Cloud-edge-device collaborative computing in smart agriculture: architectures, applications, and future perspectives

Area of Science:

• Agricultural Science
• Computer Science
• Engineering

Background:

• Growing global demand for food security and sustainable resource management drives smart agriculture innovation.
• Traditional centralized computing architectures face limitations in processing and decision-making for complex agricultural needs.

Purpose of the Study:

• To provide a comprehensive review of cloud-edge-device collaborative computing in smart agriculture.
• To identify key application domains, challenges, and future research directions.

Main Methods:

• Literature review of cloud-edge-device collaboration architectures and applications in agriculture.
• Analysis of technical characteristics, challenges, and emerging research areas.

Main Results:

• Cloud-edge-device collaboration offers distributed intelligence, real-time processing, and adaptive decision-making.
• Key application domains include environmental monitoring, intelligent irrigation, UAV-machinery coordination, livestock health, and pest control.
• Identified challenges include device heterogeneity, data consistency, resource constraints, and privacy concerns.

Conclusions:

• Cloud-edge-device collaboration is crucial for next-generation smart agriculture systems.
• Outlined research directions include intelligent scheduling, edge AI, data fusion, federated learning, interoperability, and digital twins.
• This review serves as a foundation for designing and implementing advanced smart agriculture solutions.