Harnessing Big Data and IoT for Enhanced Resource Optimization in Sustainable Construction within Smart Cities

Abstract

The construction industry of smart cities is gaining more attention when it comes to environmental preservation and improving the efficiency of resources, and so, they have to tackle sustainable resource management. In this paper, the use of big data analytics in conjunction with a system of IoT is examined as enabling technologies for achieving sustainable resource optimization in construction works. The analysis of real-time data obtained from IoT sensors and devices, together with the big data analytical capabilities, allows construction managers to make informed decisions regarding material and energy expenditure and the overall effect construction activities have on the environment. The study focuses on predictive maintenance, nebulous resource allocation, and waste minimization strategies as approaches that may address the problem of cost, carbon emissions, and material waste together with enhanced project productivity. The paper also highlights issues of data integration, as well as questions of self-sustainability, and the security of the data acquired, providing guidance for further analysis to aid the development of advanced resilient urban ecosystems. The proposed framework details how a smart city can leverage data for efficient construction and resource allocation, less pollution and waste, and increased economic output and productivity.