Advancing civil engineering: The transformative impact of neuromorphic computing on infrastructure resilience and sustainability - Ali Akbar Firoozi; Ali Asghar Firoozi; Yasser Alashker; Safeer Ahmad (Results in Engineering)
The resilience and adaptability of civil infrastructure are paramount for societal well-being and economic stability. This paper examines the transformative impact of neuromorphic computing on enhancing the resilience of infrastructure systems and advancing sustainable engineering practices. Drawing inspiration from the human brain's processing capabilities, neuromorphic computing has been demonstrated to significantly enhance the efficiency of real-time data analysis, learning, and prediction of structural integrity. We detail the fundamental principles of neuromorphic computing, its practical applications within civil engineering, and notable implementations, underscoring its substantial contributions to predictive maintenance, disaster preparedness, and environmental conservation. Our findings reveal that neuromorphic systems, through their capability to continuously learn and adapt, have effectively improved the accuracy of predictive models for infrastructure behavior under various environmental stressors, thereby facilitating more robust disaster response strategies and reducing maintenance costs by up to 30 %. Despite facing technological and integration challenges, neuromorphic computing emerges as a pioneering force in the field of civil engineering, offering a future where infrastructure is not only more durable but also inherently intelligent and responsive to changing conditions. The integration of neuromorphic computing holds the promise of revolutionizing civil engineering practices by fostering greater interdisciplinary collaboration and driving a commitment to environmental sustainability. This study advocates for broader adoption of neuromorphic technologies to cultivate a resilient, adaptive, and sustainable built environment.