AI and digital twins enable cities to anticipate and respond to crises by providing predictive analytics and virtual simulations of infrastructure performance, shifting from reactive maintenance to proactive, data‑driven resilience.
The cities of the future will not only be strong but also resilient, anticipating disruptions well before they happen and maintaining service continuity even under dire circumstances. As infrastructure becomes increasingly interconnected, the risks also increase. From extreme weather and ageing assets to cyberthreats, supply chain disruptions and geopolitical uncertainty, these challenges are essentially reshaping how infrastructure projects are planned, designed and operated.
These shifts have prompted developers to rethink the true definition of resilience across infrastructure assets.
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Debu Chakraborty, Senior Regional Director, MEA, Bentley Systems
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Traditionally linked to only the physical strength of built assets and their ability to withstand stress, true resilience now indicates critical infrastructure’s capacity to anticipate issues, adapt in real time and continue delivering essential services even when the unexpected occurs.
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The focus therefore needs to shift from building stronger infrastructure to building smarter, more predictive infrastructure, leveraging advanced technologies such as AI and digital twins to prepare cities for crises even before they occur.
As cities grow complex, traditional approaches to infrastructure management become less effective. However, many infrastructure operators still follow scheduled inspections and respond only after a fault has already occurred. This ultimately leads to costly repairs, service disruptions and increased risks to public safety. AI empowers property owners to prevent this by identifying potential issues well before they escalate into major failures.
Recognising this, the UAE is expanding its transport networks and scaling smart cities, while investing in clean energy, utilities and digital infrastructure. At the heart of this vision are ambitious national initiatives such as the Dubai Economic Agenda (D33) and UAE Net Zero 2050, guided by which the nation is also laying the foundation for long-term economic development.
AI leverages real-time data from connected assets to analyse patterns, detect anomalies and predict when maintenance might be required. This enables operators to prioritise repairs, optimise resources and minimise unplanned downtime, ensuring that critical services remain operational even during periods of disruption.
Debu Chakraborty, Senior Regional Director, MEA, Bentley Systems
However, the true value of AI extends beyond this. It empowers city authorities to move from reactive maintenance to proactively preparing for disruptions. When combined with predictive analytics, AI enables decision makers to analyse how infrastructure is likely to perform under different scenarios, allowing them to make faster, more informed decisions before a crisis unfolds.
Digital twins support this by providing a conducive environment for the practical application of AI. A digital twin is much more than just a 3D model – it is a dynamic, data-driven representation of a physical asset that continuously reflects its real-world conditions throughout its lifecycle.
By integrating engineering, operational and sensor data, digital twins allow infrastructure owners to simulate how assets will perform under diverse scenarios. Whether preparing for floods, extreme heat, transport disruptions or utility failures, city authorities can test response strategies in a virtual environment, understand how failures may cascade across interconnected systems and make informed decisions without disrupting real-world operations.
The shift from reactive crisis management to predictive scenario planning enables infrastructure operators to respond swiftly with confidence and seamless coordination in the face of disruptions. As cities continue to expand and evolve, engineers should leverage AI and similar digital technologies to evaluate how infrastructure will perform over its entire lifecycle. This is key to building resilient buildings of the future rather than simply designing for today’s requirements.
Predictive modelling and simulation empower project teams to assess how assets will respond to changing environmental conditions, increasing urban populations, evolving mobility patterns and unexpected disruptions. It further enables designers to optimise infrastructure before construction begins, reducing carbon footprints, future operational risks and improving long-term resilience. The focus should shift from merely developing an asset to determining whether it can continue performing reliably over the next several decades despite an increasingly uncertain operating environment.
Resilient infrastructure depends on both strong physical assets and reliable information flow. During an emergency, multiple stakeholders, from infrastructure operators and government agencies to emergency responders and utility providers, need to coordinate and make quick decisions. This becomes difficult when there is a lack of access to accurate and connected data.
Within a connected data environment, all stakeholders are provided with a single, reliable source of truth across the infrastructure life cycle. Moreover, by integrating engineering, construction and operational information in one place, decision makers can gain greater visibility into asset conditions, ongoing risks and system-wide impacts, enabling faster and more coordinated responses during periods of disruption.
However, with infrastructure systems becoming increasingly interconnected, reshaping data silos has become just as important as strengthening physical infrastructure. This is because modern cities rely on interconnected networks, from airports, ports, water networks and power grids to telecommunications infrastructure; all rely on one another and a single disruption in one system can quickly escalate into a much wider issue. It is high time that data is treated as a strategic asset like any other physical assets.
