Sensor-Based Plant Location Selection for Light and Air Quality
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Solution Overview
Problem
Existing systems fail to optimally determine suitable locations for indoor plants considering environmental characteristics such as occupancy, air quality, and light levels, which affects their ability to enhance occupant well-being and thrive.
Innovation Solution
A sensor system that collects occupancy, air characteristic, and light data to select optimal plant locations based on weighted selection rules balancing occupant-friendly and plant-friendly conditions, with optional reselection and automated plant relocation or luminaire control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If plants are placed in locations with good lighting conditions, then plant health is improved, but locations with good lighting may not necessarily provide optimal air quality or occupancy benefits
Solution Approach 1:
The system changes multiple environmental parameters simultaneously (lighting, air quality, occupancy patterns) to evaluate location suitability. Instead of relying on a single parameter like lighting alone, the patent integrates multiple parameters to dynamically assess and select optimal plant locations that satisfy both plant health requirements and environmental benefits.
2Ease of operation
If plants are placed to maximize air quality improvement in high-occupancy areas, then occupant well-being is enhanced, but plants may not receive adequate lighting or other conditions needed to thrive
Solution Approach 1:
The system evaluates multiple environmental parameters including light levels, air quality metrics, and occupancy data to find locations that satisfy both occupant well-being goals and plant survival requirements. The weighted selection rules balance competing objectives by considering changes in multiple parameters simultaneously rather than optimizing for a single outcome.
3Device complexity
If manual plant placement is used based on simple criteria, then device complexity is low, but the system cannot dynamically adapt to changing environmental conditions or optimize multiple competing objectives
Solution Approach 1:
The system continuously collects data from sensors monitoring lighting conditions, air quality, and occupancy patterns. This feedback loop enables the system to dynamically reassess plant location suitability and make adjustments based on changing environmental conditions, moving from static manual placement to adaptive automated optimization.
Solution Approach 2:
The system performs preliminary assessment of multiple potential locations by evaluating environmental parameters before making placement decisions. The weighted selection rules pre-establish criteria for evaluating locations, allowing the system to systematically compare and select optimal positions before plants are actually placed or relocated.
4Adaptability or versatility
If plants are relocated frequently to optimize conditions, then environmental suitability is maximized, but this increases operational complexity and disruption
Solution Approach 1:
The system implements periodic reassessment of plant locations based on collected environmental data rather than continuous or frequent relocation. By establishing evaluation intervals and using weighted selection rules to assess when relocation is truly necessary, the system balances adaptability with operational efficiency, avoiding unnecessary disruptions while maintaining optimal conditions.
Data Source
Figure 1A~1B
Figure 1C~1D
Figure 2~3
AI summary
The invention concerns a system (100) and method (200) for managing plants in one or more spaces or areas. The system (100) comprising a processing apparatus (120) arranged to receiving respective first sensor data for a plurality of locations in said one or more spaces or areas, wherein the first sensor data comprises at least one of the following: respective occupancy data for said plurality of locations, where the occupancy data for a given location is descriptive of occupancy at the respective location as a function of time, and respective air characteristic data for said plurality of locations, where the air characteristic data for a given location is descriptive of at least one characteristic of air at the respective location as a function of time; receiving respective light sensor data for said plurality of locations, wherein the light sensor data for a given location is descriptive of light level at the respective location as a function of time; and selecting, from said plurality of locations, one or more locations for the plants based on the first sensor data in consideration of the light sensor data.