Publications based on data that has been acquired using our products
Wingbeats Recorder
[1] Ioannis Kalfas, Bart De Ketelaere, Tim Beliën Wouter Saeys, Optical Identification of Fruitfly Species Based on Their Wingbeats Using Convolutional Neural Networks, Front. Plant Sci., 03 June 2022 Sec. Sustainable and Intelligent Phytoprotection, Volume 13 - 2022 | https://doi.org/10.3389/fpls.2022.812506
[2] Hassall Kirsty, Dye Alex, Potamitis Ilyas, Bell James. Resolving the identification of weak-flying insects during flight: a coupling between rigorous data processing and biology, Agricultural and Forest Entomology, Royal Entomological Society Journal, May 2021
[3] E. Fanioudakis, et al., "Mosquito wingbeat analysis and classification using deep learning," 2018 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 2018, pp. 2410-2414, doi: 10.23919/EUSIPCO.2018.8553542
[4] Ioannis Kalfas, Bart De Ketelaere, Wouter Saeys, Towards in-field insect monitoring based on wingbeat signals: The importance of practice oriented validation strategies, Computers and Electronics in Agriculture,Volume 180,2021,105849,ISSN 0168-1699,https://doi.org/10.1016/j.compag.2020.105849
[5] Elena Gorgeva, James Robertson, Sasha Voss & Jurian Hoogewerff (2023) The potential of bioacoustics for surveying carrion insects, Australian Journal of Forensic Sciences, DOI: 10.1080/00450618.2023.2295447
The e-funnel trap
[1] Iraklis I. et al., The e-funnel trap: Automatic monitoring of lepidoptera; a case study of tomato leaf miner, Computers and Electronics in Agriculture, Volume 185, 2021, 106154, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2021.106154
Treevibe
[1] Wadii Boulila, Ayyub Alzahem, Anis Koubaa, Bilel Benjdira, Adel Ammar, Early detection of red palm weevil infestations using deep learning classification of acoustic signals,Computers and Electronics in Agriculture, Volume 212,2023,108154,ISSN 0168-1699,https://doi.org/10.1016/j.compag.2023.108154
[2] Shi, H.; Chen, Z.; Zhang, H.; Li, J.; Liu, X.; Ren, L.; Luo, Y. Enhancement of Boring Vibrations Based on Cascaded Dual-Domain Features Extraction for Insect Pest Agrilus planipennis Monitoring. Forests 2023, 14, 902. https://doi.org/10.3390/f14050902
[3] Sutanto, K.D.; Husain, M.; Rasool, K.G.; Mankin, R.W.; Omer, A.O.; Aldawood, A.S. Acoustic Comparisons of Red Palm Weevil (Rhynchophorus ferrugineus) Mortality in Naturally Infested Date Palms after Injection with Entomopathogenic Fungi or Nematodes, Aluminum Phosphide Fumigation, or Insecticidal Spray Treatments. Insects 2023, 14, 339. https://doi.org/10.3390/insects14040339
[4] Sutanto, K.D.; Al-Shahwan, I.M.; Husain, M.; Rasool, K.G.; Mankin, R.W.; Aldawood, A.S. Field Evaluation of Promising Indigenous Entomopathogenic Fungal Isolates against Red Palm Weevil, Rhynchophorus ferrugineus (Coleoptera: Dryophthoridae). J. Fungi 2023, 9, 68. https://doi.org/10.3390/jof9010068
[5] R. Maruthadurai, T. Veerakumar, Channabasava Veershetty, A.N. Sathis Chakaravarthi, Acoustic detection of stem and root borer Neoplocaederus ferrugineus (Coleoptera: Cerambycidae) in cashew, Journal of Asia-Pacific Entomology, Volume 25, Issue 3,2022,101968,ISSN 1226-8615,https://doi.org/10.1016/j.aspen.2022.101968.