Debu Chakraborty, Senior Regional Director for MEA, Bentley Systems
In such a scenario, AI and digital twins empower infrastructure operators to continuously monitor these assets, predict maintenance requirements, optimise operations and identify vulnerabilities, to prevent possible service disruptions. This shift towards predictive operations also helps reduce downtime, improve public safety and ensure that essential services continue functioning even during periods of uncertainty.
It is evident that the objective isn’t to simply prevent infrastructure failures anymore – it is to maintain the continuity of critical services when communities need it the most. Furthermore, as the frequency and complexity of disruptions continue to increase, cities can no longer choose to respond only once the crisis has already unfolded. AI, digital twins and predictive analytics support this by providing governments with the tools to anticipate risks, evaluate different scenarios and make better decisions before problems escalate.
In particular, as nations like the UAE heavily invest in smart cities and next-generation infrastructure, it is critical to embed AI into physical assets as a means to ensure long-term resilience, sustainability and economic growth. Ultimately, the cities that thrive in the future will not simply be those with the newest infrastructure, but those that are equipped to continuously adapt and respond to changes through data-driven decision-making.
The global conversation on artificial intelligence has reached a decisive inflection point. After the recent developments at Anthropic and other leading AI laboratories, the world is confronted with a profound question: What kind of AI future do we truly need? For many in the Global North, the instinctive response has been to call for slower development, tighter controls, and more cautious experimentation.
Yet for developing nations—particularly across Africa, Asia, Latin America, and the Caribbean—this narrative is not only insufficient, but it is fundamentally misaligned with their urgent developmental realities.
What is required now is not deceleration, but decolonisation of AI development, equitable access to AI infrastructure, and a global framework that empowers developing nations to harness artificial intelligence as a catalyst for economic transformation and sustainability.
Artificial intelligence is no longer a futuristic abstraction; it is the engine driving productivity, innovation, and competitiveness in the twenty first century. To deny developing nations equitable access to this engine is to entrench a new digital hierarchy—one that mirrors the colonial structures of the past but with far more devastating consequences.
As Professor Ojo Emmanuel Ademola argues, the next frontier of global justice lies not in slowing AI down, but in democratising its development and ensuring that every nation has the tools to shape its own digital destiny.
The post Anthropic moment: A global reckoning
The recent turbulence within Anthropic has exposed a deeper truth about the global AI ecosystem: it is dominated by a small cluster of actors whose decisions reverberate across continents. This concentration of power is neither accidental nor benign. It reflects a broader pattern in which technological innovation is centralised in the Global North, while the Global South is relegated to the periphery as consumers rather than creators.
This imbalance is not merely technical; it is geopolitical. AI systems are increasingly shaping governance, security, finance, education, agriculture, and healthcare. When developing nations lack access to foundational models, compute infrastructure, and AI research ecosystems, they become dependent on external technologies that may not align with their cultural, economic, or political realities. The result is a new form of digital dependency—one that risks undermining sovereignty and stifling local innovation.
The post Anthropic moment therefore demands a global reckoning. It is time to confront the uncomfortable truth that AI development, as currently structured, is reproducing colonial patterns of exclusion.
Slowing AI development does nothing to address this imbalance. Decolonising AI does.
AI as an instrument of economic liberation
For developing nations, artificial intelligence is not a luxury. It is a lifeline. The potential applications are vast and transformative. In agriculture, AI can optimise crop yields, predict climate patterns, and reduce post harvest losses. In healthcare, AI can
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diagnostic capacity, support telemedicine, and strengthen disease surveillance.
In education, AI can personalise learning, expand access to quality instruction, and bridge rural urban divides. In governance, AI can enhance transparency, streamline public services, and combat corruption.
These are not theoretical possibilities; they are practical imperatives. Developing nations face structural challenges—limited industrial capacity, infrastructural deficits, and constrained fiscal space—that AI can help overcome.
But this requires access to AI tools, not restrictions. It requires investment in local AI talent, not dependency on foreign expertise. It requires sovereign AI frameworks, not imported digital architectures that fail to reflect local contexts.
Economic liberation in the 21st century will be driven by digital capability. Without equitable access to AI, developing nations risk being locked out of the global economy’s most dynamic sectors.
