Monitoring and Datalogging System for Suspended Sediment Concentration in a Trapezoidal Flume Using IoT and Fuzzy Logic
Article Sidebar
Published
Jan 31, 2026
Main Article Content
Abstract
This study seeks to establish a system for monitoring and forecasting suspended sediment concentration (SSC) via the Internet of Things (IoT) and fuzzy logic, implemented through LabVIEW on a laboratory-scale trapezoidal flume prototype. The system incorporates a flowmeter sensor (YF-S201), a water turbidity sensor (SEN0189), and a photodiode sensor for the measurement of SSC. The sediment samples utilized were silty clay soil from the West Flood Canal (KBB). The ESP32 microcontroller acquires data every 10 seconds, transmits it over TCP-IP communication to LabVIEW, stores it in an Excel file, and simultaneously uploads it to Google Sheets as a cloud database. The monitoring functionality is presented via an LCD, displaying real-time data from Google Sheets through API capabilities, thereby functioning as a synchronized integrated datalogger. Execution of fuzzy logic: The LabVIEW Fuzzy Logic Designer employs the Sugeno model, utilizing flow rate and turbidity as input variables, with SSC predicted as the output. The testing results on 2050 measurement data indicate a steady average time recording period of 8-10 seconds without latency, with a time recording error of merely 0.2%. Integration of monitoring and datalogging of IoT-based fuzzy logic real-time assessment of SSC in a trapezoidal flume.
Article Details
How to Cite
Nuha, K., Oktivasari, P., & Yatmadi, D. (2026). Monitoring and Datalogging System for Suspended Sediment Concentration in a Trapezoidal Flume Using IoT and Fuzzy Logic. Journal of Telecommunication Electronics and Control Engineering (JTECE), 8(1), 36-49. https://doi.org/10.20895/jtece.v8i1.2034
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
[1]. T. Matos, C. L. Faria, M. S. Martins, R. Henriques, P. A. Gomes, and L. M. Goncalves, “Design of a multipoint cost-effective optical instrument for continuous in-situ monitoring of turbidity and sediment,” Sensors (Switzerland), vol. 20, no. 11, Jun. 2020, doi: 10.3390/s20113194.
[2]. T. Matos, M. S. Martins, R. Henriques, and L. M. Goncalves, “Design of a sensor to estimate suspended sediment transport in situ using the measurements of water velocity, suspended sediment concentration and depth,” J Environ Manage, vol. 365, Aug. 2024, doi: 10.1016/j.jenvman.2024.121660.
[3]. J. Droujko and P. Molnar, “Open-source, low-cost, in-situ turbidity sensor for river network monitoring,” Sci Rep, vol. 12, no. 1, Dec. 2022, doi: 10.1038/s41598-022-14228-4.
[4]. Y. Li and D. van Zyl, “Analysing the segregation of coarse tailings particles with a zone-formation differential settling model,” Australian Centre for Geomechanics, 2024, pp. 271–282. doi: 10.36487/acg_repo/2455_22.
[5]. Y. Li, Z. Xu, X. Zhan, and T. Zhang, “Summary of Experiments and Influencing Factors of Sediment Settling Velocity in Still
Water,” Apr. 01, 2024, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/w16070938.
[6]. M. Anuri and R. Islamadina, “Analisis Kualitas Air Logika Fuzzy Mamdani.”
[7]. A. Suaif, D. S. Maulana, L. Yuliantini, and N. S. Aminah, Sistem Monitoring Sedimentasi Layang Sungai Cikapundung Berbasis Wireless System Menggunakan Spektroskopi Infrared. 2017. [Online]. Available: https://www.researchgate.net/publication/324834193
[8]. M. Dadi and M. Yasir, “Spectroscopy and Spectrophotometry: Principles and Applications for Colorimetric and Related Other Analysis,” in Colorimetry, IntechOpen, 2022. doi: 10.5772/intechopen.101106.
