An Intelligent IoT-Based Waste Bin System Utilizing Nearest Neighbor Algorithms for Optimized Waste Collection Routes
DOI:
https://doi.org/10.61255/decoding.v4i2.1318Keywords:
Digital twin, Internet of things, Nearest neighbor algorithm, Route optimization, Smart waste binAbstract
Purpose – Despite advances in IoT-enabled waste monitoring, existing solutions generally fail to integrate real-time bin status information with adaptive route optimization, resulting in inefficient collection operations. This study aims to design and implement an integrated system that leverages real-time waste data to facilitate intelligent, data-driven route optimization for improved waste collection operations.
Methods –This study presents an ESP32-based smart waste system using reed switch event-driven control and deep-sleep mode for energy efficiency. Waste levels were estimated using the arithmetic mean fusion of four VL53L0X sensors. A cloud-based MQTT-over-TLS architecture enables secure real-time communication, whereas a priority-based nearest-neighbor routing algorithm is evaluated across 150 nodes.
Findings – The results demonstrate that the proposed system provides accurate waste-level estimation with a mean error of 1.98%, significantly reduces energy consumption by 90.9% through deep-sleep operation, and supports near-real-time communication with an average latency of 4.66 s. Moreover, the priority-based route optimization strategy decreased the travel distance by 42.7%, ensured the immediate servicing of all full-status bins, and maintained operational feasibility within a fleet capacity of 2,700 L.
Research implications – The evaluation results demonstrate the feasibility of integrating real-time monitoring and adaptive route optimization for smart waste management. Future research should extend the validation to large-scale real-world deployments and incorporate road network-based routing models to enhance operational realism and optimization accuracy.
Originality – This study proposes an integrated smart waste platform that combines energy-efficient event-driven sensing, dynamic priority-based nearest-neighbor routing, and hardware-assisted digital twin validation for scalable and cost-effective waste management evaluation.
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References
M. A. Maulana, A. Syukri, M. D. Nurfaisal, and I. Sari, “Optimalisasi Teknologi untuk Efisiensi dan Transparansi Dalam Pengawasan Pengelolaan Sampah di Kota Serang,” Kybernology J. Gov. Stud., vol. 5, no. 1, pp. 67–80, Aug. 2025, doi: 10.26618/kjgs.v5i1.17802.
N. I. Chairunnisa et al., “Faktor-Faktor yang Mempengaruhi Perilaku Masyarakat dalam Pengelolaan Sampah Rumah Tangga di Kecamatan Harau, Sumatera Barat,” J. Huk. Polit. DAN ILMU Sos., vol. 4, no. 4, pp. 01–13, Jan. 2026, doi: 10.55606/jhpis.v4i4.5722.
“SIPSN - Sistem Informasi Pengelolaan Sampah Nasional.” Accessed: Apr. 24, 2025. [Online]. Available: https://sipsn.menlhk.go.id/sipsn/
Department of Environment and Forestry of the Special Region of Yogyakarta, “SIPSN KLHK Waste Generation Data of the Special Region of Yogyakarta for 2024,” Department of Environment and Forestry of the Special Region of Yogyakarta, unpublished raw dataset (Microsoft Excel), provided to the authors, 2025.
Department of Environment and Forestry of the Special Region of Yogyakarta, “SIPSN Achievement Data of the Special Region of Yogyakarta for 2024,” unpublished raw dataset (Microsoft Excel), provided to the authors, 2025.
G. G. H. Bhodas and M. R. Firdaus, “Efektivitas Pengelolaan Sampah Di Tempat Pengolahan Sampah 3R (TPS 3R) Di Kecamatan Tanta Kabupaten Tabalong,” JAPB, vol. 8, no. 2, pp. 1499–1533, Oct. 2025, doi: 10.35722/japb.v8i2.1300.
Field Operations Personnel, “Personal communication (structured interview),” Sendangtirto, Sleman, Yogyakarta, Apr. 22, 2025.
A. Suryaningrat, D. Kurnianto, and F. T. Syifa, “Pemanfaatan Google Firebase Pada Sistem Tempat Sampah Pintar Berbasis Internet of Things,” Din. Rekayasa, vol. 17, no. 1, Art. no. 1, 2020, doi: 10.20884/1.dr.2021.17.1.324.
D. Firmansyah, A. Ullah, A. Faizal, and H. Zarory, “Perancangan Sistem Pemantauan Kondisi Tempat Sampah Kampus Berbasis Internet of Things (iot) (studi Kasus: Fakultas Sains Dan Teknologi Uin Suska Riau),” Transm. J. Ilm. Tek. Elektro, vol. 25, no. 4, pp. 165–171, Dec. 2023, doi: 10.14710/transmisi.25.4.165-171.
