Sensors, Vol. 21, Pages 5082: Wearable Edge AI Applications for Ecological Environments
Sensors, Vol. 21, Pages 5082: Wearable Edge AI Applications for Ecological Environments
Sensors doi: 10.3390/s21155082
Authors:
Mateus C. Silva
Jonathan C. F. da Silva
Saul Delabrida
Andrea G. C. Bianchi
Sérvio P. Ribeiro
Jorge Sá Silva
Ricardo A. R. Oliveira
Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in ...
Source: Sensors - Category: Biotechnology Authors: Mateus C. Silva Jonathan C. F. da Silva Saul Delabrida Andrea G. C. Bianchi S érvio P. Ribeiro Jorge S á Silva Ricardo A. R. Oliveira Tags: Article Source Type: research