Pond Water Quality Monitoring in Consumption Fish Farming Industry Based on Internet of Things

Arsyad Cahya Subrata, Dwi Sulisworo, Meita Fitrianawati, Khairul Shafee Kalid, Wan Fatimah Wan Ahmad, Zul Hamdi Batubara, Muhammad Ramadhani

Abstract

The rapid increase in population in Indonesia has increased the demand for animal protein. As a source of animal protein, fish has excellent potential to be developed in Indonesia. However, care for water quality, a basic need, is often ignored. Meanwhile, increasing fish production can be done by ensuring that water quality is always in good condition. This research conducted aims to monitor water quality continuously. Integrating water quality monitoring systems using the Internet of Things (IoT) offers convenience in real-time monitoring and does not have to be present on-site. The parameters determining fish water quality are pH, electrical conductivity (EC), dissolved oxygen (DO), turbidity, and water temperature. The data obtained is then displayed on the Water Monitoring dashboard as graphs, indicators, and raw data the user can download. Overall, the system can measure, monitor in real-time, and store data on the results of measuring the quality of freshwater fish ponds on smartphones/laptops. The developed system also provides information on whether the water quality is “normal” or in conditions less and more than the threshold. Therefore, the developed system helps farmers monitor the quality of their fish ponds to increase the productivity of fish farming.

Keywords

water quality, internet of things, monitoring, real time

Full Text:

PDF

References

Abdalzaher, M. S., Soliman, M. S., El-Hady, S. M., Benslimane, A., & Elwekeil, M. (2021). A deep learning model for earthquake parameters observation in IoT system-based earthquake early warning. IEEE Internet of Things Journal, 9(11), 8412–8424.

Aggarwal, S., Mishra, P. K., Sumakar, K. V. S., & Chaturvedi, P. (2018). Landslide monitoring system implementing IOT using video camera. 2018 3rd International Conference for Convergence in Technology (I2CT), 1–4.

Ali, M. J., Mondal, A., & Dutta, P. (2022). Intelligent monitoring and control of wind turbine prototype using Internet of Things (IoT). 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), 1–6.

Almalawi, A., Alsolami, F., Khan, A. I., Alkhathlan, A., Fahad, A., Irshad, K., Qaiyum, S., & Alfakeeh, A. S. (2022). An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique. Environmental Research, 206, 112576.

Alphonsa, A., & Ravi, G. (2016). Earthquake early warning system by IOT using Wireless sensor networks. 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 1201–1205.

Arafat, A. I., Akter, T., Ahammed, M. F., Ali, M. Y., & Nahid, A.-A. (2020). A dataset for internet of things based fish farm monitoring and notification system. Data in Brief, 33, 106457.

Arshad, B., Ogie, R., Barthelemy, J., Pradhan, B., Verstaevel, N., & Perez, P. (2019). Computer vision and IoT-based sensors in flood monitoring and mapping: A systematic review. Sensors, 19(22), 5012.

Asha, P., Natrayan, L., Geetha, B. T., Beulah, J. R., Sumathy, R., Varalakshmi, G., & Neelakandan, S. (2022). IoT Enabled Environmental Toxicology for Air Pollution Monitoring using AI Techniques. Environmental Research, 205, 112574.

Bagwari, S., Gehlot, A., Singh, R., Priyadarshi, N., & Khan, B. (2021). Low-cost sensor-based and LoRaWAN opportunities for landslide monitoring systems on IoT platform: a review. IEEE Access, 10, 7107–7127.

Basu, M. T., Karthik, R., Mahitha, J., & Reddy, V. L. (2018). IoT based forest fire detection system. International Journal of Engineering & Technology, 7(2.7), 124–126.

Bauer, J., & Aschenbruck, N. (2018). Design and implementation of an agricultural monitoring system for smart farming. 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), 1–6.

Benzekri, W., El Moussati, A., Moussaoui, O., & Berrajaa, M. (2020). Early forest fire detection system using wireless sensor network and deep learning. International Journal of Advanced Computer Science and Applications, 11(5).

