Implementasi Image Processing pada Robot Pertanian
I will put the dimension here
Abstract
Penelitian ini menggunakan penelitian riset. Permasalahan pada penelitian ini ialah bagaimana robot pemantau mendeteksi objek yang berada didepannya. Penelitian ini bertujuan untuk mempelajari sistem deteksi robot pemantau dengan menggunakan metode Image Segmentation. Subjek yang digunakan dalam penelitian ini ialah tanaman dilahan pertanian green house. Sedangkan teknik pengumpulan data yang digunakan adalah observasi dan wawancara secara langsung di lapangan. Hasil dari penelitian ini adalah sebuah gambar yang dihasilkan oleh kamera, lalu ditampilkan pada layar monitor ataupun HP agar para pemantau dan petani dapat melihat hasil yang diperoleh. Lalu, kamera ini bisa digunakan untuk memprediksi atau memberikan kejelasan kepada para pemantau agar dapat dianalisa dan dilihat apakah tanaman tersebut telah sesuai dengan waktu yang ditentukan, contohnya melihat apakah tanaman tersebut siap untuk dipanen maupun melihat tanaman tersebut tumbuh dengan baik atau tidak. Selain itu, penelitian ini bertujuan untuk meringankan pekerjaan para petani pada saat melakukan pemantauan disiang hari jika pada hari tersebut tidak dapat dipantau secara manual.
References
M. Liao, S. Chen, C. Chou, H. Chen, S. Yeh, Y. Chang, and J. Jiang, On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system, Computers and Electronics in Agriculture, Vol. 136, pp. 125-139, 2017. https://doi.org/10.1016/j.compag.2017.03.003.
Kumar, V. Singh, S. Kumar, S. P. Jaiswal, and V. S. Bhadoria, IoT enabled system to monitor and control greenhouse, Materials Today: Proceedings, Vol. 49, No 8, pp. 3137-3141, 2022. https://doi.org/10.1016/j.matpr.2020.11.040
G. Singh, P. P. Singh, P. P. Singh Lubana, and K.G. Singh, Formulation and validation of a mathematical model of the microclimate of a greenhouse, Renewable Energy, Vol. 31, No 10, pp. 1541-1560, 2006. https://doi.org/10.1016/j.renene.2005.07.011.
H. Kim, D. H. Lee, S. W. Ahn, W. K. Kim, S. O. Hur, J. Y. Choi, S. Chung, Design and testing of an autonomous irrigation controller for precision water management of greenhouse crops, Engineering in Agriculture, Environment and Food, Vol. 8, No 4, pp. 228-234, 2015. https://doi.org/10.1016/j.eaef.2015.03.001
D. S. Paraforos, H. W. Griepentrog, Multivariable greenhouse climate control using dynamic decoupling controllers, IFAC Proceedings Volumes, Vol. 46, No 18, pp. 305-310, 2013, https://doi.org/10.3182/20130828-2-SF-3019.00064.
Chang, S. Chung, W. Fu, and C. Huang,Artificial intelligence approaches to predict growth, harvest day, and quality of lettuce (Lactuca sativa L.) in a IoT-enabled greenhouse system, Biosystems Engineering, Vol. 212, pp. 77-105, 2021. https://doi.org/10.1016/j.biosystemseng.2021.09.015.
F. Hahn, Fuzzy controller decreases tomato cracking in greenhouses, Computers and Electronics in Agriculture, Vol. 77, No 1, pp. 21-27, 2011. https://doi.org/10.1016/j.compag.2011.03.003.
H. Benyezza, M. Bouhedda, and S. Rebouh, Zoning irrigation smart system based on fuzzy control technology and IoT for water and energy saving, Journal of Cleaner Production, Vol. 302, p. 127001, 2021. https://doi.org/10.1016/j.jclepro.2021.127001.
N. Uchiyama, T. Dewi, and S. Sano, Collision Avoidance Control for a Human-Operated Four Wheeled Mobile Robot, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 228(13), pp. 2278-2284, 2014. https://doi.org/10.1177/0954406213518523.
T. Dewi, N. Uchiyama, S. Sano, and H. Takahashi, Swarm Robot Control for Human Services and Moving Rehabilitation by Sensor Fusion, Journal of Robotics, 2014(278659), 11 pages, 2014. https://doi.org/10.1155/2014/278659
Dewi T., Amperawan, Risma P., Oktarina Y., and Yudha D. A., 2020, Finger Cue for Mobile Robot Motion Control, Computer Engineering and Application Journal, 9(1), pp. 39-48. doi: 10.18495/COMENGAPP.V9I1.319.
