A Descriptive Study on Wireless Sensor Networks (WSNs) using Cloud Computing (CC)
Abstract
This paper presents a descriptive study on Wireless Sensor Networks (WSNs) using Cloud Computing (CC). WSNs are widely used in various applications, including environmental monitoring, industrial automation, and healthcare. However, WSNs face several challenges, such as limited storage capacity, processing power, and energy constraints. Cloud Computing (CC) provides a viable solution to overcome these challenges by providing a scalable, cost-effective, and on-demand computing platform for WSNs.
The paper examines the benefits and challenges of using Cloud Computing (CC) in WSNs. Moreover, the study analyzes the current trends and future directions of cloud-based WSNs, including the use of edge computing, machine learning, and artificial intelligence. The paper also discusses the security and privacy concerns associated with cloud-based WSNs and examines the different security solutions and best practices to ensure the security and privacy of WSNs.
Overall, this descriptive study provides valuable insights into the integration of Cloud Computing (CC) with Wireless Sensor Networks (WSNs) and highlights the potential of cloud-based WSNs to transform various industries and domains. The study serves as a useful resource for researchers, practitioners, and organizations interested in leveraging the power of Cloud Computing (CC) for Wireless Sensor Networks (WSNs).
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