With increasingly connected devices, cheaper hardware technologies, citizen science, and social media, more and more datasets are becoming available by the minute. This has led to the creation of a data-rich ecosystem, with both opportunities and challenges on offer. Governments, businesses and societies have significantly benefited from the data explosion through the elevation of data as a critical asset and using analytics and insights to plan and allocate limited resources to achieve operational effectiveness. Some governments have adopted open data strategies to ensure transparency in dealing with their citizens, public service improvements, and innovation. To businesses, data is a new critical asset that has received investment to understand internal bottlenecks. It helps them plan, model, and simulate future events before they even occur.
However, the benefits cannot go without challenges. One of the areas worth noting is cognitive conflict — citizens using the same data to challenge government and business decisions with a different interpretation of the data. This can result in lengthy litigations, causing delays in preliminary project design and delivery. Then there is the issue of data literacy. Organizations and governments have a considerable amount of data to use but are not data literate to exploit and derive meaningful insights to their advantage. Governments, businesses, and societies are to blame for exposing vulnerable groups to attacks and marginalization due to the poor handling of detailed data they have on them. Companies that have considerable wealth can use data to derive insights to control markets and stifle competition. This is the reason why some people are skeptical of Artificial Intelligence (AI) and Machine Learning (ML). Radical critiques of the established order view governments and corporations joining forces to employ digital technology to consolidate and extend their power and influence all aspects of society. Data ethics and innovation should be at the heart of all data initiatives to ensure safe and ethical use of AI and ML, including protection to control abuse.
Data is playing a critical role in repurposing and rejuvenating the life of existing assets, which, by their nature, would have been underutilized. It has helped drive efficiency and productivity gains by making clear patterns and behaviors of people and assets. Data, computation, automation, and analytics are at the core of 4IR. These have helped boost the circular economy model. It has benefited from the cravings of modern society to consume more information, stay connected, be independent, and be heavily assisted by computation and automation. As a result, eBay, Google, Facebook, Uber, Amazon, Twitter, LinkedIn, etc., have sprung up, and their market capitalization outstrips traditional businesses. Their business models are based on democratizing access to information and communication, connectedness, and real-time insights.
A smart energy Digital Twin enables intelligent selection and validation of domestic heat network solutions by incorporating real-world data.
Data is playing a critical role in repurposing and rejuvenating the life of existing assets, which, by their nature, would have been underutilized. It has helped drive efficiency and productivity gains by making clear patterns and behaviors of people and assets. Data, computation, automation, and analytics are at the core of 4IR. These have helped boost the circular economy model. It has benefited from the cravings of modern society to consume more information, stay connected, be independent, and be heavily assisted by computation and automation. As a result, eBay, Google, Facebook, Uber, Amazon, Twitter, LinkedIn, etc., have sprung up, and their market capitalization outstrips traditional businesses. Their business models are based on democratizing access to information and communication, connectedness, and real-time insights.
Digital Twin is a beneficial disruptive technology of our time, and it is an integral and immersive part of our behavior. A Digital Twin integrates vast amounts of static and real-time data to model and predict future events before they even occur. With this capability, it becomes possible to utilize limited resources to achieve desired results. A Digital Twin helps in reducing maintenance costs of assets, improving resource management, making infrastructure more resilient, enhancing project collaboration, and creating an innovative digital environment to solicit community feedback on local issues. One of the core characteristics of a Digital Twin is its ability to model and understand organizational processes. It helps to remove waste, prevents duplication, and leads to increasing productivity and profits. Today, these digital models are also becoming valuable in achieving net-zero carbon target realization. A smart energy Digital Twin enables intelligent selection and validation of domestic heat network solutions by incorporating real-world data.
