Time-Constrained Ensemble Sensing With Heterogeneous IoT Devices in Intelligent Transportation Systems
نویسندگان
چکیده
Recently we have witnessed the rise of Artificial Intelligence Things (AIoT) and shift sensing paradigm from cloud-centric to edge-centric, which effectively improves capability intelligence transportation systems. To improve real-time performance, in this work propose an ensemble based scheme solve time-constraint synchronized inference problem achieve robust with heterogeneous IoT devices We design implement Ensen, incorporates various novel techniques such as customized DNN model design, KD-based training, dynamic deep management, etc., improved accuracy maximize computational resource usage whole group. Extensive evaluations on different types common shown that Ensen achieves a performance can be easily extended convolutional neural networks.
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IIT Madras sponsored by the Ministry of Urban Development. The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Ministry that funded the project or IIT Madras. This report is not a standard, specification, or regulation. The rapid...
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ژورنال
عنوان ژورنال: IEEE Transactions on Intelligent Transportation Systems
سال: 2022
ISSN: ['1558-0016', '1524-9050']
DOI: https://doi.org/10.1109/tits.2022.3170028