{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T22:26:36Z","timestamp":1768775196372,"version":"3.49.0"},"reference-count":42,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,20]],"date-time":"2022-06-20T00:00:00Z","timestamp":1655683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32171797"],"award-info":[{"award-number":["32171797"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["S202110022093"],"award-info":[{"award-number":["S202110022093"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"College Student Research and Career-creation Program of Beijing City","award":["32171797"],"award-info":[{"award-number":["32171797"]}]},{"name":"College Student Research and Career-creation Program of Beijing City","award":["S202110022093"],"award-info":[{"award-number":["S202110022093"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The advances in developing more accurate and fast smoke detection algorithms increase the need for computation in smoke detection, which demands the involvement of personal computers or workstations. Better detection results require a more complex network structure of the smoke detection algorithms and higher hardware configuration, which disqualify them as lightweight portable smoke detection for high detection efficiency. To solve this challenge, this paper designs a lightweight portable remote smoke front-end perception platform based on the Raspberry Pi under Linux operating system. The platform has four modules including a source video input module, a target detection module, a display module, and an alarm module. The training images from the public data sets will be used to train a cascade classifier characterized by Local Binary Pattern (LBP) using the Adaboost algorithm in OpenCV. Then the classifier will be used to detect the smoke target in the following video stream and the detected results will be dynamically displayed in the display module in real-time. If smoke is detected, warning messages will be sent to users by the alarm module in the platform for real-time monitoring and warning on the scene. Case studies showed that the developed system platform has strong robustness under the test datasets with high detection accuracy. As the designed platform is portable without the involvement of a personal computer and can efficiently detect smoke in real-time, it provides a potential affordable lightweight smoke detection option for forest fire monitoring in practice.<\/jats:p>","DOI":"10.3390\/s22124655","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T04:12:01Z","timestamp":1655871121000},"page":"4655","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An Embedded Portable Lightweight Platform for Real-Time Early Smoke Detection"],"prefix":"10.3390","volume":"22","author":[{"given":"Bowen","family":"Liu","sequence":"first","affiliation":[{"name":"School of Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingjian","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5412-5202","authenticated-orcid":false,"given":"Pengle","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Technology, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction, and Environmental Engineering, North Dakota State University, Fargo, ND 58102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,20]]},"reference":[{"key":"ref_1","unstructured":"She, L. (2008). Application of Statistical Detection Method in Early Warning of Fire. [Master\u2019s Thesis, Huaqiao University]. Available online: https:\/\/kns.cnki.net\/KCMS\/detail\/detail.aspx?dbname=CMFD2010&filename=2009015192.nh."},{"key":"ref_2","unstructured":"Zhang, J. (2019). Research on Fire Recognition Algorithm Based on Video Image. [Master\u2019s Thesis, Jilin University]. Available online: https:\/\/kns.cnki.net\/KCMS\/detail\/detail.aspx?dbname=CMFD201902&filename=1019162464.nh."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"106874","DOI":"10.1016\/j.compag.2022.106874","article-title":"A high-precision forest fire smoke detection approach based on ARGNet","volume":"196","author":"Zhan","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_4","first-page":"1","article-title":"Smoke Sensing Alarm System Based on GSM SMS","volume":"33","author":"Jiang","year":"2014","journal-title":"Meas. Control. Technol."},{"key":"ref_5","first-page":"110","article-title":"Design of smoke sensor based on MSP430F2012 microcontroller","volume":"37","author":"Zhao","year":"2011","journal-title":"Ind. Min. Autom."