Journal of Advances in Developmental Research

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Next-Gen Smart City Operations with AIOps & IoT: A Comprehensive look at Optimizing Urban Infrastructure

Author(s) Shally Garg
Country United States
Abstract This study is above converging AIOps (Artificial Intelligence for IT Operations) with IoT (Internet of Things) to revolutionize smart cities through automated, data-driven decision-making. AIOps utilizes machine learning, big data analytics, and automation to enhance essential city operations, including traffic management, energy distribution, public safety, and infrastructure maintenance. AIOps improves anomaly detection, predictive maintenance, and incident resolution by analyzing extensive real-time IoT data, hence providing enhanced efficiency and resilience in urban settings.
Despite its benefits, challenges including data privacy, interoperability, and cybersecurity threats persist as substantial concerns. Emerging trends indicate a shift towards self-learning AI models, edge computing, and decentralized intelligence to improve scalability and security. Confronting these problems will be essential for realizing fully autonomous and adaptive smart city ecosystems. This study examines the applications, advantages, problems, and possible outcomes of AIOps-driven IoT operations, offering insights into their revolutionary impact on the growth of cities.
Keywords AIOps, IoT Operations, Smart Cities, , Edge Computing, Real-Time Data Processing, Interoperability, Autonomous Systems, Digital Transformation, Infrastructure Optimization, Network Monitoring, Event Correlation, Self-Healing Systems, Decentralized Intelligence, Sensor Networks, Traffic Management, Energy Optimization, Public Safety, Urban Resilience
Field Engineering
Published In Volume 12, Issue 1, January-June 2021
Published On 2021-03-02
Cite This Next-Gen Smart City Operations with AIOps & IoT: A Comprehensive look at Optimizing Urban Infrastructure - Shally Garg - IJAIDR Volume 12, Issue 1, January-June 2021. DOI 10.5281/zenodo.15049825
DOI https://doi.org/10.5281/zenodo.15049825
Short DOI https://doi.org/g88zjq
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