Kalhara, P. GJayasinghearachchi, V. DDias, A. H. A. TRatnayake, V. CJayawardena, CKuruwitaarachchi, N2022-07-062022-07-062018-02-19P. 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.2017.8294127.2573-3214https://rda.sliit.lk/handle/123456789/2744Illegal 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.enTreeSpiritIllegal logginglogging detectionlerting systemaudio identificationIoT networkArticle10.1109/SKIMA.2017.8294127