Dewi T., Risma P., Taqwa A., Rusdianasari, and Renaldi H., 2020, Experimental analysis on solar powered mobile robot as the prototype for environmentally friendly automated transportation, Proc. iCAST on Engineering Science, 24-25 Oct 2019, Bali: Indonesia, doi:10.1088/1742-6596/1450/1/012034.
T. Dewi, P. Risma, and Y. Oktarina, The Concept of Automatic Transport System Utilizing Weight Sensor, Vol. 9, No. 2, pp. 155-163, 2020. doi:10.18495/COMENGAPP.V0I0.339.
Dewi T., Nurmaini S., Risma P., Oktarina Y., and Roriz M., 2019, Inverse Kinematic Analysis of 4 DOF Pick and Place Arm Robot Manipulator using Fuzzy Logic Controller, IJECE, 10(2), pp. 1376-1386. doi:10.11591/ijece.v10i2.pp1376-1386.
T. Dewi, P. Risma, Y. Oktarina, and S. Muslimin, "Visual Servoing Design and Control for Agriculture Robot; a Review", Proc. 2019 ICECOS, 2-4 Oct. 2018, Pangkal Pinang: Indonesia, 2018, pp. 57-62, DOI: 10.1109/ICECOS.2018.8605209.
T. Dewi, P. Risma, and Y. Oktarina, "Fruit Sorting Robot based on Color and Size for an Agricultural Product Packaging System," Bulletin of Electrical Engineering, and Informatics (BEEI), vol. 9, no. 4, pp. 1438-1445, 2020, DOI: 10.11591/eei.v9i4.2353.
F. Septiarini, T. Dewi and Rusdianasari, Design of a solar-powered mobile manipulator using fuzzy logic controller of agriculture application, International Journal of Computational Vision and Robotics, Inderscience, Vol. 12, No. 5, pp. 506-531, 2022. https://doi.org/10.1504/IJCVR.2022.125356.
Y. Oktarina, T. Dewi, P. Risma, and M. Nawawi, Tomato Harvesting Arm Robot Manipulator; a Pilot Project, Journal of Physics: Conference Series, 1500, p 012003, Proc. 3rd FIRST, Palembang: Indonesia, 2020, DOI: 10.1088/1742-6596/1500/1/ 012003.
T. Dewi, C. Anggraini, P. Risma, Y. Oktarina, and Muslikhin, Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System, SINERGI Vol. 25, No. 2, pp. 217-226, 2021. http://doi.org/10.22441/sinergi.2021.2.013.
T. Dewi, P. Risma, and Y. Oktarina, Fruit Sorting Robot based on Color and Size for an Agricultural Product Packaging System, Bulletin of Electrical Engineering, and Informatics (BEEI), vol. 9, no. 4, pp. 1438-1445, 2020, DOI: 10.11591/eei.v9i4.2353.
T. Dewi, Z. Mulya, P. Risma, and Y. Oktarina, BLOB Analysis of an Automatic Vision Guided System for a Fruit Picking and Placing Robot, International Journal of Computational Vision and Robotics, Vol. 11, No 3, pp. 315- 326, 2021. https://doi.org/10.1504/IJCVR.2021.115161.
Dewi, T., Rusdianasari, R., Kusumanto, R., & Siproni, S. (2022). Pengolahan citra Application on Automatic Fruit Detection for Agriculture Industry. Proceedings of the 5th FIRST T1 T2 2021 International Conference (FIRST-T1-T2 2021), 9, 47–53. https://doi.org/10.2991/ahe.k.220205.009.
Farooq U., Amar M., Asad M.U., Hanif A., and Saleh S.O., 2014. Design and Implementation of Neural Network of Based Controller for Mobile Robot Navigation in Unknown Environment. International Journal of Computer and Electrical Engineering, 6(2), pp. 83-89. doi:10.7763/IJCEE.2014.V6.799
Dewi T., Wijanarko Y., Risma P., and Oktarina Y., 2018, Fuzzy Logic Controller Design for Leader-Follower Robot Navigation, 5th Proc. EECSI, 5(1), pp. 298-303. 16-18 Oct 2018, Malang : Indonesia. doi:10.1109/EECSI.2018.8752696.
