IoT Off-Grid, Data Collection from a Machine Learning Classification Using UAV.

Autor: Goulart A; Computer Science Graduate Program, Federal University of Santa Catarina, Florianópolis 88040-370, Brazil., Pinto ASR; Computer Science Graduate Program, Federal University of Santa Catarina, Florianópolis 88040-370, Brazil., Boava A; Computer Science Graduate Program, Federal University of Santa Catarina, Florianópolis 88040-370, Brazil., Branco KRLJC; Institute of Mathematics and Computer Science, Universidade de São Paulo, São Carlos 13566-590, Brazil.
Jazyk: angličtina
Zdroj: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Sep 24; Vol. 22 (19). Date of Electronic Publication: 2022 Sep 24.
DOI: 10.3390/s22197241
Abstrakt: IoT encompasses various objects, technologies, communication standards, sensors, actuators in powered environments, and networked communication. The concept adopted here, IoT off-grid, considers an environment without commercial electricity and commercial internet. Managing various utilities with IoT and collecting the relevant information from this environment is the purpose of this project. It uses machine learning to select relevant data. These data are collected safely using a drone that travels through the off-grid stations. A systematic literature mapping is presented, identifying the state of the art. The result is a software architecture proposal with configurations in the drone and off-grid stations that contemplate data collection from the IoT off-grid environment. The results are also presented with different selection algorithms used in machine learning and final execution in the prototype.
Databáze: MEDLINE
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