TY - JOUR
T1 - Processing at the Edge
T2 - A Case Study with an Ultrasound Sensor-Based Embedded Smart Device
AU - Poza-Lujan, Jose Luis
AU - Uribe-Chavert, Pedro
AU - Sáenz-Peñafiel, Juan José
AU - Posadas-Yagüe, Juan Luis
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - In the current context of the Internet of Things, embedded devices can have some intelligence and distribute both data and processed information. This article presents the paradigm shift from a hierarchical pyramid to an inverted pyramid that is the basis for edge, fog, and cloud-based architectures. To support the new paradigm, the article presents a distributed modular architecture. The devices are made up of essential elements, called control nodes, which can communicate to enhance their functionality without sending raw data to the cloud. To validate the architecture, identical control nodes equipped with a distance sensor have been implemented. Each module can read the distance to each vehicle and process these data to provide the vehicle’s speed and length. In addition, the article describes how connecting two or more CNs, forming an intelligent device, can increase the accuracy of the parameters measured. Results show that it is possible to reduce the processing load up to 22% in the case of sharing processed information instead of raw data. In addition, when the control nodes collaborate at the edge level, the relative error obtained when measuring the speed and length of a vehicle is reduced by one percentage point.
AB - In the current context of the Internet of Things, embedded devices can have some intelligence and distribute both data and processed information. This article presents the paradigm shift from a hierarchical pyramid to an inverted pyramid that is the basis for edge, fog, and cloud-based architectures. To support the new paradigm, the article presents a distributed modular architecture. The devices are made up of essential elements, called control nodes, which can communicate to enhance their functionality without sending raw data to the cloud. To validate the architecture, identical control nodes equipped with a distance sensor have been implemented. Each module can read the distance to each vehicle and process these data to provide the vehicle’s speed and length. In addition, the article describes how connecting two or more CNs, forming an intelligent device, can increase the accuracy of the parameters measured. Results show that it is possible to reduce the processing load up to 22% in the case of sharing processed information instead of raw data. In addition, when the control nodes collaborate at the edge level, the relative error obtained when measuring the speed and length of a vehicle is reduced by one percentage point.
KW - Ambient intelligence
KW - Edge and fog computing
KW - Embedded device
KW - Smart cities
UR - https://www.scopus.com/pages/publications/85124308037
U2 - 10.3390/electronics11040550
DO - 10.3390/electronics11040550
M3 - Artículo
AN - SCOPUS:85124308037
SN - 2079-9292
VL - 11
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
IS - 4
M1 - 550
ER -