[6] Shi, H.; Chen, Z.; Zhang, H.; Li, J.; Liu, X.; Ren, L.; Luo, Y. A Waveform Mapping-Based Approach for Enhancement of Trunk Borers’ Vibration Signals Using Deep Learning Model. Insects 2022, 13, 596. https://doi.org/10.3390/insects13070596
[7] Liu, X.; Zhang, H.; Jiang, Q.; Ren, L.; Chen, Z.; Luo, Y.; Li, J. Acoustic Denoising Using Artificial Intelligence for Wood-Boring Pests Semanotus bifasciatus Larvae Early Monitoring. Sensors 2022, 22, 3861. https://doi.org/10.3390/s22103861
[8] Mohamed Esmail Karar, Abdel-Haleem Abdel-Aty, Fahad Algarni, Mohd Fadzil Hassan, M.A. Abdou, Omar Reyad, Smart IoT-based system for detecting RPW larvae in date palms using mixed depthwise convolutional networks, Alexandria Engineering Journal, Volume 61, Issue 7, 2022, Pages 5309-5319, ISSN 1110-0168, https://doi.org/10.1016/j.aej.2021.10.050
[9] Mankin, R.; Hagstrum, D.; Guo, M.; Eliopoulos, P.; Njoroge, A. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects 2021, 12, 259. https://doi.org/10.3390/insects12030259
[10] Mohamed Esmail Karar, Omar Reyad1, Abdel-Haleem Abdel-Aty, Saud Owyed and Mohd F. Hassan, Intelligent IoT-Aided Early Sound Detection of Red Palm Weevils, Computers, Materials & Continua, DOI:10.32604/cmc.2021.019059
[11] Rigakis I., et al., TreeVibes: Modern Tools for Global Monitoring of Trees for Borers. Smart Cities 2021, 4, 271-285. https://doi.org/10.3390/smartcities4010017
[12] Abdulrahman Saad Aldawood, Khawaja Ghulam Rasool, Koko Dwi Sutantu and Mureed Husain, DETECTION AND CONTROL OF RED PALM WEEVIL UNDER FIELD CONDITIONS, Arab Journal of Plant Protection, 13th Arab Congress of Plant Protection, Tunisia, 16-21 October 2022 https://cgspace.cgiar.org/bitstream/handle/10568/127320/d84e2b3c09a836d1fdd1110419251b94.pdf?sequence=2
[13] Mankin, R.W. 2023. Developments in crop insect pest detection techniques. Book Chapter. 117-146. https://doi.org/10.19103/AS.2022.0113.03
[1] Ioannis Kalfas, Bart De Ketelaere, Tim Beliën Wouter Saeys, Optical Identification of Fruitfly Species Based on Their Wingbeats Using Convolutional Neural Networks, Front. Plant Sci., 03 June 2022 Sec. Sustainable and Intelligent Phytoprotection, Volume 13 - 2022 | https://doi.org/10.3389/fpls.2022.812506
[2] Hassall Kirsty, Dye Alex, Potamitis Ilyas, Bell James. Resolving the identification of weak-flying insects during flight: a coupling between rigorous data processing and biology, Agricultural and Forest Entomology, Royal Entomological Society Journal, May 2021
[3] E. Fanioudakis, et al., "Mosquito wingbeat analysis and classification using deep learning," 2018 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 2018, pp. 2410-2414, doi: 10.23919/EUSIPCO.2018.8553542
[4] Ioannis Kalfas, Bart De Ketelaere, Wouter Saeys, Towards in-field insect monitoring based on wingbeat signals: The importance of practice oriented validation strategies, Computers and Electronics in Agriculture,Volume 180,2021,105849,ISSN 0168-1699,https://doi.org/10.1016/j.compag.2020.105849
[5] Elena Gorgeva, James Robertson, Sasha Voss & Jurian Hoogewerff (2023) The potential of bioacoustics for surveying carrion insects, Australian Journal of Forensic Sciences, DOI: 10.1080/00450618.2023.2295447
The e-funnel trap
[1] Iraklis I. et al., The e-funnel trap: Automatic monitoring of lepidoptera; a case study of tomato leaf miner, Computers and Electronics in Agriculture, Volume 185, 2021, 106154, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2021.106154
Treevibe
