Grid-Based Sunlight Assessment Using Location And Light Sensors
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Solution Overview
Problem
Property owners and managers face challenges in efficiently managing lawn care, including the need for DIY lawncare that requires significant time and equipment maintenance, while professional services are costly. Accurate monitoring of sunlight, a key factor in vegetation health, is difficult due to changing sun positions, and existing systems lack precise sunlight assessment for optimizing lawn care.
Innovation Solution
A system with a computer processor and database that segregates locations into grid areas, using sensors to measure sunlight and shadows, providing a map of sunlight availability, and recommending treatments based on sunlight data, including irrigation adjustments and grass variety selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If DIY lawncare is performed, then cost is reduced, but time investment and equipment maintenance increase
Solution Approach 1:
The system enables property owners to automatically monitor and assess sunlight conditions on their own lawns using sensors and processing systems, eliminating the need for professional services while reducing time investment through automated data collection and analysis
Solution Approach 2:
Manual sunlight assessment and lawncare decision-making are replaced with an automated electronic system that uses light sensors, GPS location tracking, and computer processing to evaluate sunlight conditions and provide actionable insights
2Reliability
If professional landscape services are employed, then lawncare effectiveness is improved, but cost increases
Solution Approach 1:
The system empowers property owners to independently assess and manage their lawn care needs by providing accurate sunlight condition data, eliminating dependency on professional services while maintaining effective lawncare through data-driven decisions
Solution Approach 2:
The system continuously collects sunlight data, processes it through grid-based analysis, and provides feedback to property owners about optimal lawncare timing and conditions, enabling effective self-management without professional intervention
3Device complexity
If sunlight monitoring is performed manually, then equipment complexity is reduced, but measurement precision decreases
Solution Approach 1:
Manual sunlight monitoring is replaced with electronic light sensors that automatically measure and record sunlight conditions, providing precise quantitative data without requiring complex manual observation equipment or expertise
Solution Approach 2:
The monitoring system divides the lawn into grid areas with specific coordinates, allowing precise location-based sunlight assessment at multiple points across the property, enhancing measurement precision through systematic spatial segmentation
4Measurement precision
If grid-based sunlight assessment is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The lawn is divided into a grid of defined areas with specific coordinates, allowing systematic and precise sunlight assessment at multiple standardized locations across the property, improving measurement precision through structured spatial division
Solution Approach 2:
The system uses a unified grid-based approach that can assess sunlight conditions across entire properties or specific zones, providing versatile functionality for different lawncare needs while maintaining consistent measurement precision throughout
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise sunlight monitoring and data-driven lawn care recommendations, optimizing water conservation and vegetation health, and reducing the need for manual labor and professional services.
Implementation Method 1
a light sensor that generates sensor light data based on observed light
Data Source
AI summary
Systems and methods are provided to assess light conditions at a location. The system can include a computer processor (CP) and a database. The database can store a grid map that includes a plurality of grid areas that segregate the location. The system can include a location sensor and a light sensor that generates sensor light. The CP can perform processing including: (1) determining that a sample event has been attained; (2) inputting sample data including location data and light data, (3) identifying, based on the location data, a grid area, of the plurality of grid areas, that corresponds to the location data; and (4) associating, based on the identifying, the sample with the grid area. The processing can further include (5) aggregating the sample with a previous sample that has been associated with the grid area; (6) generating a light value result based on the light level value and the previous light level value; and (7) applying the light value.