Edge-Cloud Architectures Using UAVs Dedicated To Industrial IoT Monitoring And Control Applications

The deployment of new technologies to ease the control and management of a massive data volume and its uncertainty is a very significant challenge in the industry. Under the name "Smart Factory", the Industrial Internet of Things (IoT) aims to send data from systems that monitor and control the physical world to data processing systems for which cloud computing has proven to be an important tool to meet processing needs. unmanned aerial vehicles (UAVs) are now being introduced as part of IIoT and can perform important tasks. UAVs are now considered one of the best remote sensing techniques for collecting data over large areas. In the field of fog and edge computing, the IoT gateway connects various objects and sensors to the Internet. It function as a common interface for different networks and support different communication protocols. Edge intelligence is expected to replace Deep Learning (DL) computing in the cloud, providing a variety of distributed, low-latency and reliable intelligent services. In this paper, An unmanned aerial vehicle is automatically integrated into an industrial control system through an IoT gateway platform. Rather than sending photos from the UAV to the cloud for processing, an AI cloud trained model is deployed in the IoT gateway and used to process the taken photos. This model is designed to overcome the latency channels of the cloud computing architecture. The results show that the monitoring and tracking process using advanced computing in the IoT gateway is significantly faster than in the cloud.