Aug 2026· Journal of Environmental & Earth Sciences· 0 citations· 89 references
Abstract
Mechanical intelligence infrastructure (MII) is a paradigm shift in the design and management of the built environment through a combination of autonomous architecture and real-time control over environmental processes. This paper discusses the intersection of these two technologies with reference to their ability to develop adaptive, long-term, and efficient infrastructure systems. Autonomous design uses AI-based and generator-based design algorithms, which allow the design of highly optimized forms capable of evolving to external influences. Controlled by IoT sensors and AI-based processes, real-time environmental process control constantly monitors and adjusts the performance of the infrastructure to maximize the use of energy, increase comfort, and resilience. The combination of these systems allows the infrastructure to conform to the evolving conditions in a proactive manner with long-term sustainability and effectiveness. MII has been applied in smart buildings, smart cities, industrial systems, and critical infrastructure, where it has significant value in terms of energy efficiency, resource optimization, and disaster resilience. Nevertheless, there are issues of data interoperability, high cost, and regulatory requirements. With the further advancement of technology, the opportunity to change the city environment, the workplace, and the infrastructure is enormous. This paper gives a detailed analysis of the present, the new trend, and the future of mechanically intelligent infrastructure.
The increasing use of Unmanned Aerial Vehicles (UAVs) in energy-sector operations- such as pipeline inspection, infrastructure monitoring, and remote asset surveillance- has highlighted critical limitations in predominantly manual and semi-automated drone systems. While current UAV deployments offer improved safety a...
G. I. Akanbi, O. Kolade, S. Akande et al.· SPE Nigeria Annual Internati...· 0 citations
Special emphasis is placed on the concept of explainable AI, human in the loop decision making, risk based asset prioritization and ongoing model validation as ways to provide public accountability and reliability in critical infrastructure sectors.
Marjan Sultana Nuha· Journal of Artificial Intell...· 0 citations
This article discusses edge intelligence and its role in real-time industrial Internet of Things (IoT) applications in smart manufacturing settings. The series of experiments described herein provide evidence that using an edge computing architecture result in lower latency, higher reliability, better security and fast...
J. V. Suman, P.Rutravigneshwaran, Aparna et al.· 2026 International Conferenc...· 0 citations
This study critically analyzes existing literature to pinpoint current achievements, implementation strategies, and technological progress across various civil engineering fields, and highlights several key research challenges, such as data interoperability, cybersecurity, computational complexity, scalability, standar...
M. M., Meghana C. S.· Journal of Recent Activities...· 0 citations
A cyber-physical architecture based on the IoT, which uses machine intelligence to monitor, analyze, and control manufacturing systems in real-time, which can be both scaled and powerful to serve next-generation intelligent manufacturing systems.
P. Mudholkar· Materials Research Proceedin...· 0 citations
Hybrid architectures are suitable for inclusive IoT environments when immediate local reactions are combined with configurable external logic and reliable monitoring, and the findings indicate that hybrid architectures are suitable for inclusive IoT environments when immediate local reactions are combined with configur...
Peter Tsonkov, Fatima Sapundzhi, Slavi Georgiev et al.· EEPES 2026· 0 citations
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