Decolonising AI is therefore not merely a moral argument; it is an economic necessity.
The ethical imperative: AI must reflect global diversity
Artificial intelligence is shaped by the data it consumes and the perspectives embedded within its design. When AI systems are trained predominantly on Western data, Western languages, and Western cultural assumptions, they inevitably reproduce Western biases. This creates a profound ethical challenge: AI becomes a mirror of the Global North, rather than a reflection of global humanity.
Decolonising AI means ensuring that developing nations have the capacity to build models that reflect their own languages, cultures, histories, and values. It means empowering African researchers to build AI systems that understand Yoruba, Swahili, Hausa, and Amharic.
It means enabling Asian researchers to develop models that reflect the nuances of Hindi, Mandarin, and Bahasa Indonesia. It means supporting Latin American researchers to create AI systems grounded in their social realities.
Ethical AI cannot exist without diverse AI. And diverse AI cannot exist without decolonised AI development.
The geopolitical stakes: Sovereignty in the digital age
In the digital age, sovereignty is no longer defined solely by territorial borders. It is defined by control over data, algorithms, and digital infrastructure. Nations that lack AI sovereignty will find themselves increasingly vulnerable to external influence—whether through imported technologies, algorithmic decision making, or digital surveillance architectures.
Decolonising AI is therefore a matter of national security. Developing nations must build their own AI ecosystems, establish their own regulatory frameworks, and cultivate their own digital talent pipelines.
They must invest in sovereign cloud infrastructure, national AI research institutes, and regional AI collaboration networks.
The geopolitical stakes are clear: nations that control AI will shape the future. Nations that do not will be shaped by it.
A new global framework: Equitable access, shared responsibility
The world needs a new global framework for AI development—one that prioritises equity, sustainability, and shared responsibility. Such a framework must include equitable access to compute infrastructure, ensuring that developing nations can train and deploy advanced AI models. It must support open and collaborative research ecosystems that enable cross border innovation and knowledge exchange. It must invest in local AI talent through scholarships, research grants, and regional AI academies. It must encourage indigenous AI development so that local languages, cultures, and contexts are represented in global AI systems. And it must promote sustainable deployment strategies aligned with climate resilience, economic inclusion, and social justice.
This is not charity; it is global responsibility. The future of AI must be built by all nations, not a privileged few.
Conclusion
The world stands at a crossroads. After Anthropic, the debate must shift from slowing AI down to democratising its development. The Global South cannot afford to be spectators in the AI revolution. They must be architects of their own digital futures. Decolonising AI is not a slogan; it is a strategic imperative for global equity, economic development, and sustainable progress.
Artificial intelligence will define the next century. The question is whether it will be a tool of liberation or a new instrument of digital colonialism. The answer depends on whether the world chooses caution over justice, restriction over inclusion, and centralisation over shared prosperity.
Professor Ojo Emmanuel Ademola asserts that the time has come for a new global compact—one that recognises AI as a universal right, not a privileged asset. The future belongs to nations that embrace AI boldly, ethically, and inclusively. Decolonising AI is the path to that future.
Ademola is first African Professor of Cybersecurity and Information Technology Management, Global Education Advocate, Chartered Manager.
Fake Webometrics University Rankings (WURs) are targeting universities in the Global South, leading to the rise of dissemination of inaccurate ranking data through news outlets and consulting agencies.
But they have remained largely obscured from the European academic community due to Geo-IP masking tactics, which necessitate the adopting of institutional measures to enhance vigilance and safeguard the integrity and authority of academic rankings.
This is the outcome of a study that provided a comprehensive analysis of the fake Webometrics University Rankings (WURs) phenomenon observed in the first half of 2026 after investigating 300 publications gathered from 39 countries between 6 January and 6 July 2026.
Titled “Fake Webometrics University Rankings: Network expansion, Geo-IP cloaking, and institutional vulnerabilities in the global south”, the study was published on 18 August in Preprints.org – a free multidisciplinary platform providing a preprint service dedicated to making early versions of research outputs permanently available and citable.
The author of the study, independent researcher and consultant Dr Vladimir Moskovkin, said: “This study moves beyond identifying isolated web scams; it documents an aggressive, transnational ‘metric chimera’ economy”.
Moskovkin is the former director of the Centre for the Development of Publication Activity at Belgorod State National Research University, Russia, where he was also a professor in the university’s Department of World Economy.