Chaduvula, K., Markapudi, B. R., & Jyothi, C. R. (2023). Design and Implementation of IoT based flood alert monitoring system using microcontroller 8051. Materials Today: Proceedings, 80, 2840–2844.

Chen, C.-H., Wu, Y.-C., Zhang, J.-X., & Chen, Y.-H. (2022). IoT-Based Fish Farm Water Quality Monitoring System. Sensors, 22(17), 6700.

Danh, L. V. Q., Dung, D. V. M., Danh, T. H., & Ngon, N. C. (2020). Design and deployment of an IoT-based water quality monitoring system for aquaculture in Mekong Delta. International Journal of Mechanical Engineering and Robotics Research, 9(8), 1170–1175.

Dubey, V., Kumar, P., & Chauhan, N. (2019). Forest fire detection system using IoT and artificial neural network. International Conference on Innovative Computing and Communications: Proceedings of ICICC 2018, Volume 1, 323–337.

Fauzia, S. R., & Suseno, S. H. (2020). Resirkulasi Air untuk Optimalisasi Kualitas Air Budidaya Ikan Nila Nirwana (Oreochromis niloticus). Jurnal Pusat Inovasi Masyarakat (PIM), 2(5), 887–892.

Fedele, R., Merenda, M., & Giammaria, F. (2018). Energy harvesting for IoT road monitoring systems. Instrumentation, Mesure, Metrologie, 17(4), 605.

GRARI, M., YANDOUZI, M., IDRISSI, I., BOUKABOUS, M., MOUSSAOUI, O., AZIZI, M., & MOUSSAOUI, M. (2022). Using IoT and ML for Forest Fire Detection, Monitoring, and Prediction: a Literature Review. Journal of Theoretical and Applied Information Technology, 100(19).

Hakim, W. M. A., Ramli, A. F., Basarudin, H., Abu, M. A., & Ahmad, I. (2020). WSN and IoT based landslide monitoring system. Test Engineering and Management, 83, 10926–10932.

Hidayatullah, M., Fat, J., & Andriani, T. (2018). Prototype Sistem Telemetri Pemantauan Kualitas Air pada Kolam Ikan Air Tawar Berbasis Mikrokontroler. Positron, 8(2), 43–52.

Hussain, A., Draz, U., Ali, T., Tariq, S., Irfan, M., Glowacz, A., Antonino Daviu, J. A., Yasin, S., & Rahman, S. (2020). Waste management and prediction of air pollutants using IoT and machine learning approach. Energies, 13(15), 3930.

Idrees, Z., Zou, Z., & Zheng, L. (2018). Edge computing based IoT architecture for low cost air pollution monitoring systems: a comprehensive system analysis, design considerations & development. Sensors, 18(9), 3021.

Jain, A., & Kumar, A. (2020). Smart agriculture monitoring system using IoT. International Journal for Research in Applied Science & Engineering Technology.

Jawad, H. M., Nordin, R., Gharghan, S. K., Jawad, A. M., & Ismail, M. (2017). Energy-efficient wireless sensor networks for precision agriculture: A review. Sensors, 17(8), 1781.

Karad, S., & Thakur, R. (2021). Efficient monitoring and control of wind energy conversion systems using Internet of things (IoT): a comprehensive review. Environment, Development and Sustainability, 23, 14197–14214.

Karunarathne, S. M., Dray, M., Popov, L., Butler, M., Pennington, C., & Angelopoulos, C. M. (2020). A technological framework for data-driven IoT systems: Application on landslide monitoring. Computer Communications, 154, 298–312.

Kaur, G., Braveen, M., Krishnapriya, S., Wawale, S. G., Castillo-Picon, J., Malhotra, D., & Osei-Owusu, J. (2023). Machine Learning Integrated Multivariate Water Quality Control Framework for Prawn Harvesting from Fresh Water Ponds. Journal of Food Quality, 2023.

