论文标题
迈向设备的AI和区块链，以实现6G启用农业供应链管理
Towards On-Device AI and Blockchain for 6G enabled Agricultural Supply-chain Management
论文作者
论文摘要
6G设想人工智能（AI）有动力的解决方案，以增强网络中的服务质量（QoS）并确保资源的最佳利用。在这项工作中，我们提出了一个基于无人机（UAV），AI和区块链的结合，用于农业供应链管理，以确保可追溯性，透明度，跟踪库存和合同。我们提出了一种解决方案，以通过产生具有各种资源准确权衡权衡的模型的路线图来促进设备AI。完全卷积神经网络（FCN）模型通过无人机捕获的图像进行生物量估计。我们激发了迭代修剪的想法，提供具有各种复杂性和准确性的多种特定任务模型，而不是用于在无人机上部署的单一压缩FCN模型。为了减轻启用6G的动态无人机网络中飞行故障的影响，提出的模型选择策略将帮助无人机根据运行时资源需求更新模型。
6G envisions artificial intelligence (AI) powered solutions for enhancing the quality-of-service (QoS) in the network and to ensure optimal utilization of resources. In this work, we propose an architecture based on the combination of unmanned aerial vehicles (UAVs), AI and blockchain for agricultural supply-chain management with the purpose of ensuring traceability, transparency, tracking inventories and contracts. We propose a solution to facilitate on-device AI by generating a roadmap of models with various resource-accuracy trade-offs. A fully convolutional neural network (FCN) model is used for biomass estimation through images captured by the UAV. Instead of a single compressed FCN model for deployment on UAV, we motivate the idea of iterative pruning to provide multiple task-specific models with various complexities and accuracy. To alleviate the impact of flight failure in a 6G enabled dynamic UAV network, the proposed model selection strategy will assist UAVs to update the model based on the runtime resource requirements.
