Design and Application of a Smart Blasting Platform for Intelligent Construction Management

Abstract

Blasting is widely used in tunnel excavation, mining, underground construction, and building demolition, yet current management systems still suffer from information isolation, low design efficiency, limited monitoring capability, inaccurate feature recognition, and poor effect evaluation. To address these issues, a smart blasting platform is proposed by integrating a geographic information system (GIS), building information modeling (BIM), artificial intelligence (AI), and global navigation satellite system (GNSS) to enhance information sharing, parameter prediction accuracy, feature recognition, effect evaluation and intelligent construction management. First, GIS, BIM, blasting recorder, GNSS, and others are adopted to build a smart blasting data perception system. Second, GIS–BIM–IoT fusion, data fusion, blasting design, intelligent optimization, feature recognition, and effect evaluation methods are established. Finally, the overall architecture and technical implementation of the platform are designed and demonstrated through representative hydropower and tunnel engineering projects. The GIS and BIM model of blasting established in this work provides the spatial location reference and information sharing for blasting design, construction, and management, enabling the blasting GIS–BIM-based design. The goodness of fit ( R 2 ) of the proposed intelligent optimization method is 0.83, indicating good predictive performance for blasting parameters and effect indicators. The proposed blasting feature recognition method can effectively denoise signal and extract characteristics from the perspective of time-frequency and energy and the extracted dominant frequency is within 50 Hz. The proposed blasting effect evaluation has an accuracy rate of over 80%, achieving a reliable evaluation of blasting effects. The design and application of a smart blasting platform realize multisource information perception, data fusion, GIS–BIM-based design, intelligent optimization, feature recognition, and effect evaluation, which can provide an interactive, integrated, and mutually beneficial solution for intelligent construction management.