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| Title | Missing Data Estimation And Imputation Algorithm For Wireless Sensor Network Applications |
|---|---|
| ID_Doc | 37126 |
| Authors | Srinivas L.N.B.; Jayavel K. |
| Year | 2022 |
| Published | 2022 International Conference on Computer Communication and Informatics, ICCCI 2022 |
| DOI | http://dx.doi.org/10.1109/ICCCI54379.2022.9740892 |
| Abstract | Wireless Sensor Networks (WSNs) contain a large number of spatially located sensors for monitoring the physical conditions of the environment or machinery. The data collected from the sensors are retrieved and stored in a central computer for analysis. The WSNs are used for measurement of parameters such as temperature, humidity, sound pressure, wind velocity, pollution levels and air quality usually from remote and sometime not easily reachable locations. The evolution of WSN has lead to developments in the field of Internet of Things (IoT) and now smart cities. In the aforementioned scenarios, data quality is highly crucial for better decision making. As WSNs are constrained by cost and resource factors, one has to carefully study the data collected either online or offline, to take the right decisions. Missing data is one of the prominent data quality problems. After thorough analysis of work carried out by many researchers in this field, a regression based approach for Multivariate data is proposed in this paper. An experimental analysis is carried out on a dataset generated from a simulated WSN environment. © 2022 IEEE. |
| Author Keywords | Imputation; Missing data; Regression; Wireless Sensor Networks |
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