AppleAero: Drone-Based Intelligent System for Apple Orchard Management

Abstract

The present invention relates to an AppleAero: Drone-Based Intelligent System for Apple Orchard Management. The AppleAero system introduces an intelligent, drone-based solution for managing apple orchards, targeting challenges such as tree health monitoring, nutrient and pest management, accurate yield estimation, and enhanced marketing. Equipped with multispectral and thermal imaging sensors, the drones collect data on apple tree health, which is analyzed by AI algorithms for early detection of issues. Precision application of fertilizers and pesticides reduces waste, while yield estimation models aid in logistics planning. AppleAero also integrates blockchain-based traceability, virtual orchard tours, and digital marketing to boost consumer trust and demand, thereby enhancing profitability for apple farmers. Accompanied Drawing [FIG. 1]

Specification

Description:[001] The present invention pertains to the field of agricultural technology, specifically drone-based intelligent systems for precision orchard management. This invention leverages aerial imaging, artificial intelligence (AI), and machine learning (ML) to provide detailed insights into apple orchards, optimizing tree health monitoring, nutrient and pest management, yield estimation, and marketing.
BACKGROUND OF THE INVENTION
[002] The following description provides the information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[003] Apple orchards are a cornerstone of agricultural productivity in regions such as Himachal Pradesh and Jammu & Kashmir, producing over 600,000 metric tons of apples annually in Himachal alone. Despite the significance of apple production, orchard management faces criti , Claims:1. A drone-based system for apple orchard management, comprising:
I. a multispectral imaging module for assessing tree health based on chlorophyll levels and leaf moisture,
II. a thermal imaging sensor for detecting water stress, pests, and diseases,
III. an AI processing unit that analyzes collected data to generate actionable insights for precision agriculture.
2. The system of claim 1, wherein the drone further includes a precision application system for targeted delivery of fertilizers, pesticides, and fungicides, reducing resource waste and environmental impact.
3. An intelligent system for orchard yield estimation, comprising:
I. drones equipped with high-resolution imaging sensors for capturing detailed imagery of apple blossoms and fruit set,
II. machine learning algorithms configured to process image data and provide accurate yield forecasts based on historical data and environmental conditions.
4. The system of claim 3, further comprising a pre-harvest planning module that uses yield forecasts to as

Documents