Wireless Sensor Networks for Intelligent Agricultural and Health Monitoring

Abstract

WSNs have become a revolutionary technology in real time monitoring in the agricultural and health sector but issues of power, data integrity, scalability, and security of communication hinder their implementation at a large scale. Poor practices in irrigation, degradation of soil and unpredictable climatic changes lower crop productivity in intelligent agriculture. Likewise, with health monitoring, absence of continuous, remote, and low-cost patient monitoring increases the chances of late diagnosis and emergency intervention. The given limitations of the current paper have been overcome through the introduction of an elaborate WSN-based approach to intelligent agricultural and health monitoring applications. The first goal is the development of an energy efficient scalable and very-secure system of WSN architecture that can handle data acquisition (environmental and physiological) in real-time, data transmission, and analytics. The suggested approach combines low-power sensor nodes, adaptive clustering algorithms, edge-based preprocessing of data, and machine learning models with the help of the cloud to perform a predictive analysis. Agriculture monitors soil moisture, temperature, humidity, and nutrients to improve irrigation accuracy and crop assessment, while healthcare uses wearable biosensors for continuous monitoring of heart rate, temperature, and oxygen saturation. The management strategy uses routing algorithms that are energy conscious, data aggregation and data anomaly detection models to improve the network lifetime and accuracy of decisions. Data integrity and privacy are provided with security measures such as lightweight encryption and authentication. This paper encompasses system architecture design, the optimization of communication protocol, the measurement of performance, and the possible implementation situation in the real world, which will prove the viability of WSN-based intelligent monitoring systems to apply in sustainable agriculture and smart healthcare systems.