[9]. O. Kisi and Z. M. Yaseen, “The potential of hybrid evolutionary fuzzy intelligence model for suspended sediment concentration prediction,” Catena (Amst), vol. 174, pp. 11–23, Mar. 2019, doi: 10.1016/j.catena.2018.10.047.
[10]. R. M. Adnan, Z. M. Yaseen, S. Heddam, S. Shahid, A. Sadeghi-Niaraki, and O. Kisi, “Predictability performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid adaptive neuro-fuzzy system model,” International Journal of Sediment Research, vol. 37, no. 3, pp. 383–398, Jun. 2022, doi: 10.1016/j.ijsrc.2021.10.001.
[11]. K. Rezaei and M. Vadiati, “A comparative study of artificial intelligence models for predicting monthly river suspended sediment load,” Journal of Water and Land Development, vol. 45, pp. 107–118, 2020, doi: 10.24425/jwld.2020.133052.
[12]. W. Kang, K. Lee, and J. Kim, “Prediction of Suspended Sediment Concentration Based on the Turbidity–Concentration Relationship Determined via Underwater Image Analysis,” Applied Sciences (Switzerland), vol. 12, no. 12, Jun. 2022, doi: 10.3390/app12126125.
[13]. L. C. Teixeira, P. P. Mariani, O. C. Pedrollo, N. M. dos Reis Castro, and V. Sari, “Artificial Neural Network and Fuzzy Inference System Models for Forecasting Suspended Sediment and Turbidity in Basins at Different Scales,” Water Resources Management, vol. 34, no. 11, pp. 3709–3723, Sep. 2020, doi: 10.1007/s11269-020-02647-9.
[14]. S. Kambalimath and P. C. Deka, “A basic review of fuzzy logic applications in hydrology and water resources,” Aug. 01, 2020, Springer Science and Business Media Deutschland GmbH. doi: 10.1007/s13201-020-01276-2.
[15]. N. Das, S. Saha, M. Nasipuri, S. Basu, and T. Chakraborti, “Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology,” PLoS One, vol. 18, no. 6 June, Jun. 2023, doi: 10.1371/journal.pone.0286862.
[16]. I. Abdi Pratama, H. Hariyadi, A. Wirasatriya, L. Maslukah, and D. M. Yusuf, “Validasi Pengukuran Turbiditas dan Material Padatan Tersuspensi di Banjir Kanal Barat, Semarang dengan Menggunakan Smartphone,” 2021. [Online]. Available: https://ejournal2.undip.ac.id/index.php/ijoce
[17]. F. Muhammad and D. A. Yunar, “Pengaruh Koefisien Kekasaran Chezy Tehadap Angkutan Sedimen Dasar Sungai di Ruas Jembatan Maesa-Nunu Palu,” Jurnal Sains dan Teknologi Tadulako, vol. 8, no. 2, p. 2022, 2022.
[18]. J. Ni, B. Yu, and P. Wu, “A numerical study of the flow and sediment interaction in the middle reach of the huai river,” Water (Switzerland), vol. 13, no. 15, Aug. 2021, doi: 10.3390/w13152041.
[19]. B. Yan, R. Zhang, and P. Zhang, “Flume experiment on the sediment-retaining effect of submerged breakwaters under the combined action of waves and currents,” J Mar Sci Eng, vol. 8, no. 5, May 2020, doi: 10.3390/JMSE8050340.
[20]. E. Widia Astuti et al., “Sistem Pengukuran Tingkat Kekeruhan Air (Turbidity) Dengan Metode Spektofotometri AFILIASI.” [Online]. Available: https://journal.unej.ac.id/JEI
[21]. A. Hermawan and E. N. Afiato, “Analisis Angkutan Sedimen Dasar (Bed Load) Pada Saluran Irigasi Yogya,” vol. XXVI, no. 1, 2021.
[22]. G. Zenan, B. Attila, and P. T. Szemes, “Actuator control using TCP IP communication under LabVIEW USB6001 environment,”
[23]. Carpathian Journal of Electronic and Computer Engineering, vol. 14, no. 2, pp. 11–14, Dec. 2021, doi: 10.2478/cjece-2021-0008.