Lakshmikantha, V., Hiriyannagowda, A., Manjunath, A., Patted, A., Basavaiah, J., & Anthony, A. A. (2021). IoT based smart water quality monitoring system. Global Transitions Proceedings, 2(2), 181–186.

Lau, Y. M., Wang, K. L., Wang, Y. H., Yiu, W. H., Ooi, G. H., Tan, P. S., Wu, J., Leung, M. L., Lui, H. L., & Chen, C. W. (2023). Monitoring of rainfall-induced landslides at Songmao and Lushan, Taiwan, using IoT and big data-based monitoring system. Landslides, 20(2), 271–296.

Mendoza-Cano, O., Aquino-Santos, R., López-de la Cruz, J., Edwards, R. M., Khouakhi, A., Pattison, I., Rangel-Licea, V., Castellanos-Berjan, E., Martinez-Preciado, M. A., & Rincón-Avalos, P. (2021). Experiments of an IoT-based wireless sensor network for flood monitoring in Colima, Mexico. Journal of Hydroinformatics, 23(3), 385–401.

Montanaro, T., Sergi, I., Basile, M., Mainetti, L., & Patrono, L. (2022). An iot-aware solution to support governments in air pollution monitoring based on the combination of real-time data and citizen feedback. Sensors, 22(3), 1000.

Nocheski, S., & Naumoski, A. (2018). Water monitoring iot system for fish farming ponds. Industry 4.0.

Pappu, S., Vudatha, P., Niharika, A. V, Karthick, T., & Sankaranarayanan, S. (2017). Intelligent IoT based water quality monitoring system. International Journal of Applied Engineering Research, 12(16), 5447–5454.

Pasika, S., & Gandla, S. T. (2020). Smart water quality monitoring system with cost-effective using IoT. Heliyon, 6(7), e04096.

Pirmagomedov, R., Blinnikov, M., Amelyanovich, A., Glushakov, R., Loskutov, S., Koucheryavy, A., Kirichek, R., & Bobrikova, E. (2018). IoT based earthquake prediction technology. Internet of Things, Smart Spaces, and Next Generation Networks and Systems: 18th International Conference, NEW2AN 2018, and 11th Conference, ruSMART 2018, St. Petersburg, Russia, August 27–29, 2018, Proceedings 18, 535–546.

Priharti, W., Rosmawati, A. F. K., & Wibawa, I. P. D. (2019). IoT based photovoltaic monitoring system application. Journal of Physics: Conference Series, 1367(1), 12069.

Rajakumar, G., Sankari, M. S., Shunmugapriya, D., & Maheswari, S. P. U. (2018). IoT based smart agricultural monitoring system. Asian J. Appl. Sci. Technol, 2, 474–480.

Ramya, A., Rohini, R., & Ravi, S. (2019). Iot based smart monitoring system for fish farming. International Journal of Engineering and Advanced Technology, 8(6 Special Issue), 420–424.

Rohadi, E., Adhitama, D. W., Ekojono, E., Ariyanto, R., Asmara, R. A., Ronilaya, F., Siradjuddin, I., & Setiawan, A. (2018). Sistem Monitoring Budidaya Ikan Lele Berbasis Internet Of Things Menggunakan Raspberry Pi. Jurnal Teknologi Informasi Dan Ilmu Komputer, 5(6), 745–750.

Saini, K., Kalra, S., & Sood, S. K. (2022). An Integrated Framework for Smart Earthquake Prediction: IoT, Fog, and Cloud Computing. Journal of Grid Computing, 20(2), 17.

Salam, A., & Salam, A. (2020). Internet of things for environmental sustainability and climate change. Internet of Things for Sustainable Community Development: Wireless Communications, Sensing, and Systems, 33–69.

Saputri, S. A. (2020). Pemanfaatan Tepung Ikan Salem pada Spicy Salem Fish Pie untuk Mendukung Gerakan Memasyarakatkan Makan Ikan (Gemarikan). Prosiding Pendidikan Teknik Boga Busana, 15(1).