He told University World News he was able to confirm obscuration in Europe because that is where he is based – in the Czech Republic – but he believes the fake rankings are also obscured in other developed countries, such as the US, Canada, Australia and New Zealand, and surmises that the information campaigns involving fake rankings were targeted exclusively at countries in the Global South.
“The evolution from simple fake website clones (spring 2025/early 2026) to complex ‘July 2026 new wave’ domains (webometrics.one, webometrics.top, webometric.org) indicates that perpetrators are highly adaptive,” Moskovkin pointed out.
“By exposing how fake domains bypass European detection through Geo-IP masking and successfully penetrate official state documents and international recruitment portals (like SMAPSE or BAYHOST), the research highlights a systemic threat to the integrity of global higher education,” Moskovkin indicated.
“The scammers configured the server so that the fake webometrics.org content was displayed only to users from specific regions (South-East Asia, the Middle East, and Africa) – areas where the demand for rankings is highest and vigilance is lower,” Moskovkin pointed out.
“Therefore, safeguarding higher education requires a coordinated global response involving researchers, media watchdogs, and state accreditation bodies,” Moskovkin stressed.
Phenonomon driven by technologies
Moskovkin said: “The study reveals that approximately 65% of cases involving the dissemination of inaccurate ranking data were initiated by news outlets and consulting agencies.”
He noted that this proves that the phenomenon is “largely driven by PR technologies and information aggregation, rather than isolated errors by universities themselves”.
“The most striking finding is the pronounced geographical imbalance: 81.3% of fake publications originate from the Global South, with Indonesia acting as the primary epicentre (accounting for over 50% of all recorded publications), followed by Turkey (10.3%), Ukraine (8.7%) and both the Philippines and Egypt (7.0%),” Moskovkin added.
Other countries – totalling 34 countries, 23.3% of publications – include developing countries such as Montenegro, Jordan, Moldova, Uganda, and Yemen.
“The presence of developed nations (the US, Spain, Israel, the UK, Germany and Canada) is sporadic and associated with local marketing errors or the activity of international consulting and recruitment agencies.
“Overall, this confirms the transnational and opportunistic nature of the fake WUR market, penetrating any region in search of image-driven demand,” Moskovkin indicated.
“This shows that universities in developing regions, facing immense pressure regarding publication performance and rigid KPI/accreditation systems, are uniquely vulnerable to fake rankings and actively exploit them to simulate international prestige,” Moskovkin pointed out.
“Furthermore, the data demonstrates a clear Pareto distribution, where a small number of countries hold the vast majority of ‘fake webometric weight’, creating an institutionalised illusion of global success,” Moskovkin indicated.
Takeaway messages to HE policymakers
Asked about the most important takeaway messages for higher education policymakers and decision makers, Moskovkin said: “Policymakers and university leadership must realise that relying on unverified web metrics for national KPIs, hiring criteria, and institutional benchmarking creates a dangerous feedback loop of misinformation.”
He said ministries of higher education need to establish rigorous, independent audit mechanisms for academic metrics and rely solely on authentic, verified international repositories, such as the official data hosted on Figshare via the Cybermetrics Lab.
“An example of such successful work is the effort of the Center for Civic Education (CCE) in Montenegro, which, based on our research, succeeded in having an erroneous Order of the Ministry of Education, Science and Innovation of Montenegro revoked.
“The Order had been based on the fake webometrics.org ranking when hiring faculty for Montenegrin universities,” Moskovkin pointed out.
He said several actions must be taken to deal with the rise of the fake university ranking systems.
First, he said, official ranking providers and the academic community must take technical and legal action.
“Official providers must implement proactive legal and technical defences, while the academic community must establish global observatories.”
Moskovkin has published several studies and reports about fake university ranking sites in 2026, including the study titled “Pandemic of ‘Predatory’ Rankings: Why academic integrity fails the stress test” and the article titled “Predatory university rankings jeopardise the value of Webometrics”, and is involved in a group of higher education experts which is in the final stage of launching Global Observatory on Academic Metrics and University Rankings (GOAMUR), which will “continuously monitor, expose, and neutralise predatory ranking networks before they distort educational policy and consumer trust”.
Second, strategies identified in the group’s research must be implemented.
