Technological Integration for Micronutrient Monitoring in Water Systems

Abstract The convergence of Internet of Things (IoT) and cloud computing offers a transformative approach to micronutrient monitoring in environmental and agricultural systems. As IoT devices generate continuous data streams, cloud platforms provide scalable resources for real-time processing, analysis, and storage. This systematic review, conducted under PRISMA 2020 guidelines, examined 36 studies on IoT–cloud integration for micronutrient detection. Most studies were sourced from Google Scholar (50.00%), Web of Science (33.33%), and SCOPUS (16.67%). Peer-reviewed journal articles dominated (72.22%), with Asia contributing the highest share of research (50.00%), led by India (30.56%). Surface water was the most monitored source (38.89%), followed by treated water (19.44%) and groundwater (13.89%). Chemical parameter sensors were most common (43.90%), and Arduino platforms were the predominant hardware (52.78%), with GSM communication technologies leading (46.43%). Unspecified cloud platforms accounted for 25.00%, while AI-enhanced cloud solutions represented 14.29%. Core challenges identified include data volume, energy constraints, latency, interoperability, and security vulnerabilities, particularly in remote settings. The findings highlight the need for robust, context-aware IoT–cloud frameworks, improved reporting standards, and the adoption of AI and edge–cloud architectures to enhance sustainable, data-driven decision-making in precision micronutrient management.