision
making capabilities.