On the Study and Analysis of Automated Aquaponics System Using AVR Microcontroller

Alka Sathyan*, Senthil Arumugam Muthukumaraswamy, Habibur Rahman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

With exponential increases in population, the need for water has equally gone up. Water resources are rapidly drying up, whether it is used for drinking or agricultural and industrial purposes. The main aim is to study aquaponics systems that would efficiently use water and analyze methods of monitoring and controlling the parameters concerning water quality. This paper focuses on the study and analysis of different techniques to enhance aquaponics systems’ efficiency through IoT-supported automation techniques. AVR microcontroller is interfaced with aquaponics systems through IoT to obtain readings to monitor the system parameters remotely. With this automation process, it can be more convenient to maintain an environment optimal for both the plants and fish. The results reveal methods used to balance the water quality conditions and how automation increases system efficiency.

Original languageEnglish
Title of host publicationIntelligent Manufacturing and Energy Sustainability
EditorsA. N. Reddy, Deepak Marla, Margarita N. Favorskaya, Suresh Chandra Satapathy
PublisherSpringer
Chapter51
Pages519-528
Number of pages10
ISBN (Electronic)9789811664823
ISBN (Print)9789811664816
DOIs
Publication statusPublished - 2022
EventInternational Conference on Intelligent Manufacturing and Energy Sustainability 2021 - Hyderabad, India
Duration: 18 Jun 202119 Jun 2021

Publication series

NameSmart Innovation, Systems and Technologies
Volume265
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

ConferenceInternational Conference on Intelligent Manufacturing and Energy Sustainability 2021
Abbreviated titleICIMES 2021
Country/TerritoryIndia
CityHyderabad
Period18/06/2119/06/21

Keywords

  • Aquaponics
  • Automation
  • AVR microcontroller
  • IoT

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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