[24]. R. M. Adnan, K. S. Parmar, S. Heddam, S. Shahid, and O. Kisi, “Suspended sediment modeling using a heuristic regression method hybridized with kmeans clustering,” Sustainability (Switzerland), vol. 13, no. 9, May 2021, doi: 10.3390/su13094648.
[25]. C. Luo and H. Wang, “Fuzzy forecasting for long-term time series based on time-variant fuzzy information granules,” Applied Soft Computing Journal, vol. 88, Mar. 2020, doi: 10.1016/j.asoc.2019.106046.
[26]. A. Adriansyah, M. H. Budiutomo, H. Hermawan, R. I. Andriani, R. Sulistyawan, and A. U. Shamsudin, “Design of water level detection monitoring system using fusion sensor based on Internet of Things (IoT),” Sinergi (Indonesia), vol. 28, no. 1, pp. 191–198, 2024, doi: 10.22441/sinergi.2024.1.019.
[27]. Y. R. Sujono, E. Sulistio Budi, and I. Nugrahanto, “Modul Pengaturan Motor Pompa DC Metode PID pada Sistem Kontrol Ketinggian Air berbasis Arduino,” Jurnal Elkolind, vol. 10, no. 2, 2023, doi: 10.33795/elkolind.v10i2.3624.
[28]. A. Khedri, N. Kalantari, and M. Vadiati, “Comparison study of artificial intelligence method for short term groundwater level prediction in the northeast Gachsaran unconfined aquifer,” Water Sci Technol Water Supply, vol. 20, no. 3, pp. 909–921, May 2020, doi: 10.2166/ws.2020.015.
[29]. A. Choudhary, B. S. Das, K. Devi, and J. R. Khuntia, “ANFIS- and GEP-based model for prediction of scour depth around bridge pier in clear-water scouring and live-bed scouring conditions,” Journal of Hydroinformatics, vol. 25, no. 3, pp. 1004–1028, May 2023, doi: 10.2166/hydro.2023.212.
[30]. R. Ananda Pratama and M. Arman, “Sistem Akuisisi Data Temperatur Showcase Berbasis IoT Menggunakan ESP32 dengan Sensor Termokopel dan Logging ke Google Spreadsheets.”
[31]. Dr Apurva Yadav, Pradhnesh Dalvi, and Harshal Juwale, “RFID-Based Attendance Management System Using ESP32 and Google Sheets,” The Voice of Creative Research, vol. 7, no. 2, pp. 419–429, Apr. 2025, doi: 10.53032/tvcr/2025.v7n2.51.
[32]. M. D. Ramadhan, A. Wisaksono, J. Jamaaluddin, and A. Ahfas, “Prototype Of Moisture Content Meter In Grain Using Esp32 Based On Spreadsheet,” Journal of Computer Networks, Architecture and High Performance Computing, vol. 6, no. 2, pp. 502–513, Apr. 2024, doi: 10.47709/cnahpc.v6i2.3530.
[33]. B. Qayyum, A. Ahmed, I. Ullah, and S. A. Shah, “A Fuzzy-Logic Approach for Optimized and Cost-Effective Early Warning System for Tsunami Detection,” Sustainability (Switzerland), vol. 14, no. 21, Nov. 2022, doi: 10.3390/su142114516.
[34]. D. Yatmadi, M. S. B. Kusuma, M. Muin, N. Yuanita, A. B. Muslim, and H. N. Alam, “Sediment Transport of Cohesive Sediment in Kanal Banjir Barat Jakarta Using Non-Orthogonal Boundary Fitted Model,” International Journal of Design and Nature and Ecodynamics, vol. 19, no. 4, pp. 1231–1242, Aug. 2024, doi: 10.18280/ijdne.190414. “Peraturan Kementrian Kesehatan Republik Indonesia.”
