A Cloud-Based Virtual Sensor Approach for Intelligent Marine Water Quality Monitoring
Keywords:
Marine Water Quality Monitoring, Virtual Sensors, Internet of Things (IoT), Azure IoT Central, AI-Based Monitoring, Cloud-Based AnalyticsAbstract
Recent studies indicate that the practical implementation of virtual sensors is closely associated with Internet of Things (IoT) technologies, which enable continuous data acquisition and reliable transmission from distributed sensing devices. The rapid scalability of IoT systems and the exponential growth of telemetric data streams have created an increasing demand for cloud computing integration, allowing efficient storage, processing, and real-time analysis of large-scale datasets [1], [2]. The literature emphasizes that cloud platforms provide a favorable environment for the deployment of virtual sensing frameworks, as they support centralized data management, dynamic allocation of computational resources, and advanced analytical capabilities [3], [4].
The integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms with IoT-based cloud infrastructures is widely recognized as a key enabler for the development of intelligent monitoring systems. Numerous studies demonstrate that AI/ML techniques significantly enhance anomaly detection accuracy, predictive analytics performance, and real-time decision support, particularly when virtual sensors are employed to estimate environmental parameters or validate physical measurements [1], [5], [6]. This approach reduces the impact of measurement noise and sensor drift while improving the overall reliability and robustness of monitoring systems.
Although peer-reviewed publications specifically focused on Azure IoT Central remain relatively limited, the broader scientific and technical literature confirms the potential of cloud-based IoT platforms to provide secure communication, scalable analytics, real-time data ingestion, and predictive insight generation [2], [3], [7],[8]. Therefore, existing research suggests that the integration of virtual sensors, IoT technologies, and cloud infrastructures represents a promising and still underexplored direction for the development of intelligent marine water quality monitoring systems, reinforcing the scientific relevance and practical significance of this study.
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