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This scheme is based on both a pattern analysis and a predictive model at that time when the threshold is exceeded. The analyzing process of noise information is performed on Arduino board and noise data is collected from multiple sensors with Bluetooth transmission technology. The Firebase cloud server allows users to access the collected data easily. In addition, a large amount of stored data is analyzed systematically using both R program and a predictive model according to a noise pattern. Performance analysis is carried out to evaluate the excellent performance of the proposed system by showing the accurate predictive results.<\/jats:p>","DOI":"10.3233\/jifs-169829","type":"journal-article","created":{"date-parts":[[2018,7,20]],"date-time":"2018-07-20T12:27:17Z","timestamp":1532089637000},"page":"5867-5879","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Intelligent noise prediction scheme with pattern analysis and deep learning technique"],"prefix":"10.1177","volume":"35","author":[{"given":"Sang-Hyeon","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, GangneungWonju National University, Jukheon-gil, Gangneung, Gangwon-do, South Korea"}]},{"given":"Moon-Sik","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, GangneungWonju National University, Jukheon-gil, Gangneung, Gangwon-do, South Korea"}]}],"member":"179","published-online":{"date-parts":[[2018,7,18]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"LeeS.-H. 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