Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2744
Title: | TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network |
Authors: | Kalhara, P. G Jayasinghearachchi, V. D Dias, A. H. A. T Ratnayake, V. C Jayawardena, C Kuruwitaarachchi, N |
Keywords: | TreeSpirit Illegal logging logging detection lerting system audio identification IoT network |
Issue Date: | 19-Feb-2018 |
Publisher: | IEEE |
Citation: | P. 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. |
Series/Report no.: | 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA); |
Abstract: | Illegal 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. |
URI: | http://rda.sliit.lk/handle/123456789/2744 |
ISSN: | 2573-3214 |
Appears in Collections: | Department of Computer Systems Engineering-Scopes Research Papers - Dept of Computer Systems Engineering Research Papers - IEEE Research Papers - SLIIT Staff Publications |
Files in This Item:
File | Description | Size | Format | |
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TreeSpirit_Illegal_logging_detection_and_alerting_system_using_audio_identification_over_an_IoT_network.pdf Until 2050-12-31 | 1.38 MB | Adobe PDF | View/Open Request a copy |
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