Dataset of short-term prediction of CO2 concentration based on a wireless sensor network

Ari Wibisono, Hanif Arief Wisesa, Novian Habibie, Aulia Arshad, Aditya Murdha, Wisnu Jatmiko, Ahmad Gamal, Indra Hermawan, Siti Aminah

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


This CO2 data is gathered from WSN (Wireless Sensor Network) sensors that is placed in some areas. To make this observation framework run effectively, examining the relationships between factors is required. We can utilize multiple wireless sensor devices. There are three parts of the system, including the sensor device, the sink node device, and the server. We use those devices to acquire data over a three-month period. In terms of the server infrastructure, we utilized an application server, a user interface server, and a database server to store our data. This study built a WSN framework for CO2 observations. We investigate, analyze, and predict the level of CO2, and the results have been collected. The Random Forest algorithm achieved a 0.82 R2 Score.

Original languageEnglish
Article number105924
JournalData in Brief
Publication statusPublished - Aug 2020
Externally publishedYes


  • CO monitoring system
  • CO prediction
  • IoT system
  • Prediction system
  • Wireless sensor network


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