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.
Amit Mangal Reviewer
09 Sep 2024 02:15 PM
Approved
Relevance and Originality:
The Research Article addresses a critical issue in the construction industry by exploring the application of Artificial Intelligence (AI) to enhance project management. Given the construction industry's slow adoption of digital technologies and the complexity of managing large, safety-critical projects, the focus on AI's potential to improve efficiency and effectiveness is both relevant and innovative. The originality of the research lies in its pioneering approach to evaluating AI solutions specifically for construction project management and developing a framework that can guide future AI implementations in this sector.
Methodology:
The study employs a mixed-method research design, combining both quantitative and qualitative data collected through structured online survey questionnaires. This approach is robust as it allows for a comprehensive analysis of the current state of AI adoption in construction project management. However, the summary lacks details on the specific statistical techniques used for quantitative analysis and the methods for qualitative data interpretation. Information on sample size justification, survey design, and how the data was analyzed would provide a clearer picture of the methodology.
Validity & Reliability:
The Research Article indicates the use of a mixed-method approach, which is beneficial for understanding both quantitative and qualitative aspects of AI adoption. However, the summary does not provide specific information on how validity and reliability were ensured. Details on the validation process for the survey instrument, the reliability of the data collected, and how potential biases were addressed would strengthen the assessment of the study's validity and reliability.
Clarity and Structure:
The summary is clear and well-structured, effectively outlining the problem of AI adoption in construction, the research objectives, and the methodological approach. It describes the challenges faced and the development of a framework for AI implementation. For improved clarity, the summary could include more details on the key findings from the data, specific recommendations provided, and how the framework was developed and validated. This would provide a more comprehensive view of the research outcomes and their implications.
Result Analysis:
The summary indicates that the research was successful in understanding the needs of construction professionals and establishing a framework for AI solutions. However, it lacks specific results or data demonstrating the effectiveness of the proposed framework. Including details on the main findings, such as specific challenges identified, insights gained from the survey data, and how the framework addresses these challenges, would enhance the result analysis. Additionally, discussing any limitations of the study and areas for further research would provide a more detailed evaluation of the research outcomes.
IJ Publication Publisher
Done Sir
Amit Mangal Reviewer