[35]. N. Jafarzade et al., “Viability of two adaptive fuzzy systems based on fuzzy c means and subtractive clustering methods for modeling Cadmium in groundwater resources,” Heliyon, vol. 9, no. 8, Aug. 2023, doi: 10.1016/j.heliyon.2023.e18415.
[36]. A. C. Rizky, M. Rangga, P. Kusuma, and A. Muzakki, “Aquabot Guard: Upaya FIltrasi Hasil Sedimentasi Laut yang Ramaha Lingkungan dan Berkelanjutan Bagi Ekosistem Laut (Aqua Bot Guard: Environmentally Friendly and Sustainable Marine Sedimentation Filtration Efforts for Marine Ecosystems),” vol. 2, no. 1, pp. 549–559, 2024.
[37]. M. Sedighkia, M. Jahanshahloo, and B. Datta, “Hybrid neuro fuzzy inference systems for simulating catchment sediment yield,” International Journal of Sediment Research, vol. 39, no. 3, pp. 305–316, Jun. 2024, doi: 10.1016/j.ijsrc.2024.02.004.
[2]. T. Matos, M. S. Martins, R. Henriques, and L. M. Goncalves, “Design of a sensor to estimate suspended sediment transport in situ using the measurements of water velocity, suspended sediment concentration and depth,” J Environ Manage, vol. 365, Aug. 2024, doi: 10.1016/j.jenvman.2024.121660.
[3]. J. Droujko and P. Molnar, “Open-source, low-cost, in-situ turbidity sensor for river network monitoring,” Sci Rep, vol. 12, no. 1, Dec. 2022, doi: 10.1038/s41598-022-14228-4.
[4]. Y. Li and D. van Zyl, “Analysing the segregation of coarse tailings particles with a zone-formation differential settling model,” Australian Centre for Geomechanics, 2024, pp. 271–282. doi: 10.36487/acg_repo/2455_22.
[5]. Y. Li, Z. Xu, X. Zhan, and T. Zhang, “Summary of Experiments and Influencing Factors of Sediment Settling Velocity in Still
Water,” Apr. 01, 2024, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/w16070938.
[6]. M. Anuri and R. Islamadina, “Analisis Kualitas Air Logika Fuzzy Mamdani.”
[7]. A. Suaif, D. S. Maulana, L. Yuliantini, and N. S. Aminah, Sistem Monitoring Sedimentasi Layang Sungai Cikapundung Berbasis Wireless System Menggunakan Spektroskopi Infrared. 2017. [Online]. Available: https://www.researchgate.net/publication/324834193
[8]. M. Dadi and M. Yasir, “Spectroscopy and Spectrophotometry: Principles and Applications for Colorimetric and Related Other Analysis,” in Colorimetry, IntechOpen, 2022. doi: 10.5772/intechopen.101106.
[9]. O. Kisi and Z. M. Yaseen, “The potential of hybrid evolutionary fuzzy intelligence model for suspended sediment concentration prediction,” Catena (Amst), vol. 174, pp. 11–23, Mar. 2019, doi: 10.1016/j.catena.2018.10.047.
[10]. R. M. Adnan, Z. M. Yaseen, S. Heddam, S. Shahid, A. Sadeghi-Niaraki, and O. Kisi, “Predictability performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid adaptive neuro-fuzzy system model,” International Journal of Sediment Research, vol. 37, no. 3, pp. 383–398, Jun. 2022, doi: 10.1016/j.ijsrc.2021.10.001.
[11]. K. Rezaei and M. Vadiati, “A comparative study of artificial intelligence models for predicting monthly river suspended sediment load,” Journal of Water and Land Development, vol. 45, pp. 107–118, 2020, doi: 10.24425/jwld.2020.133052.
[12]. W. Kang, K. Lee, and J. Kim, “Prediction of Suspended Sediment Concentration Based on the Turbidity–Concentration Relationship Determined via Underwater Image Analysis,” Applied Sciences (Switzerland), vol. 12, no. 12, Jun. 2022, doi: 10.3390/app12126125.
