Development of a Pest Automatic Diagnosis System for Intelligent Agriculture Using Image Recognition

Nowadays, the intelligent agriculture is rapidly developing in most of the countries. In some advanced countries, both the research and development of agricultural-related technology and the application of innovative technology have actively been supported with the policies in the recent years. In this paper, the study on agricultural pest and disease diagnosis system is discussed and evaluated. The pest automatic diagnosis system platform is implemented and constructed with image recognition, artificial intelligence algorithm, and network monitoring system. By using image recognition on pest identification and scientific management can achieve the primary goal of intelligent prevention and precision monitoring in agriculture, whereas data analysis of farmland is fulfilled to provide farmers with data-based information, so that farmers can immediately understand the status of the farmland, such as weather conditions, spraying time, pest quantity, pest distribution, etc. Additionally, through the diagnosis and analysis of image recognition and AI algorithm, the grading and amount of variable pesticide spraying is determined to improve and enhance the control of pest and disease and to achieve the goal of reducing pesticide usage and environmental pollution