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Title	Anomalies Detection On Attached Iot Device At Cattle Body In Smart Cities Areas Using Deep Learning
ID_Doc	9597
Authors	Rajawat A.S.; Bedi P.; Goyal S.B.; Shaw R.N.; Ghosh A.; Aggarwal S.
Year	2022
Published	Studies in Computational Intelligence, 1002
DOI	http://dx.doi.org/10.1007/978-981-16-7498-3_14
Abstract	The anomalies detection on attached IoT devices on cattle in Smart Cities Areas using deep learning that help administrator to identify the unauthorized accessing of attached IoT device on Cattle Body. In this research work, we proposed deep learning techniques by real-time monitoring for extracting data and comparing current temperature, up temperature, down temperature humidity. In this research work main objective is to develop cattle farming technologies in Smart Cities Areas for smarter, Secure, and use the Internet of Things, alias IoT, to keep track of system behaviour and unauthorized accessing. Each object is labelled with a portable gadget. Our proposed wearable interface and sink node are architecturally based on the cloud system. Early detection of malicious and illicit access recognition of abnormalities to design IoT based smart sensor system for securing cattle body area network environment using deep learning. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Author Keywords	Anomalies detection; Deep learning; IoT device; Smart city; Smart sensor system

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