“These include the urgent restoration of the official webometrics.info portal as a single source of truth, the enforcement of strict verification protocols that require universities to cross-check any ranking claims solely against authentic repositories (such as the official Figshare archive), and the establishment of global monitoring systems to inform regulators about the geo-targeting tactics used by scammers to bypass detection,” Moskovkin said.
Third, GOAMUR is preparing an open letter to the ministries of higher education and scientific research worldwide, calling on national governments to take direct responsibility for monitoring and sanctioning the use of fake metrics within their own jurisdictions.
“Given the unprecedented, global scale of this academic fraud, it is time for ministries to ensure that institutional ‘prestige’ is not built on digital deception and to hold local universities accountable for upholding academic integrity,” Moskovkin stressed.
A threat to global HE sector
Global higher education expert and director of strategic insights at RMIT University in Australia, Angel Calderon, told University World News: “The continued proliferation of fake global university rankings, alongside the growing visibility of fraudulent or unsubstantiated expertise, is a matter of significant concern for the global higher education sector.
“While strategic geo-targeting is increasingly evident, particularly in emerging economies that are strengthening their higher education systems, it is important to emphasise the need to empower university leaders and the broader academic community to uphold academic integrity and adhere to the ethical principles of responsible scholarly publishing and information dissemination,” added Calderon, who is the author of “Sustainability Rankings: What they are about and how to make them meaningful”.
Proliferation of fake rankings expected
Calderon warned that the proliferation of fake global rankings and fraudulent expertise is unlikely to disappear anytime soon in an era of rapid technological transformation.
“I anticipate that academics and institutions will increasingly become targets of unscrupulous entities seeking commercial gain, as competition for resources intensifies and the pressure to demonstrate institutional relevance grows.
“This underscores the need for continued vigilance against such practices and for sustained efforts to raise awareness among university leaders, policymakers, academics, the media, and society more broadly.”
He said it is imperative to foster greater collaboration between academics in established higher education systems and their counterparts in emerging and developing systems, enabling them to learn from one another while strengthening quality assurance, upholding academic integrity, and promoting responsible academic practice.
Governments should be ‘more active’
“At the same time, national governments should be encouraged to play a more active role in establishing and strengthening frameworks for academic integrity, as well as robust systems for the verification and dissemination of reliable information.”
He said that while many critics contend that global rankings should be discontinued, they are unlikely to disappear anytime soon. Similarly, the pressure on academics to publish is unlikely to diminish in the foreseeable future.
“Ideally, we should reframe the ways in which academic staff are recognised and rewarded by reducing the sector’s reliance on quantitative performance indicators, including bibliometric measures.
“These challenges are complex and unlikely to be resolved easily,” he said.
“Nevertheless, it is important to continue discussions on reforming academic promotion and reward systems to ensure that they more fully recognise the breadth, quality, and impact of academic contributions.”
University World News reached out to the Webometrics Ranking of World Universities, QS World University Rankings, ShanghaiRanking’s Academic Ranking of World Universities and THE World University Rankings for reaction to the study but received no responses.
The field of engineering is undergoing a profound transformation, driven by the rapid advancement of emerging technologies. From AI in engineering to the Internet of Things (IoT), these innovations are reshaping the way engineers approach problem-solving, design, and manufacturing. As the world enters the era of Industry 4.0, it is crucial for aspiring engineers to understand the impact of these technologies and how they will shape the future of the profession.
In this article, we will explore the key emerging technologies that are revolutionizing engineering, including artificial intelligence, IoT, 3D printing, renewable energy, and more. We will also discuss the importance of integrating these technologies into engineering education and the role of academic institutions like Amrita University in preparing students for the challenges and opportunities of the future.
Artificial Intelligence and Machine Learning
AI in engineering and Machine Learning (ML) are at the forefront of the technological revolution. These technologies enable systems to learn from data, make predictions, and improve over time. AI and ML are being applied in various areas of engineering, such as
Automation and Optimization
AI algorithms can analyze complex datasets to enhance efficiency and reduce operational costs in manufacturing. By optimizing processes and automating repetitive tasks, AI is helping engineers streamline operations and improve productivity.
Predictive Maintenance
AI-powered predictive maintenance systems can monitor the health of equipment and infrastructure in real-time, identifying potential issues before they lead to costly breakdowns. This proactive approach improves reliability, reduces downtime, and extends the lifespan of assets.
Design Optimization
AI and ML can assist engineers in optimizing product designs by analyzing vast amounts of data, simulating scenarios, and identifying the most effective solutions. This leads to improved performance, reduced material usage, and faster time-to-market.