[13]. L. C. Teixeira, P. P. Mariani, O. C. Pedrollo, N. M. dos Reis Castro, and V. Sari, “Artificial Neural Network and Fuzzy Inference System Models for Forecasting Suspended Sediment and Turbidity in Basins at Different Scales,” Water Resources Management, vol. 34, no. 11, pp. 3709–3723, Sep. 2020, doi: 10.1007/s11269-020-02647-9.
[14]. S. Kambalimath and P. C. Deka, “A basic review of fuzzy logic applications in hydrology and water resources,” Aug. 01, 2020, Springer Science and Business Media Deutschland GmbH. doi: 10.1007/s13201-020-01276-2.
[15]. N. Das, S. Saha, M. Nasipuri, S. Basu, and T. Chakraborti, “Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology,” PLoS One, vol. 18, no. 6 June, Jun. 2023, doi: 10.1371/journal.pone.0286862.
[16]. I. Abdi Pratama, H. Hariyadi, A. Wirasatriya, L. Maslukah, and D. M. Yusuf, “Validasi Pengukuran Turbiditas dan Material Padatan Tersuspensi di Banjir Kanal Barat, Semarang dengan Menggunakan Smartphone,” 2021. [Online]. Available: https://ejournal2.undip.ac.id/index.php/ijoce
[17]. F. Muhammad and D. A. Yunar, “Pengaruh Koefisien Kekasaran Chezy Tehadap Angkutan Sedimen Dasar Sungai di Ruas Jembatan Maesa-Nunu Palu,” Jurnal Sains dan Teknologi Tadulako, vol. 8, no. 2, p. 2022, 2022.
[18]. J. Ni, B. Yu, and P. Wu, “A numerical study of the flow and sediment interaction in the middle reach of the huai river,” Water (Switzerland), vol. 13, no. 15, Aug. 2021, doi: 10.3390/w13152041.
[19]. B. Yan, R. Zhang, and P. Zhang, “Flume experiment on the sediment-retaining effect of submerged breakwaters under the combined action of waves and currents,” J Mar Sci Eng, vol. 8, no. 5, May 2020, doi: 10.3390/JMSE8050340.
[20]. E. Widia Astuti et al., “Sistem Pengukuran Tingkat Kekeruhan Air (Turbidity) Dengan Metode Spektofotometri AFILIASI.” [Online]. Available: https://journal.unej.ac.id/JEI
[21]. A. Hermawan and E. N. Afiato, “Analisis Angkutan Sedimen Dasar (Bed Load) Pada Saluran Irigasi Yogya,” vol. XXVI, no. 1, 2021.
[22]. G. Zenan, B. Attila, and P. T. Szemes, “Actuator control using TCP IP communication under LabVIEW USB6001 environment,”
[23]. Carpathian Journal of Electronic and Computer Engineering, vol. 14, no. 2, pp. 11–14, Dec. 2021, doi: 10.2478/cjece-2021-0008.
[24]. R. M. Adnan, K. S. Parmar, S. Heddam, S. Shahid, and O. Kisi, “Suspended sediment modeling using a heuristic regression method hybridized with kmeans clustering,” Sustainability (Switzerland), vol. 13, no. 9, May 2021, doi: 10.3390/su13094648.
[25]. C. Luo and H. Wang, “Fuzzy forecasting for long-term time series based on time-variant fuzzy information granules,” Applied Soft Computing Journal, vol. 88, Mar. 2020, doi: 10.1016/j.asoc.2019.106046.
[26]. A. Adriansyah, M. H. Budiutomo, H. Hermawan, R. I. Andriani, R. Sulistyawan, and A. U. Shamsudin, “Design of water level detection monitoring system using fusion sensor based on Internet of Things (IoT),” Sinergi (Indonesia), vol. 28, no. 1, pp. 191–198, 2024, doi: 10.22441/sinergi.2024.1.019.
