Abstract
The abstract of the article discusses the increasing global population and the resulting need for enhanced food production to meet the growing demand. It highlights the use of drone technology in agriculture for crop monitoring, pesticide spraying, and precision agriculture to address constraints in crop production. The abstract also mentions advancements in drone technology, sensor development, and the integration of Artificial Intelligence (AI) and deep learning for remote crop monitoring.
Introduction
The introduction highlights the challenges of increasing food production to meet the growing global population, emphasizing the need for modernizing agriculture practices. It mentions the Food and Agriculture Organization's data on chronic hunger, the necessity to enhance food production by 50% by 2050, and the diminishing resources like land and water for agriculture. The text underscores the importance of addressing food security issues through advancements in agricultural technology, such as drone technology for crop monitoring and pesticide spraying.
Drone in Agriculture
Agricultural drones, also known as UAVs (Unmanned Aerial Vehicles), are being increasingly utilized in the agriculture sector for tasks like crop monitoring and pesticide spraying. These drones offer benefits such as cost-effectiveness, time-saving, and high-resolution image capture, aiding farmers in making informed decisions for better crop management. The drones come in different types like fixed-wing, helicopter, and multi-copter, each with its own advantages and applications in precision agriculture.
Crop condition monitoring
Crop health monitoring involves the use of drones equipped with cameras and advanced image analysis tools to detect diseases, nutrient deficiencies, and water stress in crops. By capturing images and creating vegetation indices maps, drones help differentiate between healthy plants, unhealthy plants, and weeds, providing valuable insights for farmers to take corrective actions and optimize crop yield. This technology has revolutionized traditional crop monitoring methods by enabling real-time data analysis and precise identification of crop health issues.
Digital color camera images
A digital color-infrared camera system was developed for monitoring wheat fields, allowing analysis of crop conditions and soil types based on Green Normalized Difference Vegetation Indices (GNDVI). This lightweight and compact system was used with a Vector-P UAV controlled by an autopilot program to capture images at specific points. The technology provided valuable data for agricultural applications, although it had limitations in precise control and image capturing capabilities.
Relation between color and health
The relation between plant health and image spectrum refers to the connection between the health status of plants and the specific wavelengths of light they reflect or absorb. By analyzing the spectrum of light reflected by plants, researchers can assess their health condition, detect diseases, monitor growth, and evaluate nutrient levels. Different plant health indicators, such as chlorophyll content or stress levels, can be inferred by studying how plants interact with different wavelengths of light, providing valuable insights for precision agriculture and crop management.
Plant protection spraying
Pesticide spraying traditionally involves manual methods that can pose health risks and environmental concerns due to inefficiencies and overuse of chemicals. To address these issues, drone-mounted sprayers are being utilized, offering advantages such as increased coverage, improved effectiveness, and reduced human labor. These drones can carry large pesticide tanks, follow pre-programmed routes, and are proving to be more efficient and effective in controlling pests and diseases in agriculture.
Future challenges and conclusions
The text discusses the advancements in drone technology for precision farming, focusing on crop monitoring and pesticide spraying applications. It highlights the evolution of drone structures, sensor development, innovation in pesticide spraying drones, and the integration of deep learning and AI for crop monitoring. The increasing adoption of drones in precision agriculture post-2017 is attributed to weight reduction, cost-effectiveness, and improved payload capacity, signaling a shift towards more efficient and automated farming practices.