The development of an iot-based automated temperature and ph monitoring system to enhance the management of gourami fish ponds | [ARPN Journal of Engineering and Applied Sciences • 2024]

Author(s):

1. Muthmainnah: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

2. Muhammad Farid Nashirudin: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

3. Wiwis Sasmitaninghidayah: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

4. Ninik Chamidah: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

5. Agus Mulyono: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

6. Imam Tazi: Department of Physics, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim,Malang,Indonesia

Abstract:

This research aims to develop an Internet of Things (IoT)-based automated system for monitoring temperature and pH in the context of gourami fish farming. Gourami fish ponds are often situated in various environments with significant variations in environmental conditions. The system is designed to enable pond owners to remotely monitor real-time water temperature and pH, which are key factors in maintaining optimal water quality and fish health. The temperature sensor used is the DS18B20, while the pH sensor used is the E210C. The ESP32 platform is employed due to its integrated Wi-Fi capabilities. Monitoring displays are accessible on an LCD, personal computer (PC), and smartphone. This research involves the calibration and validation of temperature and pH sensors to ensure accurate measurements. The average standard deviation value for the temperature sensor is 0.092, and for the pH sensor, it is 0.031. The average accuracy of the temperature sensor is 98.60%, while the pH sensor has an average accuracy of 98.41%. The results demonstrate that IoT based temperature and pH monitoring allow for in-depth data analysis of environmental conditions and long-term trend analysis in pond management.

Page(s): 294-300

DOI: DOI not available

Published: Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 5, Year: 2024

Keywords:

temperature , pH , monitoring , IoT , gourami farming

References:

[1] Prayogo N. A.,Siregar A. S.,Sukardi P.,Bessho Y. .1801 .) under photoperiod manipulations. Biodiversitas, 21(4) : 1365-1372.

[2] Sudana I. W. .2020 .Analysis of Income and Marketing Efficiency of Gouramy in Yeh Embang Kangin Jembrana Village. SEAS (Sustainable Environ. Agric. Sci., 4(2) : 111-119.

[3] Yanuhar U.,Musa M.,Evanuarini H.,Wuragil D. K.,Permata F. S. .2022 .Water Quality in Koi Fish (Cyprinus carpio) Concrete Ponds with Filtration in Nglegok District, Blitar Regency. Univers. J. Agric. Res., 100619(6) : 814-820.

[4] Lastauskienė E. .2021 .The Impact of Intensive Fish Farming on Pond Sediment Microbiome and Antibiotic Resistance Gene Composition. , 673756 : 1-12.

[5] Kampczyk A.,Dybel K. .2021 .The Fundamental Approach of the Digital Twin Application in Railway Turnouts with Innovative Monitoring of Weather Conditions. , 21(5757) : 1-14.

[6] Chuang C. H.,Huang C. W.,Chang K. Y. .2023 .Associations of anomalous water temperature, salinity, and pH with change in water color of fish farming ponds. J. World Aquac. Soc., : 1-12.

[7] Subhan R. Y.,Hartono D. P. .2022 .Growth Performance of Giant Gouramy (Osphronemus gouramy) In Pre-Enlargement Phase with Different Temperature. Asian J. Aquat. Sci., 5(1) : 96-104.

[8] Andriyono S.,Fitrani M. .2021 .Non-native species existence and its potency to be invasive species on freshwater ecosystem in East Java province. Indonesia. Egypt. J. Aquat. Biol. Fish, 170621(2) : 1013-1024.

[9] Priyanka R.,Reji M. .2019 .IOT based health monitoring system using blynk app. Int. J. Eng. Adv. Technol., 8(6) : 78-81.

[10] Hutabarat D. P.,Susanto R.,Prasetya B.,Linando B.,Arosha S. M. N. .2022 .Smart system for maintaining aquascape environment using internet of things based light and temperature controller. Int. J. Electr. Comput. Eng., 12(1) : pp896-902.

[11] Prahasanti C.,Romadhona W. R.,Dinaryanti A.,Airlangga U.,Indonesia S. .2020 .Viability Test of Collagen Extract from Gouramy Scale (Oshpronemusgouramy) on Bone Marrow Mesenchymal Stem Cell Culture. Medico-Legal Updat. , 20(4) : 1786-153.

[12] Zhang Z.,Peng K.,Wu Z.,Ling Z.,Li Z.,Sci Z. .2023 .Assessment of the impact of wetland changes on carbon storage in coastal urban agglomerations from 1990 to 2035 in support of SDG15.1. Total Environ, 162824 : .

[13] Hong W. J. .2021 .Water quality monitoring with arduino based sensors. Environ. - MDPI, 8(1) : 1-15.

[14] Obata K.,Schwarze M.,Schomäcker R.,Abdi F. F. .2020 .In situ observation of pH change during water splitting in neutral pH conditions: Impact of natural convection driven by. , : .