},{"key":"ref_6","first-page":"86","article-title":"Development of ionic smoke sensor","volume":"15\u201317","author":"Wang","year":"2004","journal-title":"Min. Saf. Environ. Prot."},{"key":"ref_7","first-page":"2","article-title":"Design of fire alarm based on Raspberry Pi","volume":"107","author":"Zhang","year":"2018","journal-title":"Comput. Prod. Circ."},{"key":"ref_8","unstructured":"Zhu, T., Yang, Z., Zhou, G., Zhang, C., and Han, J. (2021). A Lightweight Network Flame and Smoke Detection Algorithm. Appl. Sci. Technol., 83\u201386."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Liu, J., Wu, Y., Gao, X., and Zhang, X. (2022). A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties. Remote Sens., 14.","DOI":"10.3390\/rs14030668"},{"key":"ref_10","first-page":"1622","article-title":"Fire Smoke Detection Based on Mixed Gaussian Model and Wavelet Transform","volume":"29","author":"Aiguo","year":"2008","journal-title":"J. Instrum."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1016\/j.patrec.2008.01.013","article-title":"A fast accumulative motion orientation model based on integral image for video smoke detection","volume":"29","author":"Yuan","year":"2008","journal-title":"Pattern Recognit. Lett."},{"key":"ref_12","unstructured":"Gunnar, H. (2016). Fire Plumes, Flame Height, and Air Entrainment, Springer."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1016\/j.patcog.2006.07.007","article-title":"Real-time detection of steam in video images","volume":"40","author":"Ferrari","year":"2007","journal-title":"Pattern Recognit."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4326","DOI":"10.1016\/j.patcog.2012.06.008","article-title":"A double mapping framework for extraction of shape-invariant features based on multi-scale partitions with AdaBoost for video smoke detection","volume":"45","author":"Yuan","year":"2012","journal-title":"Pattern Recognit."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Cruz, H., Eckert, M., Meneses, J., and Mart\u00ednez, J.F. (2016). Efficient Forest Fire Detection Index for Application in Unmanned Aerial Systems (UASs). Sensors, 16.","DOI":"10.3390\/s16060893"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1007\/s10694-014-0453-y","article-title":"A saliency-based method for early smoke detection in video sequences","volume":"52","author":"Jia","year":"2016","journal-title":"Fire Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1007\/s10694-016-0580-8","article-title":"Multi Feature Analysis of Smoke in YUV Color Space for Early Forest Fire Detection","volume":"52","author":"Vinsley","year":"2016","journal-title":"Fire Technol."},{"key":"ref_18","first-page":"305","article-title":"Video smoke detection using shape, color and dynamic features","volume":"33","author":"Wang","year":"2017","journal-title":"J. Intell. Fuzzy Syst. Appl. Eng. Technol."},{"key":"ref_19","unstructured":"Song, S. (2021). Research on Forest Fire Detection Based on Improved GMM Algorithm. [Master\u2019s Thesis, Nanjing University of Posts and Telecommunications]. Available online: https:\/\/kns.cnki.net\/kcms\/detail\/detail.aspx?FileName=1021853567.nh&DbName=CMFD2022."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1007\/s10694-019-00831-x","article-title":"Forest fire smoke detection based on visual smoke root and diffusion model","volume":"55","author":"Gao","year":"2019","journal-title":"Fire Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1007\/s10694-020-01052-3","article-title":"Full-Scale Video-Based Detection of Smoke from Forest Fires Combining ViBe and MSER Algorithms","volume":"57","author":"Gao","year":"2021","journal-title":"Fire Technol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lou, L., Chen, F., and Cheng, P. (2022). Smoke root detection from video sequences based on multi-feature fusion. J. For. Res., 1\u201316.","DOI":"10.1007\/s11676-022-01461-w"},{"key":"ref_23","first-page":"170","article-title":"Video Fire Smoke Recognition Based on Block Segmentation and SVM","volume":"29","author":"Hu","year":"2012","journal-title":"Comput. Simul."},{"key":"ref_24","unstructured":"Guo, W. (2012). Research on Forest Fire Smoke Image Detection Technology Based on Motion Features. [Master\u2019s Thesis, Beijing Forestry University]. Available online: https:\/\/kns.cnki.net\/KCMS\/detail\/detail.aspx?dbname=CMFD2012&filename=1012350392.nh."