Transportation: Historically, the transportation sector has benefited hugely from digital twins, especially in aviation. It needs intense data analytics and insights about machine processes and performance due to the safety and reliability requirements for operations. This is also applicable to transportation infrastructure design, modeling, and simulation to understand the impact of transportation network development on the environment, traffic scenario modeling, and simulation of driving scenarios to improve safety on roads, construction costs, passenger analysis, asset lifecycle modeling, travel flows, etc. Recently, automated driving has become a topical issue and has seen significant investments. Digital twins help model environmental scenes and hazard detection to reduce crashes and save lives.
Energy and utilities: A smart energy Digital Twin helps in understanding current and future energy requirements through modeling and simulation with real-life data from sensors. Examples of insights derived through digital twins are hourly, monthly, and annual heat demands using different climatic conditions, building typologies and material composition, and household dynamics. The demand invariably relates to hourly, peak, monthly,
and yearly electricity consumption. The suitable energy technology investment can have a corresponding impact on net-zero realization. Additionally, digital twins in the utility sector perform system feasibility and grid integration analysis, collate and analyze large datasets in real time to design and optimize distribution networks.
Construction: Digital twins provide the tools, data integration (aerial and drone surveys, building models, terrain, sensor data), and the platform to manage a construction site in a virtual environment. This helps visualize all construction activities taking place — who is doing what, where, and when. This also enables stakeholder engagement and collaboration. Further, dashboard insights assist project managers in identifying and resolving risks in real time to minimize delays and optimize costs. Because it is virtual, it facilitates remote access via live video streaming that helps monitoring and coordination from anywhere.
Spatial data represents the Earth (spaces, places, and locations) and its features using geometric and topological constructs for object representation. Hence, it creates digital twins of the built environment and helps integrate diverse datasets to derive insights and patterns from multiple sources. Spatial data and digital twins share similar elements and characteristics: data capture, integration and interoperability, data standards, methods and procedures, automation, computation and analytics, modeling, simulation and prediction, data visualization, communication and sharing, and the technology platform for deployment. These make them intertwined, making spatial data an integral part of the Digital Twin ecosystem.
Engineering 4.0 has seen the advent and widespread application of AI and ML, mass adoption of robotics to replace specific human tasks with precision, connected devices, IoT, digital twins, and Big Data analytics and insights to improve and design spaces. These technologies attempt to mimic almost all the human senses to enhance and create new spaces, making it difficult to distinguish humans from machines. We are in a state of flux, and adoption is happening at great speed. Reality and virtuality are becoming indistinguishable. There is great scope to perfect human behavior in digital twins to create sustainable spaces. We are inching ever closer to human behavior modeling with Edge Computing, Blockchain, Holographic Projections, ML, AI, Virtual Reality, Metaverse and hovering in the horizon is quantum and neuromorphic computing. Currently, facial recognition, image analysis, computer vision, and health informatics are providing advances to help understand and appreciate human behavior. In the UK, the Channel 4 TV series Humans is a must watch, as it explores the themes of AI and robotics, “focusing on the social, cultural, and psychological impact of the invention of anthropomorphic robots called synth”. There is growing adoption and integration of psychological research into computer applications, making it difficult to distinguish choices and decisions made by humans from machines. Humans are not machines because they create machines. Humans make life choices and mistakes; however, machines are programed to follow specific rules without making as many mistakes as possible in developing and using spaces. Even though we strive to model human behavior in devices, we need empathy to achieve greatness. The key challenges to human behavior modeling are emotional intelligence, culture, religion, sex, environment, and life experiences to demonstrate passion, thoughts, and efforts to execute and interact in human spaces. Interestingly, neuromorphic computing led by Intel is the next big thing to the full realization of human behavior modelling. It is concerned with mimicking the neural structure and inner workings of human brain and acts to deal with uncertainty, vagueness, ambiguity and contradictions in the natural world.
Cape Canaveral Air Force Station, Florida, USA, 25 September 2006: A modernized Global Positioning System Block IIR (GPS IIR-M) satellite – designated GPS IIR-15(M) – built by Lockheed Martin was
China has established national island surveillance and monitoring system and completed airborne remote-sensing surveillance …
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