Computer-assisted method for the maintenance of a snow slope and computer-assisted system for carrying out such a method
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Solution Overview
Problem
Existing methods for maintaining ski slopes rely on subjective human assessment, leading to inconsistent snow quality and inefficient resource allocation.
Innovation Solution
A computer-aided method and system that utilize sensors to record time-dependent condition data, including snow hardness, temperature, and water content, to create a predictive model for proactive slope maintenance, optimizing snow preparation and resource allocation based on objective data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If subjective human assessment is used to control snow groomers and snowmaking equipment, then operational flexibility and adaptability are maintained, but snow slope quality consistency deteriorates
Solution Approach 1:
The patent replaces the mechanical system of subjective human assessment with an automated sensor-based measurement and control system. Sensors mounted on snow groomers objectively measure snow conditions (hardness, temperature, density) and this data feeds into a predictive model that automatically controls snowmaking equipment and groomer operations, eliminating human subjectivity and ensuring consistent snow quality
Solution Approach 2:
The system enables self-service by allowing the snow slope maintenance system to automatically monitor its own condition through sensors and adjust operations based on predictive modeling. The predictive model forecasts snow condition changes and automatically triggers appropriate maintenance actions without requiring continuous human intervention, making the system self-regulating
2Reliability
If reactive snow slope maintenance is performed based on current conditions, then immediate problems are addressed, but proactive prevention of negative changes is lost
Solution Approach 1:
The patent implements preliminary action through its predictive model that forecasts future snow condition changes based on current sensor data, weather forecasts, and historical patterns. The system proactively schedules maintenance operations before negative changes occur, allowing snowmaking and grooming to be performed in advance to prevent quality degradation rather than reacting to problems after they occur
Solution Approach 2:
The system establishes continuous feedback loops where sensors constantly monitor snow conditions and this data feeds into the predictive model. The model's forecasts trigger control actions that are then monitored for their effects, creating a closed-loop system where maintenance decisions are continuously refined based on actual outcomes versus predicted outcomes, improving both responsiveness and reliability over time
3Measurement precision
If experienced personnel subjectively assess snow slope conditions, then operational judgment is applied, but measurement precision and objectivity deteriorate
Solution Approach 1:
The patent replaces the human sensory and judgment system with precise electronic sensors that objectively measure snow conditions. Sensors mounted on snow groomers measure parameters such as snow hardness, temperature, and density with high precision, eliminating the variability and subjectivity of human assessment while providing quantifiable, actionable data for control decisions
Solution Approach 2:
The predictive model serves as an intermediary between raw sensor data and control decisions. It processes complex sensor measurements, weather forecasts, and historical data to generate actionable forecasts that guide maintenance operations, bridging the gap between precise measurement and practical operational decisions while maintaining objectivity
4Reliability
If frequent snow grooming and snowmaking operations are performed, then snow slope quality is maintained, but resource consumption and operational costs increase
Solution Approach 1:
The predictive model forecasts when snow conditions will deteriorate to unacceptable levels, allowing the system to schedule maintenance operations only when and where they are truly needed. This prevents unnecessary grooming and snowmaking runs, optimizing resource allocation by performing operations in advance to extend the interval between maintenance events while maintaining quality standards
Solution Approach 2:
The system applies maintenance actions selectively based on predicted needs rather than uniformly across the entire slope. The predictive model identifies specific areas and time windows where maintenance will be effective, allowing partial action (focusing resources on critical areas) rather than excessive action (treating the entire slope equally), thereby improving resource efficiency while maintaining overall quality
Data Source
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AI summary
1. Computer-aided method for maintaining a snow slope and system for carrying out such a method. 2.1 A computer-aided method for maintaining a snow slope is known, according to which time-dependent condition data of the snow slope are recorded. 2.2 According to the invention, the condition data comprise snow condition data that depend on the condition of a slope surface of the snow slope, wherein a predictive model for the condition of the snow slope at at least one future point in time is calculated from the recorded condition data, and wherein information about the predictive model is output. 2.3 Application for monitoring and maintaining snow slopes in ski resorts