System and method for implementing neural network models on edge devices in IoT networks
US11176421B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 23, 2019 |
| Grant date | Nov 16, 2021 |
| Priority date | — |
| Expiry date | Nov 21, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a system for implementing neural network models on edge devices in an Internet of Things (IoT) network are disclosed. In an embodiment, the method may include receiving a neural network model trained and configured to detect objects from images, and iteratively assigning a new value to each of a plurality of parameters associated with the neural network model to generate a re-configured neural network model in each iteration. The method may further include deploying for a current iteration the re-configured neural network on the edge device. The method may further include computing for the current iteration, a trade-off value based on a detection accuracy associated with the at least one object detected in the image and resource utilization data associated with the edge device, and selecting the re-configured neural network model, based on the trade-off value calculated for the current iteration.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.