Abstract
This paper introduces a framework for implementing Autonomous Elements in Controlled Environment Agriculture (CEA) systems, leveraging a Service-Oriented Architecture (SOA) and aligned with Industry 4.0 principles. By integrating artificial intelligence and the MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) control loop, the framework optimizes environmental conditions and resource management in CEA facilities. The system includes a set of Autonomous Elements—Humidity Management, Temperature Management, Nutrient Solution Control, Air Quality Management, Light Management, and Visual Plant Mass Estimation—to address critical aspects of crop cultivation. These elements are designed using SOA, decomposing system functionality into modular, reusable services, ensuring seamless communication and interoperability across components. By incorporating Industry 4.0 technologies such as IoT and edge computing, this framework enables continuous data-driven decision-making and autonomous operation to meet the demands of sustainable, high-efficiency agriculture.
| Originalsprache | Englisch |
|---|---|
| Titel | NOMS 2025-2025 IEEE Network Operations and Management Symposium |
| Erscheinungsort | https://ieeexplore.ieee.org/xpl/conhome/11073532/proceeding |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 12 Mai 2025 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
-
SDG 2 – Kein Hunger
Research Field
- Assistive and Autonomous Systems
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