Snow Piste Prediction Model for Objective Maintenance Planning
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Solution Overview
Problem
Existing methods for maintaining snow pistes rely heavily on subjective assessments, leading to inconsistent and suboptimal snow quality due to human evaluation, which lacks foresight and precision in planning and preparation.
Innovation Solution
A computer-aided method and system that captures state data, including snow constitution and topography, using sensors on piste groomers and other devices to create a prediction model for future snow conditions, enabling objective and precise planning of snow preparation and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If subjective assessment by experienced personnel is used to control piste groomers and snowmaking machines, then operational flexibility and adaptability are maintained, but consistency and precision of snow quality deteriorate
Solution Approach 1:
The patent replaces the mechanical system of subjective human assessment with an automated sensor-based measurement system. Sensors mounted on piste groomers and snowmaking machines objectively measure snow parameters such as hardness, temperature, and density, eliminating variability in human judgment while maintaining operational control through automated feedback systems.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from the snow piste is processed in real-time and used to automatically adjust groomer and snowmaking machine operations. This closed-loop control ensures consistent snow quality by constantly monitoring and correcting deviations from target parameters, while still allowing operators to adapt to changing conditions through the automated system.
2Measurement precision
If time-dependent capture of snow constitution data is implemented, then prediction accuracy for future snow conditions is improved, but data processing complexity and measurement requirements increase
Solution Approach 1:
The system performs preliminary data capture and processing by continuously monitoring snow constitution parameters and storing this information for later analysis. By pre-capturing time-dependent data during routine groomer operations, the system builds a historical database that enables accurate predictions of future snow conditions without requiring complex real-time processing during critical decision-making moments.
Solution Approach 2:
The system uses the existing movement and operational patterns of piste groomers to automatically collect snow data along their regular routes. The groomers themselves serve as mobile data collection platforms, eliminating the need for separate dedicated measurement equipment and reducing overall system complexity while maintaining comprehensive spatial and temporal coverage.
3Loss of information
If sensors are mounted on piste groomers for data acquisition, then measurement coverage and data completeness are improved, but equipment load and operational complexity increase
Solution Approach 1:
The patent integrates multiple functions into the piste groomers, combining their existing snow preparation role with additional data collection and measurement capabilities. The same vehicle that compacts and prepares the snow piste also serves as a mobile laboratory equipped with sensors for measuring snow constitution, temperature, density, and other parameters, eliminating the need for separate dedicated measurement equipment.
Solution Approach 2:
The system merges the data acquisition function with the operational function of piste groomers. By combining sensor arrays, data processing units, and communication systems into the existing groomer platform, the patent creates a unified system that performs both snow preparation and scientific measurement simultaneously, reducing overall equipment complexity while maximizing data completeness.
Data Source
AI summary
A computer-aided method for maintaining a snow piste, according to which state data relating to the snow piste are captured in a time-dependent manner. The state data include snow constitution data which depend on a constitution of a piste surface of the snow piste, a prediction model for the state of the snow piste at at least one point in time in the future is calculated from the captured state data, and information relating to the prediction model is output.