Sustainable Smart Aquaponics Farming Using IoT and Data Analytics

B. Paul, Shubham Agnihotri, B. Kavya, Prachi Tripathi, C. Babu
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Abstract

Traditional agriculture is facing numerous serious issues such as climate variation, population rise, water scarcity, soil degradation, and food security and many more. Though, Aquaponics is a promising solution, research on building an economically feasible smart Aquaponics system is still a challenge. In this paper, a sustainable smart Aquaponics system using Internet of Things (IOT) and Data Analytics is proposed. The acquired data from sensors such as Ph sensor, and temperature sensor, is analyzed using machine learning techniques to interpret the health of the system. Further, the proposed system includes automated fish feeder which is controlled by Raspberry Pi to automate and reduce the maintenance issues. The android application helps the user to remotely control and monitor the health of the system and also track the critical system parameters. Further the system is driven by the solar power to make it sustainable. A comprehensive survey on the key aspects of Aquaponics including comparison of the proposed model with the traditional aquaponics model is also presented.
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利用物联网和数据分析的可持续智能水培农业
传统农业正面临着许多严重的问题,如气候变化、人口增长、水资源短缺、土壤退化和粮食安全等等。虽然鱼菜共生是一个很有前途的解决方案,但建立一个经济可行的智能鱼菜共生系统的研究仍然是一个挑战。本文提出了一种基于物联网(IOT)和数据分析的可持续智能鱼菜共生系统。从传感器(如Ph传感器和温度传感器)获取的数据使用机器学习技术进行分析,以解释系统的健康状况。此外,该系统还包括由树莓派控制的自动喂鱼器,以实现自动化并减少维护问题。android应用程序帮助用户远程控制和监控系统的健康状况,并跟踪关键的系统参数。此外,该系统由太阳能驱动,使其可持续发展。对鱼菜共生的关键方面进行了全面的调查,包括与传统鱼菜共生模型的比较。
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