An IoT-Based Aquaculture Monitoring System Using Firebase
Source abstract
Abstract
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.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Water Quality Monitoring Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (37)
Show source-provided references
1. BPS Statistics Indonesia, Statistical Yearbook of Indonesia 2022. Jakarta, Indonesia: BPS-Statistics Indonesia, 2022. [Online]. Available: https://www.bps.go.id/publication/2020/04/29/e9011b3155d45d70823c141f/statistik-indonesia-2020.html
2. Proteomics in fish health and aquaculture productivity management: Status and future perspectives10.1016/j.aquaculture.2022.739159 ↗
3. The behavior of catfish traders on the food safety perspective in Malang markets, Indonesia10.13057/biodiv/d230504 ↗
4. Hasan · Internet of Things A—Z: Technologies and Application · 2018 · 7
5. Water quality monitoring using physiochemical sensors
6. IoT based system for monitoring and control of industrial process using real-time firebase database
7. IoT-based smart monitoring and management system for fish farming10.11591/eei.v12i3.3365 ↗
8. Prototype of aquaculture using IoT technologies
9. Development of IoT based fish monitoring system for aquaculture10.32604/iasc.2022.021559 ↗
10. G. Fortino and P. Trunfio, Internet of Things Based on Smart Objects: Technology, Middleware, and Applications. Switzerland: Springer, 2014. [Online]. Available: https://link.springer.com/book/10.1007/978-3-319-00491-410.1007/978-3-319-00491-4 ↗
11. Internet of Thing (IoT) review of review: Bibliometric overview since its foundation10.1016/j.future.2023.01.016 ↗
12. Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities10.1016/j.eswa.2022.119456 ↗
13. A systematic review on energy efficiency in the Internet of Underwater Things (IoUT): Recent approaches and research gaps10.1016/j.jnca.2023.103594 ↗
14. The Internet of Things (IoT) in healthcare: Taking stock and moving forward10.1016/j.iot.2023.100721 ↗
15. Remote health monitoring using IoT-based smart wireless body area network10.32604/cmc.2021.014647 ↗
16. IoT-EMS: An Internet of Things based environment monitoring system in volunteer computing environment10.32604/iasc.2022.022833 ↗
17. Mobile application for agrotechnology systems using Internet of Things (IoT)
18. A systematic review of IoT technologies and their constituents for smart and sustainable agriculture applications10.1016/j.sciaf.2023.e01577 ↗
19. Internet of Things in aquaculture: A review of the challenges and potential solutions based on current and future trends
20. Development of smart aquaculture farm management system using IoT and AI-based surrogate models10.1016/j.jafr.2022.100357 ↗
21. Design of pH control system and water recirculation in aquaponic cultivation using mamdani fuzzy logic control
22. IoT based smart aquaculture system with automatic aerating and water quality monitoring
23. A low-cost AI buoy system for monitoring water quality at offshore aquaculture cages
24. Design and implementation of a smart seawater aquarium system based on Artificial Intelligence of Things technology10.1109/JSEN.2022.3200958 ↗
25. Development of Iot monitoring system for aquaculture application
26. Rizvi · Microcontroller Programming—An Introduction · 2012 · 204
27. Tiny machine learning for resource-constrained microcontrollers10.1155/2022/7437023 ↗
28. Low-cost arduino controlled dual-polarity high voltage power supply10.1016/j.ohx.2022.e00382 ↗
29. Development of android app-based portable water quality testing device using arduino
30. Technologies driving the shift to smart farming: A review10.1109/JSEN.2022.3225183 ↗
31. Machine learning for microcontroller-class hardware: A review10.1109/JSEN.2022.3210773 ↗
32. GAN-AE: An unsupervised intrusion detection system for MQTT networks10.1016/j.engappai.2022.105805 ↗
33. Characterization of turbidity water sensor SEN0189 on the changes of total suspended solids in the water
34. Arduino based system for domestic waste water management using pH sensor
35. Cloud computing: Google firebase firestore optimization analysis10.11591/ijeecs.v29.i3.pp1719-1728 ↗
36. What do firebase developers discuss about? An empirical study on stack overflow posts
37. Enhancement of embedded controller firebase database labview interactive IoT based production natural parameters monitoring