[1] Wadii Boulila, Ayyub Alzahem, Anis Koubaa, Bilel Benjdira, Adel Ammar, Early detection of red palm weevil infestations using deep learning classification of acoustic signals,Computers and Electronics in Agriculture, Volume 212,2023,108154,ISSN 0168-1699,https://doi.org/10.1016/j.compag.2023.108154
[2] Shi, H.; Chen, Z.; Zhang, H.; Li, J.; Liu, X.; Ren, L.; Luo, Y. Enhancement of Boring Vibrations Based on Cascaded Dual-Domain Features Extraction for Insect Pest Agrilus planipennis Monitoring. Forests 2023, 14, 902. https://doi.org/10.3390/f14050902
[3] Sutanto, K.D.; Husain, M.; Rasool, K.G.; Mankin, R.W.; Omer, A.O.; Aldawood, A.S. Acoustic Comparisons of Red Palm Weevil (Rhynchophorus ferrugineus) Mortality in Naturally Infested Date Palms after Injection with Entomopathogenic Fungi or Nematodes, Aluminum Phosphide Fumigation, or Insecticidal Spray Treatments. Insects 2023, 14, 339. https://doi.org/10.3390/insects14040339
[4] Sutanto, K.D.; Al-Shahwan, I.M.; Husain, M.; Rasool, K.G.; Mankin, R.W.; Aldawood, A.S. Field Evaluation of Promising Indigenous Entomopathogenic Fungal Isolates against Red Palm Weevil, Rhynchophorus ferrugineus (Coleoptera: Dryophthoridae). J. Fungi 2023, 9, 68. https://doi.org/10.3390/jof9010068
[5] R. Maruthadurai, T. Veerakumar, Channabasava Veershetty, A.N. Sathis Chakaravarthi, Acoustic detection of stem and root borer Neoplocaederus ferrugineus (Coleoptera: Cerambycidae) in cashew, Journal of Asia-Pacific Entomology, Volume 25, Issue 3,2022,101968,ISSN 1226-8615,https://doi.org/10.1016/j.aspen.2022.101968.
[6] Shi, H.; Chen, Z.; Zhang, H.; Li, J.; Liu, X.; Ren, L.; Luo, Y. A Waveform Mapping-Based Approach for Enhancement of Trunk Borers’ Vibration Signals Using Deep Learning Model. Insects 2022, 13, 596. https://doi.org/10.3390/insects13070596
[7] Liu, X.; Zhang, H.; Jiang, Q.; Ren, L.; Chen, Z.; Luo, Y.; Li, J. Acoustic Denoising Using Artificial Intelligence for Wood-Boring Pests Semanotus bifasciatus Larvae Early Monitoring. Sensors 2022, 22, 3861. https://doi.org/10.3390/s22103861
[8] Mohamed Esmail Karar, Abdel-Haleem Abdel-Aty, Fahad Algarni, Mohd Fadzil Hassan, M.A. Abdou, Omar Reyad, Smart IoT-based system for detecting RPW larvae in date palms using mixed depthwise convolutional networks, Alexandria Engineering Journal, Volume 61, Issue 7, 2022, Pages 5309-5319, ISSN 1110-0168, https://doi.org/10.1016/j.aej.2021.10.050
[9] Mankin, R.; Hagstrum, D.; Guo, M.; Eliopoulos, P.; Njoroge, A. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects 2021, 12, 259. https://doi.org/10.3390/insects12030259
[10] Mohamed Esmail Karar, Omar Reyad1, Abdel-Haleem Abdel-Aty, Saud Owyed and Mohd F. Hassan, Intelligent IoT-Aided Early Sound Detection of Red Palm Weevils, Computers, Materials & Continua, DOI:10.32604/cmc.2021.019059
[11] Rigakis I., et al., TreeVibes: Modern Tools for Global Monitoring of Trees for Borers. Smart Cities 2021, 4, 271-285. https://doi.org/10.3390/smartcities4010017
[12] Abdulrahman Saad Aldawood, Khawaja Ghulam Rasool, Koko Dwi Sutantu and Mureed Husain, DETECTION AND CONTROL OF RED PALM WEEVIL UNDER FIELD CONDITIONS, Arab Journal of Plant Protection, 13th Arab Congress of Plant Protection, Tunisia, 16-21 October 2022 https://cgspace.cgiar.org/bitstream/handle/10568/127320/d84e2b3c09a836d1fdd1110419251b94.pdf?sequence=2
[13] Mankin, R.W. 2023. Developments in crop insect pest detection techniques. Book Chapter. 117-146. https://doi.org/10.19103/AS.2022.0113.03