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 construction management


Benefits of Artificial Intelligence in Construction Management

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The construction industry faces numerous hurdles that have hampered its expansion and resulted in exceptionally low productivity levels. Artificial intelligence and its applications have completely altered the landscape of the construction industry. The construction industry is one of the least digital in the world, with most players acknowledging a long-standing culture of resistance to change. The lack of digitization and the industry's extremely manual character make project management more complex and time-consuming than it needs to be. When compared to traditional procedures, AI techniques have helped to improve automated processes and create superior competitive advantages.


AI Inroads in Construction Management - Constructech

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Whether you use artificial or augmented with intelligence, AI (artificial intelligence) is catching on in the industry. Recent announcements include its use in field and office alike. For example, Black & Veatch is implementing Zinier's intelligent field service automation platform, ISAC, (Intelligent Service Automation and Control) to deepen realtime visibility into the field, to anticipate service disruptions through AI-driven recommendations, and to improve operational efficiencies by automating manual front-office, backoffice, and field-office tasks. ISAC will help ensure faster, more seamless communication among Black & Veatch's extensive field services workforce. According to Zinier, ISAC is the eyes, ears, and algorithms that analyze an organization's past and present.


Site-Layout Modeling: How AI Can Help Construction Industry? – AI.Business

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Site-Layout Modeling: How AI Can Help Construction Industry? The efficient planning of site space through the construction project is referred to as site layout planning. Due to its impact on safety, productivity and security on construction sites, several site layout planning models have been developed in the past decades. These models have the common aim of generating best layouts considering the defined constraints and conditions. However, the underlying assumptions that were made during the development of these models seem disparate and often implicit.