EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration

arXiv:2403.14027v1 Announce Type: new
Abstract: Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative sensing system that splits the task into object localization and fine-grained classification. Objects are classified either at the edge or within the cloud, based on their estimated difficulty. The framework comprises a low-power device-tailored front-end model for object localization, classification, and difficulty estimation, along with a transformer-graph convolutional network-based back-end model for fine-grained classification. …

abstract arxiv challenges classification cloud collaboration collaborative complexities cs.cv deployment detection edge energy fine-grained intelligent localization marine object objects sensing ship the edge through type