[27]. Y. R. Sujono, E. Sulistio Budi, and I. Nugrahanto, “Modul Pengaturan Motor Pompa DC Metode PID pada Sistem Kontrol Ketinggian Air berbasis Arduino,” Jurnal Elkolind, vol. 10, no. 2, 2023, doi: 10.33795/elkolind.v10i2.3624.
[28]. A. Khedri, N. Kalantari, and M. Vadiati, “Comparison study of artificial intelligence method for short term groundwater level prediction in the northeast Gachsaran unconfined aquifer,” Water Sci Technol Water Supply, vol. 20, no. 3, pp. 909–921, May 2020, doi: 10.2166/ws.2020.015.
[29]. A. Choudhary, B. S. Das, K. Devi, and J. R. Khuntia, “ANFIS- and GEP-based model for prediction of scour depth around bridge pier in clear-water scouring and live-bed scouring conditions,” Journal of Hydroinformatics, vol. 25, no. 3, pp. 1004–1028, May 2023, doi: 10.2166/hydro.2023.212.
[30]. R. Ananda Pratama and M. Arman, “Sistem Akuisisi Data Temperatur Showcase Berbasis IoT Menggunakan ESP32 dengan Sensor Termokopel dan Logging ke Google Spreadsheets.”
[31]. Dr Apurva Yadav, Pradhnesh Dalvi, and Harshal Juwale, “RFID-Based Attendance Management System Using ESP32 and Google Sheets,” The Voice of Creative Research, vol. 7, no. 2, pp. 419–429, Apr. 2025, doi: 10.53032/tvcr/2025.v7n2.51.
[32]. M. D. Ramadhan, A. Wisaksono, J. Jamaaluddin, and A. Ahfas, “Prototype Of Moisture Content Meter In Grain Using Esp32 Based On Spreadsheet,” Journal of Computer Networks, Architecture and High Performance Computing, vol. 6, no. 2, pp. 502–513, Apr. 2024, doi: 10.47709/cnahpc.v6i2.3530.
[33]. B. Qayyum, A. Ahmed, I. Ullah, and S. A. Shah, “A Fuzzy-Logic Approach for Optimized and Cost-Effective Early Warning System for Tsunami Detection,” Sustainability (Switzerland), vol. 14, no. 21, Nov. 2022, doi: 10.3390/su142114516.
[34]. D. Yatmadi, M. S. B. Kusuma, M. Muin, N. Yuanita, A. B. Muslim, and H. N. Alam, “Sediment Transport of Cohesive Sediment in Kanal Banjir Barat Jakarta Using Non-Orthogonal Boundary Fitted Model,” International Journal of Design and Nature and Ecodynamics, vol. 19, no. 4, pp. 1231–1242, Aug. 2024, doi: 10.18280/ijdne.190414. “Peraturan Kementrian Kesehatan Republik Indonesia.”
[35]. N. Jafarzade et al., “Viability of two adaptive fuzzy systems based on fuzzy c means and subtractive clustering methods for modeling Cadmium in groundwater resources,” Heliyon, vol. 9, no. 8, Aug. 2023, doi: 10.1016/j.heliyon.2023.e18415.
[36]. A. C. Rizky, M. Rangga, P. Kusuma, and A. Muzakki, “Aquabot Guard: Upaya FIltrasi Hasil Sedimentasi Laut yang Ramaha Lingkungan dan Berkelanjutan Bagi Ekosistem Laut (Aqua Bot Guard: Environmentally Friendly and Sustainable Marine Sedimentation Filtration Efforts for Marine Ecosystems),” vol. 2, no. 1, pp. 549–559, 2024.
[37]. M. Sedighkia, M. Jahanshahloo, and B. Datta, “Hybrid neuro fuzzy inference systems for simulating catchment sediment yield,” International Journal of Sediment Research, vol. 39, no. 3, pp. 305–316, Jun. 2024, doi: 10.1016/j.ijsrc.2024.02.004.