TY - JOUR 
A1 - Salhaoui, Marouane
AU - Guerrero González, Antonio
AU - Arioua, Mounir
AU - Ortiz Zaragoza, Francisco José
AU - El Oualkadi, Ahmed
AU - Torregrosa Bonet, Carlos Luis
T1 - Smart industrial IoT monitoring and control system based on UAV and cloud computing applied to a concrete plant
Y1 - 2019
SN - 1424-8220
UR - http://hdl.handle.net/10317/9444
AB - Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.
KW - Ingeniería Eléctrica
KW - Ingeniería Química
KW - Química-Física
KW - UAVs
KW - Drones
KW - Industry 4.0
KW - Concrete plant
KW - IoT protocols
KW - IoT gateway
KW - Image recognition
KW - Cloud computing
KW - Network latency
KW - End-to-end delay
KW - 23 Química
KW - 3306 Ingeniería y Tecnología Eléctricas
LA - eng
PB - MDPI
ER -