| Autor: |
de Azevedo LJM; Institute of Mathematics and Computer Science, University of São Paulo, Sao Paulo 13560-970, SP, Brazil., Estrella JC; Institute of Mathematics and Computer Science, University of São Paulo, Sao Paulo 13560-970, SP, Brazil., Delbem ACB; Institute of Mathematics and Computer Science, University of São Paulo, Sao Paulo 13560-970, SP, Brazil., Meneguette RI; Institute of Mathematics and Computer Science, University of São Paulo, Sao Paulo 13560-970, SP, Brazil., Reiff-Marganiec S; School of Electronics, Computing and Maths, University of Derby, Kedleston Rd., Derby DE22 1GB, UK., de Andrade SC; Computing Department, Federal University of Technology-Paraná, R. Cristo Rei, 19, Toledo 85902-490, PR, Brazil. |
| Abstrakt: |
The Internet of Things consists of "things" made up of small sensors and actuators capable of interacting with the environment. The combination of devices with sensor networks and Internet access enables the communication between the physical world and cyberspace, enabling the development of solutions to many real-world problems. However, most existing applications are dedicated to solving a specific problem using only private sensor networks, which limits the actual capacity of the Internet of Things. In addition, these applications are concerned with the quality of service offered by the sensor network or the correct analysis method that can lead to inaccurate or irrelevant conclusions, which can cause significant harm for decision makers. In this context, we propose two systematic methods to analyze spatially distributed data Internet of Things. We show with the results that geostatistics and spatial statistics are more appropriate than classical statistics to do this analysis. |
