학술논문

Advanced Agro Management Using Machine Learning and IoT
Document Type
Conference
Source
2023 IEEE North Karnataka Subsection Flagship International Conference (NKCon) North Karnataka Subsection Flagship International Conference (NKCon), 2023 IEEE. :1-6 Nov, 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Visualization
Machine learning algorithms
Crops
Flowering plants
Sensor systems
Sensors
Diseases
esp32 cam
Arduino
web application and Inception V3
Language
Abstract
In this research study, we aim to create a revolutionary agricultural management portal that is capable of identifying diseases in leaves, flowers, and fruits deploying an Arduino Board, an Esp32-camera module to collect real-time visuals and machine learning algorithms. Through the integration of sensors and cameras into the agricultural environment, our system can collect information on crop development and health as well as recognize and diagnose illnesses. As a result, choices like irrigation strategies, fertilization, and pest control can be made knowing exactly what diseases are present and how they might impact crop health thanks to machine learning algorithms like InceptionV3.Through an all-inclusive Full Stack web application, which will identify the ailment, prescribe items for treatment, and provide the option to purchase them.The technology utilized in this research is projected to improve sustainable crop growing practices, raise flower, fruit, and leaf yields, and minimize crop losses, as well as provide a trained consultation alternative for one-on-one personal assistance.