Aquaculture Resilience: Empowering Food Security through IoT Based People's Farm Robots
Abstract
The COVID-19 pandemic starkly revealed the vulnerability of global food systems, prompting a pressing call for sustainable and resilient practices. This conceptual paper forms an integral part of a comprehensive study aimed at investigating the pivotal role of technological and sustainable solutions in surmounting pandemic-induced challenges and attaining vital food security objectives. Specifically, this conceptual paper delves into the possibilities inherent in cloud-based management, robotics, and circular economy principles, focusing on their potential to bolster food security. To this end, the paper proposes the implementation of an ’IoT based Farm robot’ to enhance aquaculture resilience in Yogyakarta, Indonesia – an apt locale renowned for its vibrant community and agricultural traditions. Leveraging cloud technology, the paper explores the remote management and monitoring of fishponds, thereby optimizing resource utilization and elevating overall productivity. Through the integration of robotics, the automation and precision introduced to fish farming processes serve to lessen reliance on manual labor. Furthermore, the incorporation of circular economy principles underpins sustainable practices, minimizing waste and maximizing the efficiency of resources. By harnessing the synergy of cloud-based management, robotics, and circular economy principles, this conceptual paper introduces a solution that empowers local communities to both navigate the current pandemic crisis and foster enduring aquaculture resilience. The discourse presented within this paper holds valuable implications for policymakers, researchers, and practitioners invested in aquaculture and food security. Moreover, it contributes to the wider conversation concerning sustainable food systems, offering a pathway to cultivating a more secure and resilient future for aquaculture in Yogyakarta and beyond, even amidst pandemics and other disruptive occurrences.
Keywords: food security, post pandemic, fishpond, robot, cloud, IoT
References
[1] Adams JB, Whitfield AK, Van Niekerk L. A socio-ecological systems ap proach towards future research for the restoration, conservation and management of southern African estuaries. African Journal of Aquatic Science. 2020;45(1-2):231– 241.
[2] Arrahman, R. (2022). Rancang Bangun Pintu Gerbang Otomatis Menggunakan Arduino Uno R3. Jurnal Portal Data, 2(2).
[3] Bhatnagar A, Devi P. Water quality guidelines for the management of pond fish culture. International Journal of Environmental Science. 2013;3(6):1980–2009.
[4] Boyd CE. Water quality management for pond fish culture. Elsevier Scientific Pub lishing Co. 1982.
[5] Delincé G. The ecology of the fish pond ecosystem: with special reference to Africa. Volume 72. Springer Science & Business Media; 2013.
[6] Deng C, Gao Y, Gu J, Miao X, Li S. Research on the growth model of aquaculture organisms based on neural network expert system. In 2010 sixth international conference on natural computation (Vol. 4, pp. 1812-1815). IEEE. 2010 Aug. https://doi.org/10.1109/ICNC.2010.5584492
[7] Gondchawar N, Kawitkar RS. IoT based smart agriculture. International Journal of Advanced Research in Computer and Communication Engineering. 2016;5(6):838– 842.
[8] Israni S, Meharkure H, Yelore P. Application of IoT based system for advance agricultureing. 2015;3(11), 10831-10837.
[9] Kayalvizhi S, Reddy GK, Kumar PV, Prasanth NV. Cyber aqua culture monitoring system using Ardunio And Raspberry Pi. International Journal of Advanced Research in Electrical. Electronics and Instrumentation Engineering. 2015;4(5):4554–4558.
[10] Patil, K., Patil, S., Patil, S., & Patil, V. (2015). Monitoring of turbidity, pH & temperature of water based on GSM. International journal for research in emerging science and technology, 2(3), 16-21.
[11] Prapti DR, Mohamed Shariff AR, Che Man H, Ramli NM, Perumal T, Shariff M. Internet of Things (IoT)based aquaculture: an overview of IoT application on water quality monitoring. Rev Aquacult. 2022;14(2):979–92.
[12] Raju KR, Varma GH. (2017, January). Knowledge based real time monitoring system for aquaculture using IoT. In 2017 IEEE 7th international advance computing conference (IACC) (pp. 318-321). IEEE. https://doi.org/10.1109/IACC.2017.0075.
[13] Saha S, Rajib RH, Kabir S. (2018, October). IoT based automated fish farm aquacul ture monitoring system. In 2018 International Conference on Innovations in Science, Engineering and Technology (ICISET) (pp. 201-206). IEEE.
[14] Simbeye DS, Yang SF. Water quality monitoring and control for aquaculture based on wireless sensor networks. Journal of network. 2014;9(4):840.
[15] Thu Minh HV, Tri VP, Ut VN, Avtar R, Kumar P, Dang TT, et al. A model-based approach for improving surface water quality management in aquaculture using MIKE 11: a case of the Long Xuyen Quadangle, Mekong Delta, Vietnam. Water. 2022;14(3):412.
[16] Zhu HJ. Global fisheries development status and future trend analysis. Taiwan Eco nomic Research Monthly. 2010;33(3).