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Title	Real-Time Image-Based Automotive Sensing: A Practice On Fine-Grained Garbage Disposal
ID_Doc	44375
Authors	Huang W.; Mikami K.; Chen Y.; Nakazawa J.
Year	2023
Published	ACM International Conference Proceeding Series
DOI	http://dx.doi.org/10.1145/3627050.3627058
Abstract	This research presents a real-Time automotive sensing system for the data of urban garbage disposal. The proposed solution is implemented on an edge computing device mounted on garbage truck where a deep learning based image processing algorithm is implemented to automatically counted the number of collected garbage bags from garbage collection video. A MQTT-based data server was developed to enable data publication from sensing device to server and data accumulation and to facilitate application development. Our system has the functions of high concurrency and low transmission delay, offline reconnection, breakpoint transmission and client authentication. This work is to provide a real-Time, low-cost, reliable and replicable system for the implementation of a widespread sensing network for automotive edge computing and smart city applications. © 2023 Owner/Author.
Author Keywords	automotive sensing; edge computing; garbage collection; MQTT; smart cities

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