Senthilkumar, R., Venkatakrishnan, P., & Balaji, N. (2020). Intelligent based novel embedded system based IoT enabled air pollution monitoring system. Microprocessors and Microsystems, 77, 103172.

Shah, W. M., Arif, F., Shahrin, A. A., & Hassan, A. (2018). The implementation of an IoT-based flood alert system. International Journal of Advanced Computer Science and Applications, 9(11).

Sharma, A., Singh, P. K., & Kumar, Y. (2020). An integrated fire detection system using IoT and image processing technique for smart cities. Sustainable Cities and Society, 61, 102332.

Sharma, M., Singla, M. K., Nijhawan, P., Ganguli, S., & Rajest, S. S. (2020). An application of IOT to develop concept of smart remote monitoring system. Business Intelligence for Enterprise Internet of Things, 233–239.

Srividhya, S., & Sankaranarayanan, S. (2020). IoT–fog enabled framework for forest fire management system. 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 273–276.

Subrata, A. C., Sutikno, T., Sunardi, A. P., Arsadiando, W., & Baswara, A. R. C. (2022). A laboratory scale IoT-based measuring of the solar photovoltaic parameters. Int J Reconfigurable & Embedded Syst, 11(2), 135–145.

Syamsunarno, M. B., & Sunarno, M. T. (2016). Budidaya Ikan Air Tawar Ramah Lingkungan untuk Mendukung Keberlanjutan Penyediaan Ikan bagi Masyarakat. Seminar Nasional Perikanan Dan Kelautan. Pembangunan Perikanan Dan Kelautan Dalam Mendukung Kedaulatan Pangan Nasional. Bandar Lampung. Hal, 1–15.

Thirugnanam, H., Uhlemann, S., Reghunadh, R., Ramesh, M. V., & Rangan, V. P. (2022). Review of landslide monitoring techniques with IoT integration opportunities. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 5317–5338.

Triantafyllou, A., Sarigiannidis, P., & Bibi, S. (2019). Precision agriculture: A remote sensing monitoring system architecture. Information, 10(11), 348.

Udanor, C. N., Ossai, N. I., Nweke, E. O., Ogbuokiri, B. O., Eneh, A. H., Ugwuishiwu, C. H., Aneke, S. O., Ezuwgu, A. O., Ugwoke, P. O., & Christiana, A. (2022). An internet of things labelled dataset for aquaponics fish pond water quality monitoring system. Data in Brief, 43, 108400.

Verma, V., Vutukuru, K. S., Divvela, S. S., & Sirigineedi, S. S. (2022). Internet of Things and Machine Learning Application for a Remotely Operated Wetland Siphon System During Hurricanes. In Water Resources Management and Sustainability (pp. 443–462). Springer.

Wang, E. K., Wang, F., Kumari, S., Yeh, J.-H., & Chen, C.-M. (2021). Intelligent monitor for typhoon in IoT system of smart city. The Journal of Supercomputing, 77, 3024–3043.

Zahir, S. B., Ehkan, P., Sabapathy, T., Jusoh, M., Osman, M. N., Yasin, M. N., Wahab, Y. A., Hambali, N. A. M., Ali, N., & Bakhit, A. S. (2019). Smart IoT flood monitoring system. Journal of Physics: Conference Series, 1339(1), 12043.

Zambrano, A. M., Perez, I., Palau, C., & Esteve, M. (2017). Technologies of internet of things applied to an earthquake early warning system. Future Generation Computer Systems, 75, 206–215.

Zeadally, S., Shaikh, F. K., Talpur, A., & Sheng, Q. Z. (2020). Design architectures for energy harvesting in the Internet of Things. Renewable and Sustainable Energy Reviews, 128, 109901.

DOI

https://doi.org/10.21107/rekayasa.v17i3.25428

Metrics

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Arsyad Cahya Subrata

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.