Table of Contents
Technological Advances Accelerate Digital Twin Adoption
SMART MANUFACTURING
Smart Cities
INTELLIGENT BUILDINGS
Home Technology peripherals AI How digital twins and artificial intelligence can power a sustainable future

How digital twins and artificial intelligence can power a sustainable future

Apr 12, 2023 pm 03:04 PM
AI digital twin

How digital twins and artificial intelligence can power a sustainable future

Sustainability is a top priority for all organizations today – for example, a third of Europe’s largest companies have committed to net-zero emissions by 2050, according to Accenture. However, the company also found that companies must significantly accelerate their efforts over the next decade, as only 9% of companies are currently on track to achieve this goal.

One way organizations can reach net zero and address other sustainability efforts is through the combined power of digital twins and artificial intelligence. These technologies provide businesses with unparalleled insights into their operations, which can inform sustainability improvements and help them achieve their climate goals. For example, digital twins can be used to test various scenarios and help companies determine the best strategies to reduce energy consumption and emissions.

Technological Advances Accelerate Digital Twin Adoption

Of course, digital twins are already being deployed in a variety of ways. For example, helping healthcare researchers create highly accurate models of hearts, lungs or other organs to improve clinical diagnosis, education and training. The energy industry also offers many use cases for digital twins, including building digital models to guide oil drilling efforts in real time.

But recent technological advances in simulation and modeling capabilities, increased deployment of IoT sensors, and more widely available computing infrastructure mean businesses can increase their reliance on digital twins. When organizations use AI to enhance digital twins, they can realize additional benefits—for example, running simulations to investigate “what-if” scenarios and gain a deeper understanding of cause-and-effect relationships.

There are many examples of how these technologies enhance operations, including their ability to inform a greener world. With that in mind, here are some use cases that demonstrate how digital twins and AI can drive sustainability improvements across industries.

SMART MANUFACTURING

By 2025, 89% of IoT platforms will include digital twins, transforming how industrial and manufacturing facilities operate and providing fine-grained insights to enhance sustainability s hard work. Examples include:

  • Investigate ways to reduce energy consumption by gaining a deeper understanding of where energy losses occur
  • Use predictive analytics to determine how to reduce emissions by making various changes
  • Conduct risk assessments to identify operational weaknesses that could lead to incidents with environmental impact

GE Digital is an organization pioneering the use of digital twins and artificial intelligence to improve sustainability . Through its autonomous tuning software, the company creates a digital twin of the gas turbine to find optimal flame temperatures and fuel splits. The technology senses environmental and physical degradation changes in real time, facilitating automatic adjustments to ensure the gas turbine operates efficiently with low emissions and noise levels. Through this technology, the power plant can reduce carbon monoxide by 14% and nitrous oxide emissions by 10% to 14%.

Smart Cities

Urban planning, management and optimization is another area poised to be transformed by the combined power of digital twins and artificial intelligence. These smart cities offer many benefits – solving food insecurity, increasing mobility and helping identify criminal activity, to name a few. Smart cities also have a lot to offer in the form of addressing the Sustainable Development Goals.

With digital twins and artificial intelligence, city governments can understand, quantify and predict the environmental impact of their decisions, and test potential scenarios to determine which ones are best for the environment.

For example, in the UK, Transport for London (TfL) is using digital twins to collect data on noise, heat and carbon emissions across the entire Tube network. Before the technology was deployed, TfL staff could only inspect assets when the tube was closed between 1am and 5am. With the real-time network access provided by digital twins, TfL can now assess locations throughout operating hours and uncover data previously undetectable to the human eye, such as faults and thermal noise hotspots. Officials believe the project will form a key component in London's ambition to achieve a zero-carbon rail system by 2030.

As carbon neutrality becomes a priority for cities around the world, the use of digital twins and artificial intelligence is expected to increase.

INTELLIGENT BUILDINGS

Just as digital twins and artificial intelligence can help cities become more sustainable, they are increasingly being used to create smart buildings. These technologies ensure sustainability is top of mind from the outset, enabling construction managers and other stakeholders to develop virtual representations that can assess a building’s expected carbon footprint during the design phase.

This is the approach developers took when designing the Hickman Tower in London, which has become the first building in the world to receive a SmartScore Platinum rating. During construction, the digital twin connects to the building management system through various sensors, providing a comprehensive view of data such as occupancy, temperature, air quality, light levels and energy consumption. Not only does this enable developers to optimize energy performance and reduce carbon emissions, it also sets the framework for future sustainability enhancements, as these can first be simulated through Hickman’s numerical models.

Regulatory pressure is increasing on the construction industry to design greener buildings, so we can only expect more developers to follow the Hickman Tower’s lead and look to address sustainability issues before breaking new ground.

Over the past few years, becoming a more sustainable industry and ultimately one planet has been an elusive goal. But with recent advances in artificial intelligence and the growing popularity of digital twins, this vision may become a reality. Now is the time for organizations to harness the combined power of these technologies to gain insights at every stage of operations that will support a more sustainable, less carbon-intensive economy at a micro level – and a greener world overall.

The above is the detailed content of How digital twins and artificial intelligence can power a sustainable future. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
Will R.E.P.O. Have Crossplay?
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Jun 28, 2024 am 03:51 AM

This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Context-augmented AI coding assistant using Rag and Sem-Rag Context-augmented AI coding assistant using Rag and Sem-Rag Jun 10, 2024 am 11:08 AM

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Jun 11, 2024 pm 03:57 PM

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

Seven Cool GenAI & LLM Technical Interview Questions Seven Cool GenAI & LLM Technical Interview Questions Jun 07, 2024 am 10:06 AM

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

Five schools of machine learning you don't know about Five schools of machine learning you don't know about Jun 05, 2024 pm 08:51 PM

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework Jul 25, 2024 am 06:42 AM

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time Jul 17, 2024 pm 06:37 PM

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S

SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc. SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc. Aug 01, 2024 pm 09:40 PM

According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year

See all articles