Efficient Construction Waste Management Through AI

Construction is one of the most iterative processes that keep executing due to the large-scale development happening all over the world. Aggressive development has led to the considerable increase in the velocity of construction. This increase in the construction has led to various consequences that have been afflicted due to this practice, such as the creation of a lot waste. Most of the waste is due to the malpractices and the inability in achieving effective organization and planning for waste management and disposal. Therefore, for this purpose a collection of related works have been analysed. The analysis revealed that most of the techniques have not been able to effectively address the issue of construction waste creation and management in an effective manner. Therefore, in this research an innovative approach towards the management of the construction waste is achieved through the use of machine learning paradigms. The proposed methodology implements Fuzzy C-means clustering and Linear Selection along with Artificial Neural Networks and Decision Tree to achieve construction waste management effectively.