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Improved Multimedia Object Processing for the Internet of Vehicles

Bhatia, S and Alsuwailam, RI and Roy, DG and Mashat, A (2022) Improved Multimedia Object Processing for the Internet of Vehicles. In: Sensors, 22 (11).

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Official URL: https://doi.org/10.3390/s22114133


The combination of edge computing and deep learning helps make intelligent edge devices that can make several conditional decisions using comparatively secured and fast machine learning algorithms. An automated car that acts as the data-source node of an intelligent Internet of vehicles or IoV system is one of these examples. Our motivation is to obtain more accurate and rapid object detection using the intelligent cameras of a smart car. The competent supervision camera of the smart automobile model utilizes multimedia data for real-time automation in real-time threat detection. The corresponding comprehensive network combines cooperative multimedia data processing, Internet of Things (IoT) fact handling, validation, computation, precise detection, and decision making. These actions confront real-time delays during data offloading to the cloud and synchronizing with the other nodes. The proposed model follows a cooperative machine learning technique, distributes the computational load by slicing real-time object data among analogous intelligent Internet of Things nodes, and parallel vision processing between connective edge clusters. As a result, the system increases the computational rate and improves accuracy through responsible resource utilization and active–passive learning. We achieved low latency and higher accuracy for object identification through real-time multimedia data objectification.

Item Type: Journal Article
Publication: Sensors
Publisher: MDPI
Additional Information: The copyright for this article belongs to the Author(s).
Keywords: Cameras; Data handling; Decision making; Deep learning; Learning algorithms; Multimedia systems; Object detection, Conditional decisions; Cooperative learning; Edge computing; Edge intelligence; Machine learning algorithms; Multimedia data; Multimedia object; Multimedium object processing; Object processing; Real- time, Internet of things, algorithm; automation; multimedia, Algorithms; Automation; Internet of Things; Multimedia
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 22 Sep 2022 10:02
Last Modified: 22 Sep 2022 10:02
URI: https://eprints.iisc.ac.in/id/eprint/76641

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