与江河同频｜星图亿水2025年度答卷

Core Insights - The company, Star Map Yishui, has made significant advancements in its business landscape and core patented technologies in 2025, emphasizing a commitment to "precision, efficiency, and intelligence" in water management [21][22] Business Expansion and Technological Innovation - In 2025, the company launched the iWater.FMS flood simulation system to enhance watershed monitoring and management capabilities, providing efficient technical support for flood forecasting and real-time risk analysis [23] - The establishment of provincial academician and doctoral innovation workstations in Chengdu aims to deepen the integration of industry, academia, and research, strengthening core technology development and high-end talent reserves [25] Quality Development and Certifications - Star Map Yishui was recognized as a CS3-level enterprise in the eighth batch of information system construction and service capability standards, marking a significant upgrade from CS2 [27] - The company also obtained secondary qualifications for electronic and intelligent engineering contracting and safety production licenses, enhancing its recognition in solution capabilities and project delivery compliance [27] Smart Equipment and Applications - In April 2025, the company introduced a new generation of intelligent unmanned boats equipped with high-precision sensors and autonomous navigation systems, significantly improving field efficiency and data accuracy [29] Regional Market Development - The new Henan Meisheng Work Area was officially launched in August 2025, focusing on software development, intelligent water conservancy equipment testing, and system integration to support localized product iteration and project delivery [31] Industry Collaboration and Knowledge Sharing - The company actively participated in various industry events in 2025, including hosting a technical seminar on the information construction of the Kashgar irrigation area and attending the China Geography Society's annual meeting to share practices in watershed perception and model integration [33]