Publication:
TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network

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dc.contributor.authorKalhara, P. G
dc.contributor.authorJayasinghearachchi, V. D
dc.contributor.authorDias, A. H. A. T
dc.contributor.authorRatnayake, V. C
dc.contributor.authorJayawardena, C
dc.contributor.authorKuruwitaarachchi, N
dc.date.accessioned2022-07-06T04:36:10Z
dc.date.available2022-07-06T04:36:10Z
dc.date.issued2018-02-19
dc.description.abstractIllegal logging has been identified as a major problem in the world, which may be minimized through effective monitoring of forest covered areas. In this paper, we propose and describe the initial steps to build a new three-tier architecture for Forest Monitoring based on Wireless Sensor Network and Chainsaw Noise Identification using a Neural Network. In addition to detection of chainsaw noises, we also propose methodologies to localize the origin of the chainsaw noise.en_US
dc.identifier.citationP. G. Kalhara, V. D. Jayasinghearachchi, A. H. A. T. Dias, V. C. Ratnayake, C. Jayawardena and N. Kuruwitaarachchi, "TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network," 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2017, pp. 1-7, doi: 10.1109/SKIMA.2017.8294127.en_US
dc.identifier.doi10.1109/SKIMA.2017.8294127en_US
dc.identifier.issn2573-3214
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/2744
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA);
dc.subjectTreeSpiriten_US
dc.subjectIllegal loggingen_US
dc.subjectlogging detectionen_US
dc.subjectlerting systemen_US
dc.subjectaudio identificationen_US
dc.subjectIoT networken_US
dc.titleTreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT networken_US
dc.typeArticleen_US
dspace.entity.typePublication

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