In recent years, with the vigorous development of outdoor adventure sports in China, related safety incidents have occurred frequently, posing a serious threat to people’s lives and property. Traditional emergency management models that focus on “post-incident response” have struggled to meet the increasingly complex safety demands of outdoor adventures. This paper systematically explores the spatiotemporal distribution characteristics, causative mechanisms, and risk evolution patterns of outdoor adventure accidents through a comparative analysis of accident data from two distinct periods: 2015–2019 and 2021–2024. The study finds that getting lost, being trapped, and slipping are the primary types of outdoor adventure accidents, with a notable seasonal and geographical distribution. Against the backdrop of heterogeneous data sources, this paper highlights the differences and commonalities in accident characteristics across different periods and addresses the limitations of small-sample statistics. Building on this, the paper introduces the concept of “proactive management” and constructs a four-pronged proactive prevention and control system for outdoor adventure accidents in China, integrating smart technologies such as the Internet of Things, big data, and artificial intelligence. This system, encompassing “smart perception—intelligent early warning—precise intervention—collaborative governance,” aims to achieve early risk identification, dynamic assessment, and proactive intervention through technological empowerment, thereby effectively reducing accident rates. The research not only enriches the theoretical connotations of tourism safety management but also provides practical references for government departments and relevant institutions to enhance their outdoor adventure safety governance capabilities.