Towards On-Device AI and Blockchain for 6G enabled Agricultural
Supply-chain Management
- URL: http://arxiv.org/abs/2203.06465v1
- Date: Sat, 12 Mar 2022 15:36:23 GMT
- Title: Towards On-Device AI and Blockchain for 6G enabled Agricultural
Supply-chain Management
- Authors: Muhammad Zawish, Nouman Ashraf, Rafay Iqbal Ansari, Steven Davy,
Hassan Khaliq Qureshi, Nauman Aslam and Syed Ali Hassan
- Abstract summary: We propose an architecture based on the combination of unmanned aerial vehicles (UAVs), AI and blockchain for agricultural supply-chain management.
A fully convolutional neural network (FCN) model is used for biomass estimation through images captured by the UAV.
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.
- Score: 10.189149128814096
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: 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.
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