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Industrial IoT Sensor Networks and Cloud Analytics for Monitoring Equipment Insights and Operational Data

云计算 物联网 分析 计算机科学 数据分析 无线传感器网络 数据科学 计算机安全 计算机网络 数据挖掘 操作系统
作者
A. Arokiaraj Jovith,Chitra Sabapathy Ranganathan,S. Priya,Rajendran Vijayakumar,R. Kohila,Shiva Prakash
标识
DOI:10.1109/iccsp60870.2024.10543619
摘要

The Industrial Internet of Things (IIoT) has brought a new era of improved equipment monitoring and operational data management in manufacturing and other industrial settings. This research presents the use cases and benefits of IIoT sensor networks for gathering actionable insights and operational data from industrial machinery. Reliable IIoT sensor networks are built, including the design, deployment, data collecting, and cloud computing techniques. The achieved using constant, up-to-the-minute monitoring; reduced data collecting; and enhanced productivity. Data security, network stability, and scalability of the problems that develop during the deployment of IIoT sensor networks are covered in this paper. These networks might benefit from cloud computing to better manage and analyze the massive amounts of data the produce. The broader impacts of setting up IIoT sensor networks include savings in money and time and the ability to make more informed decisions based on data. It highlights the evolution of conventional industrial landscapes into linked ecosystems that may provide insightful decision-making data. The data for users to use sensor networks to monitor equipment and improve productivity. Reducing equipment downtime by 30% and increasing operational efficiency by 20% are both made potential by combining Industrial IoT sensor networks with cloud analytics. With an 80% success rate, maintenance techniques save a ton of money and make things more efficient.
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