智慧水稻栽培數位分身
Journal
精農生機研究與發展學術研討會專刊
Part Of
農業試驗所特刊第245號
Pages
157-157
ISBN
978-626-7651-10-0
Date Issued
2025-01
Author(s)
黃毓翔
吳以健
詹品晟
吳霽函
黃能富
Abstract
To enable adaptive responses to abrupt shifts in operational conditions, smart farming necessitates real-time management systems, often called cyber-physical systems. These systems achieve dynamic adjustments by incorporating sensing and monitoring capabilities, intelligent analytics and planning, and the efficient management of various farm operations across different processes. To minimize farmer intervention and enhance autonomy, digital twin systems emerge as pivotal components, creating digital replicas of intricate physical systems. In the context of Agriculture 4.0, this paper focuses on the development of a smart agriculture platform with a specific case study for paddy cultivation. This comprehensive platform integrates an AIoT-driven data collection and monitoring system, a smart irrigation system, and an AI model service system for image and data analysis. The web-based user interface includes Line notification services. By merging digital twins with Artificial Intelligence of Things (AIoT), big data analytics, computer vision, human expertise, and machine learning, the aim is to enhance the monitoring, diagnosis, prediction, and optimization of various parameters within a sophisticated paddy cultivation system. Utilizing diverse computer vision and AI techniques, this study implemented and examined several models for key growth and environmental indexes in paddy cultivation. These models encompass image recognition for individual paddy crops with 92% confidence, and crop height calculation with a 10% error rate, green coverage calculation (tillering status), leaf color classification for determining nitrogen levels, paddy disease classification and detection, soil crack width calculation, and weather monitoring.
Event(s)
精農生機研究與發展學術研討會
Proceedings of A Symposium on Research and Development of Smart Agriculture and Biomechatroincs Engineering
Subjects
Digital Twin
Agriculture 4.0
Cyber-Physical System
AIoT
paddy
machine learning
precision agriculture
Computer Vision
Publisher
農業部農業試驗所
Type
poster
File(s)![Thumbnail Image]()
Loading...
Name
no245-38.pdf
Size
463.67 KB
Format
Adobe PDF
Checksum
(MD5):275c8c3790885351a5506bdd4c5d7ec7