M. Ismail, R. K. Abdullah, and S. Abdussamad, “Tempat Sampah Pintar Berbasis Internet of Things (IoT) Dengan Sistem Teknologi Informasi,” Jambura J. Electr. Electron. Eng., vol. 3, no. 1, Art. no. 1, Jan. 2021, doi: 10.37905/jjeee.v3i1.8099.
K. A. Verryando, R. J. Iskandar, and A. Y. A. Putra, “Implementasi Sensor Ultrasonik Pada Tempat Sampah Pintar Berbasis IoT,” INTEKSIS, vol. 11, no. 1, pp. 1–12, May 2024, doi: 10.66003/inteksis.v11i1.9921.
Y. B. Widodo, T. Sutabri, and L. Faturahman, “Tempat Sampah Pintar Dengan Notifikasi Berbasis IOT,” J. Teknol. Inform. Dan Komput., vol. 5, no. 2, pp. 50–57, Oct. 2019, doi: 10.37012/jtik.v5i2.175.
M. Chaerul, M. Puturuhu, and I. Artika, “Optimasi Rute Pengangkutan Sampah dengan Menggunakan Metode Nearest Neighbour (Studi Kasus: Kabupaten Manokwari, Papua Barat),” J. Wil. Dan Lingkung., vol. 10, no. 1, pp. 55–68, Apr. 2022, doi: 10.14710/jwl.10.1.55-68.
P. N. Yanti, R. Vikaliana, and I. N. Purnaya, “Implikasi Metode Nearest Neighbor Terhadap Efektivitas Penjadwalan Truk Pengangkutan Sampah Di Dinas Lingkungan Hidup Kota Mataram,” Pros. Semin. Nas. Manaj. Ind. Dan Rantai Pasok, vol. 2, pp. 134–141, 2021.
S. M. Maturi, S. R. Dhanikonda, and S. Giddaluru, “Smart Dustbins: Real-Time Monitoring and Optimization for Waste Management in Smart Cities through IoT Devices,” Eng. Technol. Appl. Sci. Res., vol. 15, no. 1, pp. 19246–19252, Feb. 2025, doi: 10.48084/etasr.8562.
R. Alnanih, L. Elrefaei, and A. Al-Ahwal, “Advancing Sustainability Through an IoT-Driven Smart Waste Management System with Software Engineering Integration,” Sustainability, vol. 17, no. 21, p. 9803, Jan. 2025, doi: 10.3390/su17219803.
L. Barth, L. Schweiger, R. Benedech, and M. Ehrat, “From data to value in smart waste management: Optimizing solid waste collection with a digital twin-based decision support system,” Decis. Anal. J., vol. 9, p. 100347, Dec. 2023, doi: 10.1016/j.dajour.2023.100347.
D. A. Fitriani, T. Khotimah, and A. Jazuli, “Implementasi Iot Untuk Pengelolaan Sampah Cerdas Berbasis Sensor Di Kawasan Perumahan,” JATI J. Mhs. Tek. Inform., vol. 9, no. 4, pp. 7320–7325, May 2025, doi: 10.36040/jati.v9i4.14483.
K. Mekki, E. Bajic, F. Chaxel, and F. Meyer, “A comparative study of LPWAN technologies for large-scale IoT deployment,” ICT Express, vol. 5, no. 1, pp. 1–7, Mar. 2019, doi: 10.1016/j.icte.2017.12.005.
W. Royce, “Managing the Development of Large Software Systems (1970),” 2021, pp. 321–332. doi: 10.7551/mitpress/12274.003.0035.
I. Sommerville, Software engineering, Tenth edition. in Always learning. Boston Columbus Indianapolis New York San Francisco Hoboken Amsterdam Cape Town Dubai London: Pearson, 2016.
H. Mantik, “Revolusi Industri 4.0: Internet of Things, Implementasi Pada Berbagai Sektor Berbasis Teknologi Informasi (bagian 1),” JSI J. Sist. Inf. Univ. Suryadarma, vol. 9, no. 2, pp. 41–48, Jul. 2022, doi: 10.35968/jsi.v9i2.919.
D. Ramadhan, A. Hakim, and D. R. Irawati, “Sistem Pemantauan Dan Keamanan Pada Toko Berbasis Mikrokontroler Esp32 Devkit V1, Esp32 Cam Ai Thinker, Sensor Am312 Dan Buzzer Berbasis Iot,” J. Inf. Syst. Inform. Comput., vol. 9, no. 1, pp. 191–199, Jun. 2025, doi: 10.52362/jisicom.v9i1.1926.
