Dams serve as key nodes of the national water network. Amid frequent extreme precipitation events, higher standards are required for their safe operation and emergency dispatching. The industry currently faces three major pain points: poor integration of spatial structure models with business functions resulting in obvious disconnection; long analysis cycles of traditional mechanism models that fail to meet real-time decision-making needs; and data latency between front-end intelligent perception and back-end platforms, restricting the comprehensive dispatching efficiency of reservoirs. The water conservancy industry urgently needs to break down multi-source data barriers of dams, build efficient intelligent analysis models, and establish a real-time decision-making and management system to empower the development of new quality productive forces in water conservancy.
Baviat focuses on the research and development of spatial intelligence technologies for intelligent dams, and has built a full-link product system covering domestically developed digital infrastructure, vertical industry models and embodied intelligence inspection training platforms. It provides full-cycle intelligent services for new and existing dams, facilitates the transformation of water conservancy governance from passive response to active prediction, and delivers solid technical support and practical implementation solutions.
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Build a Unified Digital Base for DamsBased on the self-developed uTwin integrated platform, it dynamically matches BIM 3D spatial data, GIS geographic information, object relationships and other data with business data, realizing real-time linkage between spatial data and business scenarios.
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Establish Mechanism-Data Fusion Intelligent Model LibraryCombining the high accuracy of mechanism models and the high efficiency of machine learning models, it forms low-code agent models covering the full life cycle of intelligent construction and intelligent operation and maintenance, such as intelligent temperature control, intelligent rolling construction, engineering safety analysis and watershed dispatching, so as to improve decision-making timeliness.
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Build an Intelligent Inspection PlatformRelying on the self-developed embodied intelligence inspection platform, unmanned autonomous inspection is realized by UAVs and robots. With AI intelligent identification, real-time hidden danger analysis and automatic early warning, it achieves synchronous inspection and perception, eliminates data entry delay, and ensures safe and efficient reservoir management.
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Construct Multi-scenario Application AgentsBuild four core intelligent agents covering engineering safety, intelligent construction, flood control & benefit generation, and emergency decision-making. It enables front-line staff to quickly build customized applications, supports flexible expansion from digital base to scenario-based services, and adapts to different dam types and engineering stages.
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Improve Dam Safe Operation CapacityBased on a unified digital base and second-level intelligent fusion computing models, it realizes 3D visualization of engineering structures and flood processes, and enhances the capability of projects to cope with extreme precipitation.
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Reduce Engineering O&M CostsAdopt intelligent construction technologies to boost construction efficiency and lower project costs. Intelligent inspection via UAVs and robots cuts manpower input and eliminates potential safety hazards. Lightweight modeling reduces data storage and operation costs to achieve cost reduction and efficiency improvement.
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Promote Intelligent Engineering UpgradeWith the application of spatial intelligence, artificial intelligence and other technologies, it builds smart dams with self-perception, self-analysis, self-decision and self-control capabilities, driving the upgrade from digital dams to intelligent dams.
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Optimize Water Network Dispatching & ManagementRealize real-time linkage between spatial data and business scenarios, support rapid response of intelligent agents for flood control, water resource utilization and emergency decision-making, and enable accurate rehearsal of cross-basin dispatching, so as to comprehensively improve the management efficiency of key nodes in the national water network.
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针对该县汛期洪涝多发、信息化平台分散、数据单一、多部门协同不足等问题，项目整合各类现有平台数据，融合遥感、GIS、BIM等多源数据搭建统一数字底座，配套建设内涝、滑坡、洪水研判及应急决策等业务系统，实现数据互通共享。可对降水过程开展实时感知、分析与调度，2025年汛期累计发布数百条预警，成功精准预警“7·9”洪水事件。 -
针对老旧水库信息化系统老化、感知覆盖不足、预警滞后、调度决策缺乏科学支撑等问题，项目搭建水库数字孪生平台，完善全方位智能感知体系，搭建数据、模型、知识核心引擎，配套五大智慧业务系统。L3级实景模型平面精度≤5cm，洪水预报预见期超3天，分钟级生成调度方案，可精准模拟下游水情变化，大幅提升水库抵御超标洪水的安全保障能力。 -
针对传统水库人工巡检风险高、环境受限、无法全覆盖高频巡检等痛点，项目部署智能机器狗与室内无人机集群，依托空间智能AI技术实现无GPS环境自主巡检，通过边缘算法智能识别坝体各类隐患并自动告警。项目实现廊道全天候无人巡检，大幅压缩巡检时长，隐患识别准确率超95%，彻底消除人员高危作业风险，构建智能化巡检运维闭环。
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