IOGRUCloud: A Scalable AI-Driven IoT Platform for Climate Control in Controlled Environment Agriculture

TL;DR

IOGRUCloud is a scalable, AI-driven IoT platform for climate control in agriculture, reducing energy use and improving climate stability through advanced control algorithms and cloud-edge integration.

Contribution

The paper introduces IOGRUCloud, a novel three-tier IoT platform that combines AI control with edge computing for automated greenhouse climate management.

Findings

Reduced manual calibration effort by 73%.

Achieved 23% energy savings in greenhouses.

Maintained 99.7% system uptime handling 2.3 million sensor events daily.

Abstract

Controlled Environment Agriculture (CEA) demands precise, adaptive climate management across distributed infrastructure. This paper presents IOGRUCloud, a scalable three-tier IoT platform that integrates AI-driven control with edge computing for automated greenhouse climate regulation. The system architecture separates field-level sensing and actuation (L1), facility-level coordination (L2), and cloud-level optimization (L3-L4), enabling progressive autonomy from rule-based to fully autonomous operation. A Vapor Pressure Deficit (VPD) cascading control loop governs temperature and humidity with GRU-enhanced PID tuning, reducing manual calibration effort by 73%. Deployed across 14 production greenhouses totaling 47,000 m2, the platform demonstrates 23% reduction in energy consumption and 31% improvement in climate stability versus baseline. The system handles 2.3M daily sensor events with 99.7% uptime. We release the architecture specification and deployment results to support reproducibility in smart agriculture research.