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Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation
- Publication Year :
- 2024
-
Abstract
- Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of reliability and energy efficiency. However, its application in the field of wastewater flow estimation remains underexplored due to: (1) a lack of available datasets, (2) inconvenient toolchains for on-device AI model development and deployment, and (3) hardware platforms designed for general DL purposes rather than being optimized for energy-efficient soft sensor applications. This study addresses these gaps by proposing an automated, end-to-end solution for wastewater flow estimation using a prototype IoT device.<br />Comment: This paper is accepted by 2024 IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT)
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2407.05102
- Document Type :
- Working Paper