Snow Removal Analytics Using Video Prediction

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Solution Overview

Problem

Current systems lack an efficient and automated solution for managing snow removal on properties, leading to inefficient resource allocation, increased risk of injury, and potential malfunctions in automated devices due to inadequate prediction and optimization of snow accumulation and removal processes.

Innovation Solution

A monitoring system that utilizes video analytics, weather data, and machine learning to predict snow accumulation and optimize snow removal actions, including recommending schedules and device usage for automated devices, thereby minimizing energy consumption and reducing the risk of injury and device malfunction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated devices are used for snow removal, then productivity is improved, but device malfunction risk increases due to inadequate prediction and optimization

Engineering Contradiction:

Improvesnow removal efficiencyVSAvoiddevice malfunction risk

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary snow accumulation prediction using video analytics and weather data before deploying automated devices. This advance prediction allows optimization of device usage schedules and conditions, preventing malfunction by ensuring devices operate under appropriate environmental conditions rather than being deployed reactively

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors snow accumulation in real-time using video cameras and compares actual accumulation against predictions. This feedback loop allows dynamic adjustment of automated device deployment and operation parameters, improving reliability by adapting to changing conditions and preventing malfunction through continuous optimization

Inventive Principle:

Principle #23Feedback

2Productivity

If automated snow removal devices operate continuously, then productivity is improved, but energy consumption increases

Engineering Contradiction:

Improvesnow removal throughputVSAvoidautomated device energy consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system uses periodic video analytics monitoring at scheduled intervals to track snow accumulation. Automated devices are activated only when predicted accumulation thresholds are reached, creating a periodic on-demand operation pattern rather than continuous operation, thereby reducing energy consumption while maintaining productivity

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system dynamically changes operational parameters of automated devices based on predicted snow accumulation rates and environmental conditions. By adjusting device activation thresholds, operation intensity, and timing based on real-time predictions and historical data, the system optimizes the balance between productivity and energy consumption

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If manual snow removal is performed, then device complexity is reduced, but risk of injury increases

Engineering Contradiction:

Improvesnow removal system simplicityVSAvoidinjury risk

Core Design Contradiction:

Device complexityVSObject-affected harmful factors

Solution Approach 1:

The system implements self-service snow removal through automated devices that operate autonomously based on predicted snow accumulation. This eliminates the need for manual intervention in hazardous conditions, reducing injury risk while the predictive analytics component maintains relative system simplicity by using straightforward video analysis and threshold-based activation

Inventive Principle:

Principle #25Self-service

4Use of energy by moving object

If snow removal is delayed, then energy consumption is reduced, but precipitation removal effectiveness decreases due to accumulation

Engineering Contradiction:

Improvesnow removal energy costVSAvoidsnow removal effectiveness

Core Design Contradiction:

Use of energy by moving objectVSProductivity

Solution Approach 1:

The system performs preliminary prediction of snow accumulation using video analytics and weather data to determine optimal removal timing. By predicting future accumulation rates and comparing against thresholds, the system schedules snow removal at the most efficient moment - early enough to maintain effectiveness but not so early that energy is wasted on preventable accumulation

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts the snow accumulation threshold for triggering removal based on environmental parameters such as temperature, wind conditions, and predicted accumulation rates. This allows optimization of the balance between energy consumption and removal effectiveness by adapting the trigger point to current conditions rather than using a fixed threshold

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11631150B1Precipitation removal analytics

Publication Date: 2023.04.18 ALARM COM INC

AI summary

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing actions based on predicted precipitation accumulation. One of the methods includes receiving, from a camera, image data that depicts at least a portion of a property; determining, using the image data, a predicted current amount of precipitation that has accumulated at the property; receiving additional data that identifies characteristics of the property; determining one or more actions to remove at least some of the precipitation from the property using the predicted current amount of precipitation that has accumulated at the property, and the characteristics of the property; and performing the one or more actions to remove at least some of the precipitation from the property.