Cyber-physical system integration for autonomous decision-making in sensor-rich indoor cultivation environments
Adeoluwa Abraham Olasehinde, Anthony Osi Blessing, Joy Chizorba Obodozie, Somadina Obiora Chukwuemeka
Abstract
The increasing demand for sustainable food production in the face of climate variability, urbanization, and land constraints has accelerated the evolution of smart indoor cultivation systems. Central to this transformation is the integration of cyber-physical systems (CPS) that tightly couple computational intelligence with physical processes through embedded sensors, IoT networks, and actuation layers. This paper explores the role of CPS in enabling autonomous decision-making within sensor-rich, controlled agricultural environments, where real-time responsiveness and precision are critical for optimizing both crop performance and resource utilization. Leveraging advances in Internet of Things (IoT) fusion and edge computing, CPS-based architectures allow for localized, low-latency processing of high-frequency data streams originating from multi-modal sensors—such as temperature, humidity, nutrient concentration, CO₂ levels, and multispectral imaging. These sensor arrays, integrated with feedback control algorithms, create adaptive environments that dynamically regulate variables like light spectra, irrigation cycles, and nutrient dosing without human intervention. The paper presents a layered CPS framework that combines physical plant-environment interactions with cyber intelligence models for predictive analytics, anomaly detection, and autonomous control. Emphasis is placed on distributed decision-making mechanisms at the edge, which reduce cloud dependence while increasing fault tolerance and system scalability. Case studies of vertical farms and research-driven plant growth chambers demonstrate how CPS integration enhances yield quality, reduces input waste, and improves system resilience under varying environmental loads. Ultimately, this work outlines the design principles, technological enablers, and implementation pathways for building next-generation, self-regulating indoor farming systems through CPS, bridging the gap between plant biology, control engineering, and intelligent automation.