To address the challenges of high fall risks among the elderly in aging societies, delayed responses of traditional monitoring methods, and limitations of existing fall detection products such as single-functionality, high false alarm rates, and inadequate comfort, this study designs a multi-sensor fusion-based fall detection and cushioning system. The system adopts a hierarchical architecture integrating various sensors and PLC modules, combined with multiple key algorithms to cover six core functional modules. Experimental verification demonstrates that the system outperforms existing typical methods in fall detection accuracy, false alarm rate, and response time, demonstrating excellent practicality and reliability. Practical applications show that this system effectively serves elderly populations at risk of falls, helps reduce operational costs in nursing homes, improves monitoring efficiency, and provides integrated fall prevention solutions for multiple scenarios.