An IoT-Based Aquaculture Monitoring System Using Firebase

被引:3
作者
Sung, Wen-Tsai [1 ]
Isa, Indra Griha Tofik [1 ,2 ]
Hsiao, Sung-Jung [3 ]
机构
[1] Natl Chin Yi Univ Technol, Dept Elect Engn, Taichung 411030, Taiwan
[2] Politekn Negeri Sriwijaya, Dept Informat Management, Palembang 30139, Indonesia
[3] Takming Univ Sci & Technol, Dept Informat Technol, Taipei 11451, Taiwan
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2023年 / 76卷 / 02期
关键词
Internet of Things; aquaculture technology; water monitoring system; real-time database; aquaculture monitoring system;
D O I
10.32604/cmc.2023.041022
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Indonesia is a producer in the fisheries sector, with production reaching 14.8 million tons in 2022. The production potential of the fisheries sector can be optimally optimized through aquaculture management. One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions. IoT technology can be applied to support a fish pond aquaculture monitoring system, especially for catfish species (Siluriformes), in real-time and remotely. One of the technologies that can provide this convenience is the IoT. The problem of this study is how to integrate IoT devices with Firebase's cloud data system to provide reliable and precise data, which makes it easy for fish cultivators to monitor fishpond conditions in real time and remotely. The IoT aquaculture fishpond monitoring use 3 parameters: (1) water temperature; (2) pH water level; and (3) turbidity level of pond water. IoT devices use temperature sensors, pH sensors, and turbidity sensors, which are integrated with a microcontroller and Wi-Fi module. Data from sensor readings are sent to the Firebase cloud via the Wi-Fi module so that it can be accessed in real time by end users with an Android-based mobile app. The findings are (1) the IoT-based aquaculture monitoring system device has a low error rate in measuring temprature, pH, and turbidity with a percentage of 1.75%, 1.94% and 9.78%, respectively. Overall, the total average error of the three components is 4.49%; (2) in cost analysis, IoT-based has a cost-effectiveness of 94.21% compared to labor costs. An IoT-based aquaculture monitoring system using Firebase can be effectively used as a technology for monitoring fish pond conditions in real-time and remotely for fish cultivators that contribute to providing an IoT-based aquaculture monitoring system that produces valid data, is precise, is easy to implement, and is a low-cost system.
引用
收藏
页码:2179 / 2200
页数:22
相关论文
共 50 条
[21]   A Mobile IoT-based Elderly Monitoring System for Senior Safety [J].
Naeim, Mohamed Khaled Mohyeldin ;
Chung, Gwo Chin ;
Lee, It Ee ;
Tiang, Jun Jiat ;
Tan, Soo Fun .
INTERNATIONAL JOURNAL OF TECHNOLOGY, 2023, 14 (06) :1185-1195
[22]   IoT-Based Fish Farm Water Quality Monitoring System [J].
Chen, Chiung-Hsing ;
Wu, Yi-Chen ;
Zhang, Jia-Xiang ;
Chen, Ying-Hsiu .
SENSORS, 2022, 22 (17)
[23]   IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring [J].
Lin, Chin-Teng ;
Prasad, Mukesh ;
Chung, Chia-Hsin ;
Puthal, Deepak ;
El-Sayed, Hesham ;
Sankar, Sharmi ;
Wang, Yu-Kai ;
Singh, Jagendra ;
Sangaiah, Arun Kumar .
IEEE ACCESS, 2018, 6 :405-414
[24]   IoT-based continuous glucose monitoring system: A feasibility study [J].
Tuan Nguyen Gia ;
Ali, Mai ;
Ben Dhaou, Imed ;
Rahmani, Amir M. ;
Westerlund, Tomi ;
Liljeberg, Pasi ;
Tenhunen, Hannu .
8TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT-2017) AND THE 7TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT 2017), 2017, 109 :327-334
[25]   IoT-based system for monitoring conditions in an industrial painting booth [J].
Velasco-Hemandez, Gustavo ;
Mirani, Akseer Ali ;
Awasthi, Anshul ;
Walsh, Joseph .
2022 33RD IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC), 2022,
[26]   IoT-based patient monitoring system for predicting heart disease using deep learning [J].
Ramkumar, Govindaraj ;
Seetha, J. ;
Priyadarshini, R. ;
Gopila, M. ;
Saranya, G. .
MEASUREMENT, 2023, 218
[27]   An IoT-based wearable system using accelerometers and machine learning for fetal movement monitoring [J].
Zhao, Xin ;
Zeng, Xianyi ;
Koehl, Ludovic ;
Tartare, Guillaume ;
de Jonckheere, Julien ;
Song, Kehui .
2019 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL CYBER PHYSICAL SYSTEMS (ICPS 2019), 2019, :299-304
[28]   An IoT-Based Road Bridge Health Monitoring and Warning System [J].
Al-Ali, A. R. ;
Beheiry, Salwa ;
Alnabulsi, Ahmad ;
Obaid, Shahed ;
Mansoor, Noor ;
Odeh, Nada ;
Mostafa, Alaaeldin .
SENSORS, 2024, 24 (02)
[29]   An Anonymous IoT-Based E-Health Monitoring System Using Blockchain Technology [J].
Samuel, Omaji ;
Omojo, Akogwu Blessing ;
Mohsin, Syed Muhammad ;
Tiwari, Prayag ;
Gupta, Deepak ;
Band, Shahab S. .
IEEE SYSTEMS JOURNAL, 2023, 17 (02) :2422-2433
[30]   IoT-based risk monitoring system for safety management in warehouses [J].
Trab S. ;
Zouinkhi A. ;
Bajic E. ;
Abdelkrim M.N. ;
Chekir H. .
International Journal of Information and Communication Technology, 2018, 13 (04) :424-438