2016 2nd International Conference on Science and Technology-Computer (ICST) 2016
DOI: 10.1109/icstc.2016.7877369
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Data classification for air quality on wireless sensor network monitoring system using decision tree algorithm

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Cited by 34 publications
(15 citation statements)
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“…Thanks to the application of algorithms devised by the authors, it is possible to identify flawed sequences contained in meteorological sensors. Similar studies regarding air quality classification using specific algorithms and a decision tree are presented in publication [5]. Inquiry in this area concerns not only land meteorological stations but also marine ones [10].…”
mentioning
confidence: 85%
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“…Thanks to the application of algorithms devised by the authors, it is possible to identify flawed sequences contained in meteorological sensors. Similar studies regarding air quality classification using specific algorithms and a decision tree are presented in publication [5]. Inquiry in this area concerns not only land meteorological stations but also marine ones [10].…”
mentioning
confidence: 85%
“…The study described in [5] describes issues related to the adoption of wireless sensor networks to assess air quality. The authors have rightly noticed that, having data from individual sensors on temperature, humidity, carbon monoxide (CO), and carbon dioxide (CO2), it is possible to estimate air quality and decide about the occurrence of an emergency in the warning system.…”
mentioning
confidence: 99%
“…The air quality monitoring is identified to be better in terms of data classification [9] with decision tree algorithm. The algorithm isolates a set of data into predefined classes thereby defining a tree structure for accurate monitoring of air quality level.…”
Section: Related Workmentioning
confidence: 99%
“…Penelitian lain yang mengaplikasikan wireless sensor network dan menerapkan konsep klasifikasi dataminig diantaranya, Laksono et al (Budi et al 2016) mengaplikasikan wireless sensor network untuk membuat prediksi cuaca dengan menggunakan paramter sensor angin, suhu dan kelembaban, dengan menggunakan metode C4.5. Pada penelitian Sugiarto dan Sustika (Sugiarto and Sustika 2016) yang dilakukan pengklasifikasian data kualitas udara dengan fitur yang digunakan yaitu suhu, kelembaban, karbondioksida, dan karbon monoksida, kemudian pengklasifikasian dilakukan menggunakan metode decision tree. Saoudi et al (Saoudi et al 2016), melakukan penelitian mengaplikasikan WSN untuk mendeteksi kebakaran hutan.…”
Section: Pendahuluanunclassified