Construction Waste to Energy, Technologies, Economics, and Challenges

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

“…The shortage of skilled professionals with expertise in AI, data science, and related fields poses a significant challenge to the widespread adoption of AI in the construction industry [83,112]. Building and deploying AI solutions require specialized knowledge and technical skills, including programming, machine learning, and data analysis.…”

“…Despite these significant benefits, the literature review highlighted several challenges in the application of AI in sustainable building lifecycle. These challenges include initial implementation costs [96][97][98], data security and privacy concerns [62,66,103,104], lack of standardization [105,106,111], skills gap [83,[112][113][114][115][116], interoperability issues [66,[117][118][119], ethical considerations [66,103,120,121], and regulatory compliance [116,[120][121][122][123]. The construction industry's relatively slow adoption of AI can be attributed to factors such as the complexity of construction projects, the traditional nature of the industry, and a lack of awareness or understanding of AI's potential benefits [30,66].…”

“…Furthermore, the review identified the potential advantages and challenges of integrating AI towards creating a sustainable building lifecycle [20,23,32,47,58,[62][63][64]66,69,70,72,73,83,86,[95][96][97][98][103][104][105][106][111][112][113][114][115][116][117][118][119][120][121][123][124][125]. While highlighting the benefits, such as energy efficiency optimization, predictive maintenance, and waste reduction, the review also addressed challenges like initial implementation costs, data security and privacy concerns, lack of standardization, skills gap, interoperability issues, ethical considerations, and regulatory compliance.…”