Transparent Peer Review By Scholar9
Empowering Construction Through Artificial Intelligence
Abstract
Abstract: Artificial Intelligence is a field that is becoming widely used in almost all industries, and its applications are proven to increase efficiency in the workplace. The construction industry is slow to adapt to the digital era, with companies failing to utilize advanced technologies and adopt artificial intelligence systems. Construction projects are unique projects and often exceedingly large, complex and safety-critical making it difficult to introduce change, thereby relying on traditional processes. The processes used to plan construction projects involve a wide variety of knowledge areas and several stakeholders that must all be aligned for the project to be successful. Artificial Intelligence is a promising technological advancement that is expected to drastically improve project management for construction projects. Despite these promising benefits, AI has not been properly explored due to several factors such as its large implementation costs, data preparation needs, lack of AI strategies and lack of skilled personnel. This research work is a pioneer in this regard and is an evaluative investigation into how artificial intelligent solutions and techniques can be used to support project managers and related professionals to properly plan and manage construction projects. To achieve this objective, a mixed method research design was used to collect both quantitative and qualitative data using structured online survey questionnaires, this provides an in-depth understanding of the topic as well as identifies the challenges faced by professionals and organizations, followed by recommended steps to implement AI in their workflow. The research proved fruitful in understanding the needs of construction project professionals and organizations and has been successful in establishing a framework for AI experts to use to develop future AI solutions for construction project planning.
Uma Babu Chinta Reviewer
09 Sep 2024 01:38 PM
Approved
Relevance and Originality:
The article addresses a critical gap in the adoption of AI in the construction industry, which is currently lagging in digital transformation. The focus on improving project management through AI is highly relevant given the complexity and scale of construction projects. The originality of the study lies in its evaluation of AI's potential impact on project management within this industry, highlighting a pioneering effort to explore this area.
Methodology:
The study employs a mixed-method research design, utilizing both quantitative and qualitative data collected through structured online surveys. This approach is effective in capturing a comprehensive view of the challenges and needs related to AI implementation in construction. However, details on the specific survey questions, sampling methods, and data analysis techniques used would strengthen the methodology section.
Validity & Reliability:
The research aims to establish a framework for AI solutions in construction, but it would benefit from more empirical evidence to validate its findings. Including results from pilot implementations, case studies, or comparative analyses of AI versus traditional methods would enhance the validity and reliability of the conclusions drawn. Details on how the data was validated and how reliable the findings are would provide further assurance of the study's robustness.
Clarity and Structure:
The article is well-structured and clearly communicates the need for AI in construction project management. The description of the research objectives and the framework developed is logically presented. To improve clarity, the inclusion of visual aids such as flowcharts or diagrams depicting the AI framework and its components would help readers better understand the proposed solutions.
Result Analysis:
The article discusses the potential benefits of AI and provides recommendations for implementation, but it lacks detailed result analysis. Including specific findings from the surveys, such as statistical analyses or key insights gained from respondents, would offer a more thorough understanding of the challenges and opportunities identified. Discussing any limitations of the research and areas for future exploration would also provide a more nuanced view of the study's contributions.
IJ Publication Publisher
Ok Sir
Uma Babu Chinta Reviewer