Internet of Things (IoT) and Smart Cities
The Internet of Things (IoT) is connecting everyday objects to the internet, allowing them to collect and exchange data. This technology is creating smart environments where devices communicate seamlessly, leading to improved automation and control. In engineering, IoT is being used to:
Infrastructure Monitoring
IoT sensors can monitor the health of bridges, buildings, and other critical infrastructure, providing real-time data on structural integrity, environmental conditions, and potential hazards. This enables engineers to make informed decisions and proactively address maintenance needs.
Supply Chain Optimization
IoT devices can track assets throughout the supply chain, providing visibility and optimizing logistics. By monitoring inventory levels, transportation routes, and environmental conditions, engineers can streamline operations and reduce costs.
Smart City Development
IoT is playing a significant role in the development of smart cities. Engineers are designing IoT systems that facilitate communication between devices, improving overall functionality. Smart cities utilize IoT for traffic management, energy efficiency, and public safety, enhancing the quality of life for residents.
3D Printing and Additive Manufacturing
Additive Manufacturing, commonly known as 3D printing, is transforming product design and manufacturing processes. This technology enables the creation of complex geometries and customized parts with high precision and minimal waste. The benefits of 3D printing in engineering include:
Rapid Prototyping
3D printing allows engineers to quickly create physical prototypes of their designs, reducing development time and enabling faster iteration. This accelerates the product development cycle and facilitates early detection of design flaws.
Customization and Personalization
3D printing enables the production of customized and personalized products tailored to individual needs. This is particularly valuable in fields like medical engineering, where patient-specific implants and prosthetics can be created.
Sustainable Manufacturing
3D printing reduces material waste and enables the use of eco-friendly materials. By producing parts on-demand and minimizing inventory, 3D printing contributes to a more sustainable manufacturing process.
Renewable Energy Technologies
The urgent need to address climate change has driven significant advancements in renewable energy technologies. Engineers are developing innovative solutions to harness solar, wind, hydro, and other sustainable energy sources. The key areas of focus include:
Solar Energy
Engineers are working on improving the efficiency and affordability of solar panels, developing new materials and designs to maximize energy capture. They are also designing smart grid systems to integrate solar energy into existing power networks.
Wind Energy
Advancements in wind turbine technology, such as larger blades and more efficient generators, are increasing the power output and reliability of wind energy systems. Engineers are also developing offshore wind farms to harness the abundant wind resources available at sea.
Energy Storage
The intermittent nature of renewable energy sources requires efficient energy storage solutions. Engineers are developing advanced battery technologies, such as lithium-ion and flow batteries, to store excess energy and ensure a stable supply of clean power.
Preparing for the Future of Engineering
To prepare students for the challenges and opportunities of the future, engineering education must adapt and integrate emerging technologies in engineering into their curricula. Amrita University, one of India’s premier private institutions for higher education and research, is at the forefront of this transformation.
Amrita University offers a dynamic curriculum that undergoes rigorous updates every three years, ensuring alignment with the standards of leading institutions. The university provides a comprehensive education that emphasizes both technical skills and ethical development, preparing students to become knowledgeable and principled professionals.
Moreover, Amrita University maintains strong partnerships with industry leaders such as Microsoft, Infosys, Bosch, and Wipro, creating exceptional placement opportunities for students. These collaborations expose students to real-world challenges and provide hands-on experience with cutting-edge technologies.
Final Thoughts
The future of engineering lies in embracing emerging technologies in engineering such as AI, IoT, 3D printing, renewable energy, and more. These technologies are reshaping industries, driving innovation, and presenting both opportunities and challenges for engineers.
To thrive in this rapidly evolving landscape, aspiring engineers must develop a deep understanding of these technologies and their applications. They must also cultivate a mindset of continuous learning, adaptability, and collaboration.
Institutions like Amrita University play a crucial role in preparing students for the future of engineering. By providing a comprehensive education that integrates emerging technologies, fostering industry partnerships, and emphasizing ethical development, Amrita University equips students with the knowledge, skills, and values necessary to succeed in the era of Industry 4.0.
If you are considering a career in engineering or looking to enhance your skills in emerging technologies, Amrita University offers a wide range of programs tailored to meet the demands of the future. From undergraduate to postgraduate studies, Amrita University provides an exceptional learning environment that nurtures innovation, creativity, and social responsibility.
