A Structured Analytical Review of Cyber-Physical Systems and Edge Computing Architectures for Soil Health Monitoring in Uganda: A Case Study of the Eastern Region Agricultural Sector

Purpose: This paper aims to analyze existing Cyber-Physical Systems (CPS) architectures for soil health monitoring and the integration of edge computing, with a focus on identifying security gaps that hinder reliable and trustworthy real-time agricultural intelligence in Uganda’s Eastern Region. Methodology: A structured systematic literature review was conducted on peer-reviewed publications published between 2020 and 2025. The review examined global and sub-Saharan African CPS-based soil health monitoring architectures, with particular attention to edge computing integration, security mechanisms, and architectural design patterns. Architectural, technological, and security dimensions were synthesized to identify recurring vulnerabilities and gaps relevant to Uganda’s agricultural context. Findings: The review reveals significant architectural fragmentation, inconsistent security implementations, and limited cross-layer protection across sensing, communication, edge, and application layers. Existing deployments remain vulnerable to sensor spoofing, physical tampering, insecure edge gateways, malware propagation, and compromised data transmission. While promising advancements exist such as ML-driven anomaly detection, federated learning, cryptographic safeguards, and IT/OT convergence these solutions are often applied in isolation rather than within holistic CPS-edge security frameworks. Unique Contribution to Theory, Policy, and Practice: The study advances CPS and edge computing research by synthesizing fragmented architectural and security perspectives into a unified cross-layer analytical view. It provides evidence to support the development of secure smart agriculture and digital transformation policies in Uganda and similar contexts. The study outlines a conceptual direction for designing an integrated, secure CPS–edge architecture tailored to real-time soil health monitoring, supporting more resilient, trustworthy, and scalable agricultural decision-making systems.