Blasting is widely used in mine,tunnel excavation, underground powerhouse, and building demolition. Facing the characteristics of current blasting management system, such as single information, low design efficiency, single vibration monitoring mode, inaccurate feature extraction, poor effect recognition, and low management efficiency, as well as the situation where smart mine blasting concepts are available but do not have solutions, a smart mine blasting platform is designed in combination with geographic information system (GIS), building information modeling (BIM), and artificial intelligence. First, GIS, BIM, blasting recorder, etc. are adopted to build a smart mine blasting data perception system. Second, GIS+BIM fusion, data fusion, blasting design, intelligent optimization, feature extraction, and blasting effect recognition methods are established, and all of these methods constitute the business algorithm of smart mine blasting platform. Finally, the overall architecture and technical implementation of the platform are designed and demonstrated by taking mine blasting projects as examples. The GIS and BIM model of mine blasting established in this paper provides the spatial location reference and information sharing for blasting design, construction, and management, realizing the blasting BIM design and improving the reliability and universality. The determination coefficient of the proposed intelligent optimization method, which can predict the blasting and effect parameters accurately and optimize the blasting design intelligently, is 0.83. The proposed blasting feature extraction 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 accuracy rate of the proposed method for blasting effect recognition is more than 80%. The design and application of smart mine blasting platform integrates multi-source information perception and realizes data fusion, blasting design, intelligent optimization, feature extraction, and effect recognition, which can provide a new solution for smart mine blasting.