[15] Li Y.,Xu J.,Wright A.,Qiu C.,Wang C.,Liu H. .2021 .Integrating two aspects analysis of hydrological connectivity based on structure and process to support muddy coastal restoration. Ecol, 108416 : .

[16] Chou R. J.,Huang F. T. .2021 .Building community resilience via developing community capital toward sustainability: Experiences from a hakka settlement in Taiwan. Int. J. Environ. Res. Public Health, 18(17) : .

[17] Capocefalo A. .2019 .Exploring the potentiality of a SERS-active pH nano-biosensor. Front. Chem, 00413 : 1-11.

[18] Medina-Bailon C. .2021 .Comprehensive analytical modelling of an absolute pH sensor. Sensors, 21(15) : 1-14.

[19] Elyounsi A.,Kalashnikov A. N. .2021 .Evaluating Suitability of a DS18B20 Temperature Sensor for Use in an Accurate Air Temperature Distribution Measurement Network †. Eng. Proc., 10(1) : .

[20] Saha Ramesh,Biswas S.,Sarmah S.,Karmakar S.,Das P. .2021 .A Working Prototype Using DS18B20 Temperature Sensor and Arduino for Health Monitoring. SN Comput. Sci., 2(1) : 1-21.

[21] Wang T. .2020 .A dynamic temperature difference control recording system in shallow Lake Mesocosm. Methods X, 100930 : 100930.

[22] Mu B.,Cao G.,Zhang L.,Zou Y.,Xiao X. .2021 .Flexible wireless pH sensor system for fish monitoring. Sens. Bio-Sensing Res., 100465 : .

[23] Saikat M. .2021 .IoT and Wireless Sensor Networking-based Effluent Treatment Plant Monitoring System. , : .

[24] Pagano A.,Croce D.,Vitale G. .2022 .A Survey on LoRa for Smart Agriculture: Current Trends and Future Perspectives. , 3230505(4) : 3664-3679.

[25] Evett S. R.,Marek G. W.,Colaizzi P. D.,Brauer D. K.,A. O'Shaughnessy D. K. .2019 .CWP as affected by irrigation application method: SDI versus midelevation spray irrigation. Trans. ASABE, 62(5) : 1377-1393.

[26] Muthmainnah M.,Bako T. Deni,Tazi Imam .2022 .Karakterisasi Sensor MAX30102 Sebagai Alat Ukur Detak Jantung dan Suhu Tubuh Berbasis Photoplethysmograph. J. Pendidik. MIPA, 12(3) : 655-731.

[27] M. Le Page L.,Jarlan L.,M. M. El Hajj M.,Zribi N.,Baghdadi A.,Boone A. .2020 .Potential for the detection of irrigation events on maize plots using Sentinel-1 soil moisture products. Remote Sens, 12(10) : .

[28] Zarski J.,Kuśmierek-Tomaszewska R.,Dudek S. .2020 .Impact of irrigation and fertigation on the yield and quality of sugar beet (Beta vulgaris L.) in a moderate climate. Agronomy, 10(2) : .

[29] Kumar Jha S. .2019 .Response of growth, yield and water use efficiency of winter wheat to different irrigation methods and scheduling in North China Plain. , 03 : 292-302.

[30] Almalki F. A.,Soufiene B. O.,Alsamhi S. H.,Sakli H. .2021 .A low-cost platform for environmental smart farming monitoring system based on iot and uavs. , 13(11) : .

[31] Valentín F. .2020 .Comparing evapotranspiration and yield performance of maize under sprinkler, superficial and subsurface drip irrigation in a semiarid environment. Irrig. Sci., 38(1) : 105-115.

[32] Saad A.,Benyamina A. E. H.,Gamatie A. .2020 .Water Management in Agriculture: A Survey on Current Challenges and Technological Solutions. IEEE Access, 2974977 : 38082-38097.

[33] Montoya A. P.,Obando F. A.,Osorio J. A.,Morales J. G.,Kacira M. .2020 .Design and implementation of a low-cost sensor network to monitor environmental and agronomic variables in a plant factory. Comput. Electron. Agric., 105758 : .

[34] Campos N. G. S.,Rocha A. R.,Gondim R.,Gomes D. G. .2020 .Smart & green: An internet-of-things framework for smart irrigation. Sensors (Switzerland), 20(1) : .

[35] Carbajal Morán H.,Márquez J. F.,Camarena J. F.,Quiñones R. H. Z.,Vílchez E. E. D. la C. .2021 .Monitoring the hydrogen potential of a river in the central andes of peru from the cloud. Ecol. Eng. Environ. Technol., 22(6) : 17-26.

[36] Soeprapto H.,Ariadi H.,Badrudin U. .2023 .The dynamics of Chlorella spp. abundance and its relationship with water quality parameters in intensive shrimp ponds. Biodiversitas, 24(5) : 2919-2926.

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