},{"key":"ref_25","first-page":"1","article-title":"Research of fire smoke detection algorithm based on video","volume":"13","author":"Zhao","year":"2021","journal-title":"Int. J. Electron. Inf. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"033006","DOI":"10.1117\/1.JEI.28.3.033006","article-title":"Smoke detection and trend prediction method based on deeplabv3+ and generative adversarial network","volume":"28","author":"Cheng","year":"2019","journal-title":"J. Electron. Imaging"},{"key":"ref_27","unstructured":"Wang, L. (2011). Research and Implementation of Intelligent Video Surveillance Firework Detection. [Master\u2019s Thesis, University of Electronic Science and Technology of China]. Available online: https:\/\/kns.cnki.net\/kcms\/detail\/detail.aspx?FileName=1011073335.nh&DbName=CMFD2011."},{"key":"ref_28","first-page":"3719","article-title":"Design of servo control system based on Arduino","volume":"3","author":"Cai","year":"2012","journal-title":"Comput. Knowl. Technol."},{"key":"ref_29","first-page":"118","article-title":"Design of an intelligent car obstacle avoidance system based on Arduino","volume":"37","author":"Ge","year":"2014","journal-title":"Mod. Electron. Technol."},{"key":"ref_30","first-page":"123","article-title":"An Arduino-based smart home control system","volume":"40","author":"Cui","year":"2014","journal-title":"Electron. Technol. Appl."},{"key":"ref_31","first-page":"83","article-title":"Design of License Plate Recognition System Based on ARM Cortex-A8","volume":"21","author":"Ding","year":"2021","journal-title":"Appl. Single Chip Microcomput. Embed. Syst."},{"key":"ref_32","unstructured":"Dai, Z. (2016). Face Recognition System Based on Gabor Response Coding. [Master\u2019s Thesis, Shenzhen University]. Available online: https:\/\/kns.cnki.net\/KCMS\/detail\/detail.aspx?dbname=CMFD201701&filename=1016763661.nh."},{"key":"ref_33","first-page":"105","article-title":"Video detection and tracking system based on Raspberry Pi B+ microprocessor","volume":"39","author":"Gao","year":"2015","journal-title":"Telev. Technol."},{"key":"ref_34","first-page":"11","article-title":"Research on defect detection of dyed fabrics based on deep learning based on Raspberry Pi","volume":"47","author":"Cao","year":"2019","journal-title":"Cotton Text. Technol."},{"key":"ref_35","first-page":"305","article-title":"Design and implementation of Raspberry Pi 3B+ blind guidance system","volume":"40","author":"Chen","year":"2020","journal-title":"J. Xi\u2019an Univ. Technol."},{"key":"ref_36","first-page":"81","article-title":"Design of real-time communication system for portable smart glasses based on Raspberry Pi","volume":"39","author":"Liu","year":"2019","journal-title":"J. Northeast. Electr. Power Univ."},{"key":"ref_37","first-page":"20","article-title":"Remote intelligent monitoring and alarm system for the elderly living alone based on Raspberry Pi","volume":"39","author":"Wei","year":"2017","journal-title":"Electron. World"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2256","DOI":"10.1109\/TGRS.2020.3004353","article-title":"Super-Resolution Mapping Based on Spatial-Spectral Correlation for Spectral Imagery","volume":"59","author":"Wang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","article-title":"Multiresolution gray-scale and rotation invariant texture classification with local binary patterns","volume":"24","author":"Ojala","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","unstructured":"(2022, June 17). [Sample Fire and Smoke Video Clips]. Available online: http:\/\/signal.ee.bilkent.edu.tr\/VisiFire\/Demo\/SampleClips.html."},{"key":"ref_41","unstructured":"(2022, June 17). [Video Smoke Detection]. Available online: http:\/\/staff.ustc.edu.cn\/~yfn\/vsd.html."},{"key":"ref_42","unstructured":"(2022, June 17). [CVPR Lab. at Keimyung University]. Available online: https:\/\/cvpr.kmu.ac.kr\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4655\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:36:10Z","timestamp":1760139370000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4655"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,20]]},"references-count":42,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22124655"],"URL":"https:\/\/doi.org\/10.3390\/s22124655","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,20]]}}}