Chainsaw Sound Detection Using DNN Algorithm
Keywords:
sound processing, sound recognition, chainsaw sound detection
Abstract
Deforestation and illegal logging stand as important environmental problems. In this paper we propose a DNN architecture for sound recognition of chainsaw detection. Various parameters need to be tuned in order to identify the sound of chainsaw but not to produce too much amounts of false positive detection. The task is challenging as different sound emerge in the forest.
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References
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[6]. Kalhara P. G., Jayasinghearachchd V. D., Dias A. H. A. T., Ratnayake V. C., Jayawardena C., Kuruwitaarachchi N., TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network, In Proceedings of the 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe, Sri Lanka, 6–8 December 2017.
[7]. Prasetyo D. C., Mutiara G. A., Handayani R., Chainsaw sound and vibration detector system for illegal logging, In Proceedings of the 2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), Bali, Indonesia, 5–7 December 2018.
[8]. Jubjainai P., Pathomwong S., Siripujaka P., Chiengmai N., Chaiboot A., Wardkein P., Chainsaw location finding based on travelling of sound wave in air and ground, IOP Conf. Ser. Earth Environ. Sci. 2020.
[9]. Andrei V., Cucu H., Petrică L., Considerations on developing a chainsaw intrusion detection and localization system for preventing unauthorized logging, Journal of Electrical and Electronic Engineering, 3(6), p. 202-207, 2015.
[10]. Czuni L., Varga P. Z., Time Domain Audio Features for Chainsaw Noise Detection Using WSNs, IEEE Sens. J. 17, 1, 2017.
[11]. Meedeniya D., Ariyarathne I., Bandara M., Jayasundara R., Perera C., A Survey on Deep Learning Based Forest Environment Sound Classification at the Edge, ACM Computing Surveys, 56(3), p. 1-36, 2023.
[12]. Somwong B., Kumphet K., Massagram W., Acoustic Monitoring System with AI Threat Detection System for Forest Protection, 20th International Joint Conference on Computer Science and Software Engineering (JCSSE), p. 253-257, IEEE, 2023.
[13]. Stefanakis N., Psaroulakis K., Simou N., Astaras C., An Open-Access System for Long-Range Chainsaw Sound Detection, 30th European Signal Processing Conference (EUSIPCO), p. 264-268, IEEE, 2022.
[14]. Prasetyo D. C., Mutiara G. A., Handayani R., Chainsaw sound and vibration detector system for illegal logging, International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), p. 93-98, IEEE, 2018.
[2]. Tang Y., Han P., Wang Z., Hu L., Gao Y., Li H., Based on intelligent voice recognition of forest illegal felling of detecting methods, 2nd International Conference on Cloud Computing and Intelligent Systems, p. 1153-1156, 2012.
[3]. Soisoonthorn T., Rujipattanapong S., Deforestation detection algorithm for wireless sensor networks, 10.1109/ISCIT.2007.4392237, 2007.
[4]. Colonna J. G., Gatto B., Santos E. D., Nakamura E. F., A framework for chainsaw detection using one-class kernel and wireless acoustic sensor networks into the amazon rainforest, Mobile Data Management (MDM), 17th IEEE International Conference, vol. 2, p. 34-36, 2016.
[5]. Harvanova V., Vojtko M., Babis M., Duricek M., Pohronska M., Detection of wood logging based on sound recognition using zigbee sensor network, In Proceedings of the International Conference on Design and Architectures for Signal and Image Processing, Tampere, Finland, 2-4 November 2011.
[6]. Kalhara P. G., Jayasinghearachchd V. D., Dias A. H. A. T., Ratnayake V. C., Jayawardena C., Kuruwitaarachchi N., TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network, In Proceedings of the 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe, Sri Lanka, 6–8 December 2017.
[7]. Prasetyo D. C., Mutiara G. A., Handayani R., Chainsaw sound and vibration detector system for illegal logging, In Proceedings of the 2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), Bali, Indonesia, 5–7 December 2018.
[8]. Jubjainai P., Pathomwong S., Siripujaka P., Chiengmai N., Chaiboot A., Wardkein P., Chainsaw location finding based on travelling of sound wave in air and ground, IOP Conf. Ser. Earth Environ. Sci. 2020.
[9]. Andrei V., Cucu H., Petrică L., Considerations on developing a chainsaw intrusion detection and localization system for preventing unauthorized logging, Journal of Electrical and Electronic Engineering, 3(6), p. 202-207, 2015.
[10]. Czuni L., Varga P. Z., Time Domain Audio Features for Chainsaw Noise Detection Using WSNs, IEEE Sens. J. 17, 1, 2017.
[11]. Meedeniya D., Ariyarathne I., Bandara M., Jayasundara R., Perera C., A Survey on Deep Learning Based Forest Environment Sound Classification at the Edge, ACM Computing Surveys, 56(3), p. 1-36, 2023.
[12]. Somwong B., Kumphet K., Massagram W., Acoustic Monitoring System with AI Threat Detection System for Forest Protection, 20th International Joint Conference on Computer Science and Software Engineering (JCSSE), p. 253-257, IEEE, 2023.
[13]. Stefanakis N., Psaroulakis K., Simou N., Astaras C., An Open-Access System for Long-Range Chainsaw Sound Detection, 30th European Signal Processing Conference (EUSIPCO), p. 264-268, IEEE, 2022.
[14]. Prasetyo D. C., Mutiara G. A., Handayani R., Chainsaw sound and vibration detector system for illegal logging, International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), p. 93-98, IEEE, 2018.
Published
2023-12-15
How to Cite
1.
MARIN FB, MARIN M. Chainsaw Sound Detection Using DNN Algorithm. The Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science [Internet]. 15Dec.2023 [cited 26Dec.2024];46(4):85-8. Available from: https://gup.ugal.ro/ugaljournals/index.php/mms/article/view/6507
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