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A Novel Association Rule-Based Data Mining Approach for Internet of Things Based Wireless Sensor Networks

IEEE Access • 2021
العودة
معلومات البحث
المؤلفون Ahmed M Khedr, Walid Osamy, Ahmed Salim, Sohail Abbas
الكلمات المفتاحية Not Available
المجلة العلمية IEEE Access
الناشر Not Available
المجلد Not Available
العدد Not Available
الصفحات Not Available
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
Wireless Sensor Network (WSN) is one of the fundamental technologies used in the Internet of Things (IoT) which is deployed for diverse applications to carry out precise real-time observations. The limited resources of WSN with massive volume of fast-flowing IoT data make the aggregation and analytics of data more challenging. Recently, data mining-based solutions have been proposed to effectively handle the data being generated by the sensors and to analyze the data patterns for deducing the required information from it. The increasing need of these techniques motivated us to propose a distributed and efficient data mining technique that not only handles the massive and rapidly generated data by the nodes, but also increases the life span of the network. In this paper, we propose a novel scheme for the IoT based WSN that mines the sensor data using association rule without moving it to any Cluster Head …