Combining professional sensing equipment and intelligent algorithms, our products use the Internet of Things to automatically collect data in the production process. Yunlu helps businesses facilitate and visualize real-time management decisions by integrating and analyzing data to reducing risks and costs and improving efficiency.
Based on actual monitoring data, Yunlu uses artificial intelligence and multi-physics simulation technology, combined with professional theory and engineering experience, to analyze, predict and warn of different application scenarios to achieving active process control, ensure engineering safety, and optimize construction and design methods.
Data collection, analysis, and deduction of environmentally sensitive factors, through the control of thresholds, to achieve early warning, improve environmental protection measures, use simulation analysis to achieve cause traceability, and facilitate the accurate and effective management and control.
Extract the controllable process parameters of the key technological process, use the corresponding algorithm to simulate and reproduce the whole construction process in multiple conditions, formulate the control standard to achieving early warning and prediction of the process, improvement, and promotion.
Real-time and efficient data collection and transmission, combined with the response characteristics of the bridge under different types of action, accurately and objectively evaluate and analyze the state of the structure, and provide early warning of abnormal conditions.
Use the movable high-precision industrial camera, motion tracking, and wireless network to receive data. Being able to intelligently identify and warn the tunnel condition. By setting up corresponding sensors at the tunnel entrance in the tunnel, the external environment, deformation, stress, and soil parameters can be predicted, early warning or inversed to achieve safety status assessment.
Using remote sensing and sensors to monitor the external conditions of the surrounding environment, collect deformation and force data of slopes, roadbeds, foundation pits, foundations, etc., screen and process the data, effectively predict and evaluate the safety of facilities in different geological scenarios And applicability.
Combining the operational requirements and changes in use conditions during the use period, collect real-time data of sensitive parameters, preset alarm thresholds, and emergency decision-making methods based on historical big data, professional theory, and simulation analysis to achieve real-time display and effective emergency management.
By deploying intelligent sensing devices on large-scale building structures, real-time perception of various performance indicators of the structure, data cleaned monitoring data enter the Yunlu multi-physics simulation platform, combined with cloud computing, big data, and other technologies to achieve the integration of monitoring data Analyze and comprehensively judge the safety status of the structure to realize the safety assessment of large buildings.
Through cloud map + BIM display leakage analysis, tube burst reliability analysis, and smart pressure regulation suggestions, the leakage rate is reduced to 10-15%, the cost of new and old pipeline hardware is reduced, and the operation and maintenance cost is optimized.
Display of rainwater evolution status in hundreds of kilometers (10-meter granularity), the real-time calculation (minute-level calculation speed) of water accumulation, prediction of risk 0-48 hours in advance, the output of decision sets through machine learning, as command and dispatch support, and integration Industry experts have technical experience in algorithm iteration.
Monitoring and quickly locating pollution sources in the whole region, increasing the corresponding speed of environmental events by more than 30%; predicting the distribution and change of air quality in the whole region; reducing labor costs by more than 40%; saving hardware costs by more than 50%.