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AI-Enhanced Predictive Scheduling Optimizing Project Timelines for Blue-Green Infrastructure Deployment
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Author(s): Raunak Rathee (Manav Rachna Institute of Research and Studies, India), Harsh Vats (Manav Rachna Institute of Research and Studies, India)and Seema Sharma (Manav Rachna Institute of Research and Studies, India)
Copyright: 2025
Pages: 20
Source title:
Integrating Blue-Green Infrastructure Into Urban Development
Source Author(s)/Editor(s): Shashi Kant Gupta (Eudoxia Research University, USA), Nitu Maurya (IILM University, India), Firdous Ahmad Malik (University of People, USA)and Laeeq Razzak Janjua (WSB University, Poland)
DOI: 10.4018/979-8-3693-8069-7.ch004
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Abstract
In the rapidly evolving world of software development, efficient project scheduling is crucial for ensuring timely delivery and maintaining system reliability. This paper explores the role of Artificial Intelligence (AI) in predictive scheduling, particularly for Blue-Green infrastructure deployment. AI-driven models can analyze historical project data, resource availability, and risk factors to optimize project timelines, allowing for seamless transitions between production environments. By leveraging predictive analytics, AI enhances decision-making, reduces deployment risks, and ensures continuous service availability. The integration of AI with Blue-Green infrastructure strategies offers significant benefits in terms of agility, resource efficiency, and reduced downtime. This paper also addresses the challenges of AI-driven scheduling, such as data quality and system complexity, while highlighting potential future developments in the field.
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