Frequently Asked Questions
What are the key emerging technologies shaping the future of engineering?
The key emerging technologies in engineering include artificial intelligence (AI), the Internet of Things (IoT), 3D printing, renewable energy technologies, and more. These technologies are transforming various aspects of engineering, from design and manufacturing to infrastructure monitoring and smart city development.
How is AI transforming the field of engineering?
AI in engineering is being applied in areas such as automation, predictive maintenance, and design optimization. AI algorithms can analyze complex datasets to enhance efficiency, reduce operational costs, and improve product performance. AI is also enabling engineers to make data-driven decisions and streamline processes.
What role does IoT play in engineering?
IoT is connecting everyday objects to the internet, allowing them to collect and exchange data. In engineering, IoT is being used for infrastructure monitoring, supply chain optimization, and smart city development. IoT sensors can provide real-time data on the health of assets, optimize logistics, and improve overall functionality.
How is 3D printing revolutionizing manufacturing?
3D printing, also known as additive manufacturing, is transforming product design and manufacturing processes. It enables the creation of complex geometries and customized parts with high precision and minimal waste. 3D printing facilitates rapid prototyping, personalization, and sustainable manufacturing practices.
What should aspiring engineers focus on to prepare for the future?
To prepare for the future of engineering, aspiring engineers should develop a deep understanding of emerging technologies in engineering such as AI, IoT, 3D printing, and renewable energy. They should also cultivate a mindset of continuous learning, adaptability, and collaboration. Pursuing education at institutions like Amrita University, which integrate emerging technologies into their curricula and foster industry partnerships, can provide a strong foundation for success in the era of Industry 4.0.
Statetron has unveiled its Andromean Class™, a new industrial architecture designed to integrate artificial intelligence (AI), robotics, autonomous logistics, energy storage and digital intelligence within a single advanced manufacturing ecosystem.
The company is proposing its first Andromean Class facility in Qatar, with an initial development concept spanning approximately 10 hectares and an architecture designed to support expansion toward multi-gigawatt-scale energy storage manufacturing capacity.
Unlike a conventional battery assembly facility, the proposed development is conceived as an intelligent, energy-integrated industrial platform in which manufacturing, logistics, energy, data and maintenance systems operate as a coordinated ecosystem.
Project Scope
The proposed Qatar facility will integrate AI-driven production, robotic assembly, autonomous material movement, digital-twin technology, automated quality control and intelligent energy management.
At the core of the manufacturing platform will be Statetron’s modular 5 MW Power Block architecture, designed for large-scale energy-storage applications serving utility, industrial, renewable-energy and grid-infrastructure markets.
The manufacturing platform is intended to support configurable energy-storage durations and progressively increase production capacity in line with market demand.
The facility’s architecture will also allow production, automation, logistics and energy infrastructure to be expanded progressively, with the long-term objective of reaching multi-gigawatt-scale manufacturing.
Factory Designed as an Energy System
The Andromean Class concept extends beyond battery manufacturing by integrating renewable energy generation, energy storage and intelligent power management into the facility itself.
Under the concept, energy systems will power the manufacturing operation while the factory produces energy-storage infrastructure, with digital intelligence connecting and optimizing the overall system.
Statetron said Qatar provides a compelling environment for the development, citing the country’s focus on advanced manufacturing, AI, robotics, Internet of Things (IoT), data analytics and clean technologies.
The proposed facility is also intended to benefit from Qatar’s strategic industrial and logistics infrastructure, including the Umm Alhoul Free Zone, which is positioned for heavy manufacturing, logistics and emerging technologies and is located adjacent to Hamad Port.
Statetron’s Andromean Class Vision
Statetron said the Andromean Class represents a new approach to industrialisation in which the factory itself becomes an intelligent and energy-integrated system.
The company aims to replace fragmented manufacturing processes with a continuously connected industrial environment where production, logistics, energy, data and maintenance are optimized together.
Lars Carlstrom, CEO of Statetron, said: “The first industrial revolution mechanised production. The digital revolution connected it. The next era will make industry intelligent, autonomous and energy-native.”
He added: “We don’t want to build another battery factory. We want to build the blueprint for how industry itself will operate in the next decade.”
The proposed Qatar development represents Statetron’s first application of the Andromean Class architecture and is intended to establish a scalable platform for the future manufacturing of large-scale energy-storage systems.
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