REVOLUTIONIZING AQUAPONICS MANAGEMENT: INTEGRATING IOT FOR WATER QUALITY CONTROL

Abstract

Aquaponics systems have emerged as an innovative and sustainable approach that interconnects recirculating aquaculture and hydroponics, synergizing their benefits. This integration capitalizes on the nutrient-rich effluents generated within the aquaculture environment, which traditionally accumulate to hazardous levels for aquatic life. However, in the context of aquaponics, these effluents are repurposed as potent liquid fertilizers, nurturing plant growth and thereby mitigating the accumulation of toxins [1]. Concurrently, the rapid evolution of the Internet of Things (IoT) technology has unveiled a global network of interconnected devices, machines, and sensors, engendering autonomous interactions and seamless data exchange [2]. Capitalizing on IoT, the present study orchestrates an Automated Aquaponic System empowered by smart sensors and microcontrollers. By continuously monitoring crucial parameters, the system provides real-time insights through a user-friendly graphical interface, transcending spatial limitations.
In this paper, we delve into the necessity of maintaining optimal water quality within aquaponic environments, elucidating conventional methods employed for water quality assessment [4]. Leveraging the potential of IoT, Section 3 introduces the paradigm of automated aquaponics, wherein a microcontroller collects and transmits data to a web repository. Subsequently, data processing triggers corresponding actuators to ensure an equilibrium of environmental parameters, thus warranting sustained system health and productivity [4]. The culmination of these efforts is realized in a dedicated mobile application and web interface, seamlessly providing users with real-time data insights and manual control over actuators.
The subsequent sections of this paper are structured as follows: Section 2 illuminates the imperative of maintaining optimal water quality in aquaponics and elucidates conventional methods for assessing pertinent water quality parameters. Section 3 expounds on the conceptual framework and technological underpinnings of the proposed automated aquaponics system. Section 4 extrapolates the implications of water quality assessment techniques within this automated context. Finally, Section 5 encapsulates the study's findings, offering insights into vital considerations when conceptualizing and implementing an automated aquaponics system. Ultimately, this research advances our understanding of sustainable aquaponic practices while harnessing the transformative potential of IoT for enhanced system performance and ecological equilibrium.