Dewi T., Risma P., and Oktarina Y., 2018, Fuzzy Logic Simulation as a Teaching-learning Media for Artificial Intelligence Class, Journal of Automation Mobile Robotics and Intelligent Systems, 12(3), pp. 3-9.doi: 10.14313/JAMRIS_3-2018/13
Dewi T., Oktarina Y., Risma P., and Kartini S., 2019, Desain Robot Pengikut Manusia Sederhana dengan Fuzzy Logic Controller, Proc. Annual Research Seminar (ARS), 5(1), pp. 12-16, 16 Nov 2019, Palembang: Indonesia.
Oktarina Y., Septiarini F., Dewi T., Risma P., and Nawawi M., 2019, Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator, Computer Engineering and Application Journal, 8(2), pp. 123-136. doi: 10.18495/COMENGAPP.V8I2.300.
T. Dewi, C. Sitompul, P. Risma, and Y. Oktarina, R. Jelista, M. Mulyati M., Simulation Analysis of Formation Control Design of Leader-Follower Robot Using Fuzzy Logic Controller, Proc 2019 ICECOS, 2-3 Oct. 2019, Batam Island: Indonesia. doi:10.1109/ICECOS47637.2019.8984433
Yudha H. M., Dewi T., Hasana N., Risma P., Oktarina, Y. Kartini S., 2019, Performance Comparison of Fuzzy Logic and Neural Network Design for Mobile Robot Navigation, Proc. 2019 ICECOS, 2-3 Oct. 2019, Batam Island: Indonesia. doi:10.1109/ICECOS47637.2019.8984577
Larasati N., Dewi T., and Oktarina Y., 2017. Object Following Design for a Mobile Robot using Neural Network. Computer Engineering and Application Journal, 6(1), pp. 5-14. doi:10.18495/COMENGAPP.V6I1.189.
Dewi T., Risma P., Oktarina Y., and Roseno M.T., 2017. Neural Network Design for a Mobile Robot Navigation a Case Study. 4th Proc. EECSI. 23-24 Sep. 2017. Yogyakarta: Indonesia. doi:10.1109/EECSI.2017.8239168.
Dewi T., Risma P., Oktarina Y., and Nawawi M., 2017. Neural Network Simulation for Obstacle Avoidance and Wall Follower Robot as a Helping Tool for Teaching-Learning Process in Classroom. 1st Proc. ICEAT, 29-30 November 2017, Mataram: Indonesia. doi:10.1088/1757-899X/403/1/012043
Risma P., Dewi T., Oktarina Y., and Wijanarko Y., 2019. Neural Network Controller Application on a Visual based Object Tracking and Following Robot. Computer Engineering and Application Journal, 8(1). doi: 10.18495/COMENGAPP.V8I1.280.
Vasilev, Ivan. 2019. Python Deep Learning: Exploring Deep Learning Techniques and Neural Network Architectures with PyTorch, Keras, and TensorFlow.
Fang, W., Wang, L., & Ren, P. (2020). Tinier-YOLO: A Real-Time Object Detection Method for Constrained Environments. IEEE Access, 8, 1935–1944. https://doi.org/10.1109/ACCESS.2019.2961959.
Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, “Rethinking the Inception Architecture for Computer Vision,” Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 2016-Decem, pp. 2818–2826, 2016, doi: 10.1109/CVPR.2016.308.
E. Wijaya, W. Swastika, and O. H. Kelana, “Implementasi Transfer Learning Pada Convolutional Neural Network Untuk Diagnosis Covid-19 Dan Pneumonia Pada Citra X-Ray,” Sainsbertek J. Ilm. Sains Teknol., vol. 2, no. 1, pp. 10–15, 2021, doi: 10.33479/sb.v2i1.125.
Iskandar Mulyana and M. A. Rofik, “Implementasi Deteksi Real Time Klasifikasi Jenis Kendaraan Di Indonesia Menggunakan Metode YOLOV5,” J. Pendidik. Tambusai, vol. 6, no. 3, pp. 13971–13982, 2022, doi: 10.31004/jptam.v6i3.4825.
Perri, M. Simonetti, and O. Gervasi, “Synthetic data generation to speed-up the object recognition pipeline,” Electron., vol. 11, no. 1, pp. 1–19, 2022, doi: 10.3390/electronics11010002.
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