20240023490. Apparatus and Method for Controlling a Growth Environment of a Plant simplified abstract (Vivent SA)
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Apparatus and Method for Controlling a Growth Environment of a Plant
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Apparatus and Method for Controlling a Growth Environment of a Plant - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240023490 titled 'Apparatus and Method for Controlling a Growth Environment of a Plant
Simplified Explanation
The abstract describes a method for controlling the growth environment of a plant using machine learning and electrical signals obtained from the plant. Here is a simplified explanation of the patent application:
- The method involves obtaining an electrical signal from a plant.
- Prediction data is generated based on the electrical signal using at least one machine learning model.
- The machine learning model has been trained to assess at least one characteristic of the plant.
- The prediction data indicate an assessment of the plant's characteristic(s) based on the output of the machine learning model.
- A user-defined rule set is applied to the prediction data to generate a plant control signal.
- The plant control signal is designed to change the growth environment of the plant.
Potential applications of this technology:
- Precision agriculture: The method can be used to optimize the growth environment of plants in agricultural settings, leading to increased crop yields and resource efficiency.
- Horticulture: It can be applied in controlled environments like greenhouses to enhance plant growth and improve the quality of flowers, fruits, and vegetables.
- Plant research: The method can aid in studying and understanding the responses of plants to different environmental conditions, helping researchers in various fields such as genetics and plant physiology.
Problems solved by this technology:
- Inefficient resource utilization: By accurately assessing plant characteristics and adjusting the growth environment accordingly, the method can optimize resource usage, reducing waste and improving sustainability.
- Inconsistent plant growth: The machine learning models can provide real-time assessments of plant characteristics, allowing for timely interventions to maintain consistent growth and prevent issues like nutrient deficiencies or diseases.
Benefits of this technology:
- Increased crop yields: By optimizing the growth environment based on plant assessments, the method can potentially enhance crop productivity and improve overall agricultural output.
- Resource efficiency: The precise control of the growth environment can lead to reduced water, fertilizer, and energy consumption, making agriculture more sustainable.
- Real-time monitoring: The use of machine learning models and electrical signals enables continuous monitoring of plant characteristics, allowing for proactive interventions and better plant management.
Original Abstract Submitted
there is provided a method of controlling a growth environment of a plant , the method comprising: obtaining an electrical signal from the plant; generating, using at least one machine learning model, prediction data based upon the electrical signal, wherein the at least one machine learning model has been trained to assess at least one characteristic of the plant, and wherein the prediction data are based upon output(s) of the at least one machine learning model and indicate an assessment of the at least one characteristic of the plant; and applying a user defined rule set to the prediction data to generate a plant control signal, wherein the plant control signal is configured to change the growth environment of the plant.
