Toward On-Device AI and Blockchain for 6G-Enabled Agricultural Supply Chain Management

Muhammad Zawish, Nouman Ashraf, Rafay Iqbal Ansari, Steven Davy, Hassaan Khaliq Qureshi, Nauman Aslam, Syed Ali Hassan

Research output: Contribution to journalArticlepeer-review

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 and 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 UAVs, 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.
Original languageEnglish
Pages (from-to)160-166
Number of pages7
JournalIEEE Internet of Things Magazine
Volume5
Issue number2
DOIs
Publication statusPublished - 1 Jun 2022

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