Main Article Content

Abstract

People's living standards are increasing with the development of the global economy, so that the production of domestic waste is increasing from year to year. However, in waste processing there is still a problem of mixing waste in landfills where hazardous waste is still mixed so that it can cause the spread of covid. Currently the trend is starting to shift to smart devices that use the Internet of Things to solve common problems such as waste management problems. In this study, a Mobile Smart Trashbin is proposed which can reduce direct interaction because it has an automatic opening and closing feature, can sort waste into hazardous and harmless, can transmit waste weight data, and can be controlled remotely and equipped with livestream. The developed system is tested by the methods of functionality testing, performance testing, and connectivity testing. Functionality testing gives the result that the whole system can work. Performance testing on the ultrasonic sensor results in an accuracy rate of 97.18%, the MG995 servo motor is at 100%, the weight sensor has an accuracy rate of 98.65%, and the use of batteries in standby can work for 13 hours 3 minutes 40 seconds and in a running state can work for 1 hour 56 minutes 42 seconds. The connectivity test of the average delay of robot control when given a command is 103.4ms, and the delay in sending waste weight data is 112.8ms.

Keywords

HX711, internet of thing, load cell half bridge, mobile smart trash bin, raspberry pi, sensor ultrasonic HX711, internet of thing, load cell half bridge, mobile smart trash bin, raspberry pi, sensor ultrasonic

Article Details

Author Biographies

Indra Hermawan, Politeknik Negeri Jakarta

Politeknik Negeri Jakarta, Teknik Informatika dan Komputer

asep kurniawan, Politeknik Negeri Jakarta

Politeknik Negeri Jakarta, Teknik Informatika dan Komputer
How to Cite
Hermawan, I., kurniawan, asep, Hanafi, R., Kinandes Sumarsono, A. F., & Arlan Ardiawan, M. (2023). Development of Mobile Smart Trash Bin Using Raspberry Pi. Jurnal Komputer Terapan, 9(1), 19–30. https://doi.org/10.35143/jkt.v9i1.5749

References

  1. Q. Zhang, Q. Yang, X. Zhang, Q. Bao, J. Su, and X. Liu, “Waste image classification based on transfer learning and convolutional neural network,” Waste Manag., vol. 135, no. August, pp. 150–157, 2021, doi: 10.1016/j.wasman.2021.08.038.
  2. F. Uguz, A. Kirkas, T. Yalvac, K. M. Gundogan, and K. Gezginc, “Is there a higher prevalence of mood and anxiety disorders among pregnant women during the COVID-19 pandemic? A comparative study,” J. Psychosom. Res., vol. 155, no. January, p. 110725, 2022, doi: 10.1016/j.jpsychores.2022.110725.
  3. K. Xiang, W.-J. Huang, F. Gao, and Q. Lai, “COVID-19 prevention in hotels: Ritualized host-guest interactions,” Ann. Tour. Res., vol. 93, p. 103376, 2022, doi: 10.1016/j.annals.2022.103376.
  4. D. Cudjoe, H. Wang, and B. zhu, “Thermochemical treatment of daily COVID-19 single-use facemask waste: Power generation potential and environmental impact analysis,” Energy, p. 123707, 2022, doi: 10.1016/j.energy.2022.123707.
  5. T. Chowdhury, H. Chowdhury, M. S. Rahman, N. Hossain, A. Ahmed, and S. M. Sait, “Estimation of the healthcare waste generation during COVID-19 pandemic in Bangladesh,” Sci. Total Environ., vol. 811, p. 152295, 2022, doi: 10.1016/j.scitotenv.2021.152295.
  6. M. Ranjbari, Z. Shams Esfandabadi, S. Gautam, A. Ferraris, and S. D. Scagnelli, “Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses,” Gondwana Res., no. xxxx, 2022, doi: 10.1016/j.gr.2021.12.015.
  7. L. Long, “Research on status information monitoring of power equipment based on Internet of Things,” Energy Reports, vol. 8, pp. 281–286, 2022, doi: 10.1016/j.egyr.2022.01.018.
  8. P. P. Ray, “A survey on Internet of Things architectures,” J. King Saud Univ. - Comput. Inf. Sci., vol. 30, no. 3, pp. 291–319, 2018, doi: 10.1016/j.jksuci.2016.10.003.
  9. F. Nahdi and H. Dhika, “Analisis Dampak Internet of Things ( IoT ) Pada Perkembangan Teknologi di Masa Yang Akan Datang,” 2021.
  10. F. Fadel, “The Design and Implementation of Smart Trash Bin,” Acad. J. Nawroz Univ., vol. 6, no. 3, pp. 141–148, 2017, doi: 10.25007/ajnu.v6n3a103.
  11. H. Hassan, F. Saad, and M. S. Mohd Raklan, “A Low-Cost Automated Sorting Recycle Bin powered by Arduino Microcontroller,” Proc. - 2018 IEEE Conf. Syst. Process Control. ICSPC 2018, no. December, pp. 182–186, 2018, doi: 10.1109/SPC.2018.8704146.
  12. M. Karthik, L. Sreevidya, R. Nithya Devi, M. Thangaraj, G. Hemalatha, and R. Yamini, “An efficient waste management technique with IoT based smart garbage system,” Mater. Today Proc., no. xxxx, pp. 7–10, 2021, doi: 10.1016/j.matpr.2021.07.179.
  13. M. Syafaat, W. F. Safari, and S. Wahyu, “Perancangan Dan Pembuatan Mobile Robot Smart Trash Bin Berbasis Bluetooth HC-05,” J. Tek., vol. 9, no. 2, pp. 78–86, 2020, doi: 10.31000/jt.v9i2.3623.
  14. P. Casado, J. M. Blanes, C. Torres, C. Orts, D. Marroquí, and A. Garrigós, “Raspberry Pi based photovoltaic I-V curve tracer,” HardwareX, vol. 11, p. e00262, 2022, doi: 10.1016/j.ohx.2022.e00262.