J. Riyanto and A. Wasid, “Perancangan Alat Bantu Parkir Mobil Berbasis Esp32-Cam Dan Sensor Jarak Vl53l0x Menggunakan Vlc,” J. Inform. Dan Komputasi Media Bahasan Anal. Dan Apl., vol. 17, no. 1, pp. 1–5, Jun. 2023, doi: 10.56956/jiki.v17i1.173.
“TCA9548A Low-Voltage 8-Channel I2C Switch With Reset,” Texas Instruments, SCPS207D, 2012, rev. 2015. Accessed: Jun. 09, 2026. [Online]. Available: https://www.ti.com/lit/ds/symlink/tca9548a.pdf
I. S. Sudibyo, B. F. T. K, and M. S. K. T. S. Utomo, “Analisis Manajemen Termal Cylindrical Battery Pack Li-Ion 18650 Secara Konveksi Paksa Dengan Variasi Temperatur Inlet dan Laju Aliran Udara Menggunakan Computional Fluid Dynamics (CFD),” J. Tek. MESIN, vol. 11, no. 1, Art. no. 1, Jan. 2023, doi: 10.36706/jrm.v24i2.554.
I. W. Nugraha, S. Triwijaya, Y. Wiarco, and M. Rukmana, “Prototipe Battery Management System dengan mempertimbangkan State of Charge dan State of Health,” J. Perkeretaapi. Indones. Indones. Railw. J., vol. 7, no. 2, pp. 61–70, Oct. 2023, doi: 10.37367/jpi.v7i2.292.
H. A. Kusuma, R. Ariandhi, S. Refly, and S. Nugraha, “Development Arduino Data Logger using INA219 Sensor for Battery Capacity Monitoring,” J. Tek. Elektro Dan Komputasi ELKOM, vol. 5, no. 1, pp. 9–15, Mar. 2023, doi: 10.32528/elkom.v5i1.8352.
“MT3608: High-Efficiency 1.2 MHz 2 A Step-Up Converter,” Aerosemi Technology Co., Ltd., Datasheet, Rev. 1.0. Accessed: Jun. 09, 2026. [Online]. Available: https://www.olimex.com/Products/Breadboarding/BB-PWR-3608/resources/MT3608.pdf
S. Dani, “Peringatan Pintu Belum Tertutup Menggunakan Sensor Magnetik (Reed Switch) dan ESP32,” Comput. J., vol. 4, no. 1, pp. 27–33, Feb. 2026, doi: 10.58477/cj.v4i1.356.
A. Awouda, E. Traini, G. Bruno, and P. Chiabert, “IoT-Based Framework for Digital Twins in the Industry 5.0 Era,” Sensors, vol. 24, no. 2, p. 594, Jan. 2024, doi: 10.3390/s24020594.
S. Komarizadehasl, B. Mobaraki, H. Ma, J.-A. Lozano-Galant, and J. Turmo, “Low-Cost Sensors Accuracy Study and Enhancement Strategy,” Appl. Sci., vol. 12, no. 6, p. 3186, Jan. 2022, doi: 10.3390/app12063186.
B. Khaleghi, A. Khamis, F. O. Karray, and S. N. Razavi, “Multisensor data fusion: A review of the state-of-the-art,” Inf. Fusion, vol. 14, no. 1, pp. 28–44, Jan. 2013, doi: 10.1016/j.inffus.2011.08.001.
R. Palupi, D. A. Yulianna, and S. S. Winarsih, “Analisa Perbandingan Rumus Haversine Dan Rumus Euclidean Berbasis Sistem Informasi Geografis Menggunakan Metode Independent Sample t-Test,” JITU J. Inform. Technol. Commun., vol. 5, no. 1, pp. 40–47, Jul. 2021, doi: 10.36596/jitu.v5i1.494.
“ESP32 Series Datasheet,” Espressif Systems, Espressif Systems, 2023. Accessed: Jun. 09, 2026. [Online]. Available: https://documentation.espressif.com/esp32_datasheet_en.pdf
“INA219 Zerø-Drift, Bidirectional Current/Power Monitor with I2C Interface,” Texas Instruments, INA219 datasheet, Aug. 2008 [Revised Dec. 2011]. Accessed: Jun. 09, 2026. [Online]. Available: https://www.ti.com/lit/ds/symlink/ina219.pdf
“AMS1117 1 A Low Dropout Voltage Regulator,” Advanced Monolithic Systems, AMS1117 datasheet. Accessed: Jun. 09, 2026. [Online]. Available: http://www.advanced-monolithic.com/pdf/ds1117.pdf
