IoT System on Dynamic Fish Feeder Based on Fish Existence for Agriculture Aquaponic Breeders

Main Article Content

Murizah Kassim
https://orcid.org/0000-0002-8494-4783
Muhammad Zulhelmi Zulkifli
Assoc. Prof. Ir, Ts. Dr. Norsuzila Ya'acob
Ir. Dr. Shahrani Shahbudin

Abstract

Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed hardware. The controller controls the feeding and feedback mechanism based on attached sensors. An ultrasonic sensor is programmed with the controller to detect the level of food and waterproof ultrasonic to detect existing fish. The humidity sensor was used to measure the humidity in the food container to control the food freshness. Two servo motors were used to move the waterproof sensor to attract the fish and to dispense the food to the fish when existed. The result presents four measured levels that are the temperature of the food container, the quality of food based on humidity measured, fish detection counter and level of fish food in the container. Data analytics on all the measured levels was presented on the ThingSpeak platform by using Blynk to get data collections from all sensors. This research is significant for fish breeders that support IR4.0 system connected online and mobile apps which also contribute to today’s agriculture.

Downloads

Download data is not yet available.

Article Details

How to Cite
1.
Kassim M, Zulkifli MZ, Ya’acob N, Shahbudin S. IoT System on Dynamic Fish Feeder Based on Fish Existence for Agriculture Aquaponic Breeders. Baghdad Sci.J [Internet]. 2021 Dec. 20 [cited 2022 Nov. 30];18(4(Suppl.):1448. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6672
Section
article

References

Kaushik N, Bagga T. Internet of things (IOT): Applications, implications & green IOT in agriculture. JGE 2020;10(12):12885-900.

Albu-Salih AT, Seno SAH. Optimal UAV deployment for data collection in deadline-based IoT applications. Baghdad Sci. J.. 2018;15(4):484-91.

Busaeri N, Hiron N, Andang A, Taufiqurrahman I, editors. Design and Prototyping the Automatic Fish Feeder Machine for Low Energy. ICSECC 2019 - International Conference on Sustainable Engineering and Creative Computing: New Idea, New Innovation, Proceedings; 2019.

Ismail NL, Kassim M, Ismail M, Mohamad R. A review of low power wide area technology in licensed and unlicensed spectrum for IoT use cases. BEEI. 2018;7(2):183-90.

Othman NA, Damanhuri NS, Syafiq Mazalan MA, Shamsuddin SA, Abbas MH, Chiew Meng BC. Automated water quality monitoring system development via LabVIEW for aquaculture industry (Tilapia) in Malaysia. IJEECS. 2020;20(2):805-12.

Kasda, Kosasih DP, Nugraha HD, Rachman M. Low-cost remote control barge boat to feeder fish. JMERD. 2021;44(2):112-21.

Zhao Z, Xu Q, Luo L, Qiao G, Wang L, Li J, et al. Effect of bio-floc on water quality and the production performance of bottom and filter feeder carp fed with different protein levels in a pond polyculture system. Aquac. 2021;531.

Yasin MNM, Hamzah MMAM, Kassim M, Arbain N. Freshwater ph level control and gui system for prawn breeding. IJATCSE. 2020;9(4):5887-93.

Ismail F, Gryzagoridis J, editors. Sustainable development using renewable energy to boost aquaponics food production in needy communities. Proceedings of the Conference on the Industrial and Commercial Use of Energy, ICUE; 2016.

Alzubi HS, Al-Nuaimy W, Buckley J, Young I, editors. An intelligent behavior-based fish feeding system. 13th International Multi-Conference on Systems, Signals and Devices, SSD 2016; 2016.

Haryanto, Ulum M, Ibadillah AF, Alfita R, Aji K, Rizkyandi R, editors. Smart aquaponic system based Internet of Things (IoT). JPCS; 2019.

Abdulzahra SA, Al-Qurabat AKM, Idrees AK. Compression-based data reduction technique for IoT sensor networks. Baghdad Sci. J. 2021;18(1):184-98.

Noor MZH, Hussian AK, Saaid MF, Ali MSAM, Zolkapli M, editors. The design and development of automatic fish feeder system using PIC microcontroller. Proceedings - 2012 IEEE Control and System Graduate Research Colloquium, ICSGRC 2012; 2012.

Jaafar A, Kassim M, Haroswati CK, Yahya CK, editors. Dynamic home automation security (DyHAS) alert system with laser interfaces on webpages and windows mobile using rasberry PI. 2016 7th IEEE Control and System Graduate Research Colloquium, ICSGRC 2016 - Proceeding; 2017.

Li L, Hong J, editors. Identification of fish species based on image processing and statistical analysis research. 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014; 2014.

Hashim AS, Grămescu B, Cartal AL, Niţu C. Modeling and identification of a high resolution servo, for mobile robotics. U.P.B. Sci. Bull., Series D. 2020;82(2):27-38.

Kassim M, Haroswati CK, Yahaya CK, Ismail MN, editors. A prototype of Web Based Temperature Monitoring system. ICETC 2010 - 2010 2nd International Conference on Education Technology and Computer; 2010.

Noar NAZM, Kamal MM, editors. The development of smart flood monitoring system using ultrasonic sensor with blynk applications. 2017 IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2017; 2018.

Hema LK, Velmurugan S, Sunil DN, Thariq Aziz S, Thirunavkarasu S, editors. IOT based real-time control and monitoring system for food grain procurement and storage. IOP Conf. Ser: Mater. Sci. Eng; 2020.

Prafanto A, Budiman E, editors. A Water Level Detection: IoT Platform Based on Wireless Sensor Network. Proceedings - 2nd East Indonesia Conference on Computer and Information Technology: Internet of Things for Industry, EIConCIT 2018; 2018.

Toh YH, Ng TM, Liew BK, editors. Automated fish counting using image processing. Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009; 2009.