Aquaponics offers a sustainable approach to agriculture by integrating aquaculture and hydroponics, using fish

waste as nutrients for plant growth and plants as natural filters for water recirculation. Despite its ecological

advantages, maintaining optimal environmental conditions within aquaponic systems remains a significant

system achieved a SUS score of 77.11%, indicating a "Good" usability rating. Sensor data was successfully

transmitted at two-minute intervals, with real-time alerts triggered when thresholds were exceeded. The results

demonstrate that the proposed system is not only technically feasible and user-friendly but also contributes to

sustainable agriculture by reducing manual labor and enabling proactive intervention. The study supports the

adoption of IoT in small- to medium-scale aquaponic farms, aligning with global efforts toward SDG 2 (Zero

Hunger), SDG 6 (Clean Water and Sanitation), and SDG 12 (Responsible Consumption and Production).

In recent years, the combination of population growth and environmental concerns led to a substantial expansion

of research aiming to address global food security challenges [1, 2, 3]. The increasing demand for water

sustainability and productivity [37], [38], [39].

Aquaponics is a sustainable agricultural method that integrates aquaculture and hydroponics [4]. It represents a

closed loop system in food production. In this system, fish are fed and raised in tanks where they produce waste

rich in ammonia (NH4) which is harmful to the fish. The water containing this waste is then pumped into a grow

bed where plants, typically leafy greens, and herbs, are cultivated. Beneficial bacteria that are present in the grow

bed act as a catalyst [5, 6] to establish a self-sustaining ecosystem which converts the ammonia into nitrates

(NO3) [7]. This process serves essential nutrients for plants. As the plants absorb these nutrients, they act as a

natural filter that purifies the water, which can then be returned to the fish tanks. This cycle, shown in Figure 1,

creates a self-sustaining ecosystem where both the fish and plants thrive. This also eliminates any introduction

of any chemical-based substance which can be harmful to the environment, as is the case for hydroponics [8].

In response to the growing significance of aquaponics, this paper explores the design and implementation of an

Internet of Things (IoT) based monitoring system that maximizes the productivity of aquaponic systems. With a

focus on real-time parameter monitoring of water temperature, pH levels, and water level, the system aims to

provide valuable insights into the dynamic interactions within the aquaponic ecosystem for proactive

management and optimization.

Moreover, aquaponics aligns with several United Nations Sustainable Development Goals (SDGs), particularly

SDG 2: Zero Hunger, SDG 6: Clean Water and Sanitation, and SDG 12: Responsible Consumption and

Production. By integrating IoT technologies into aquaponics, this work does not only address the technological

challenges of modern agriculture but also contributes to the creation of more sustainable, efficient, and resilient

food systems, especially in urban and resource-constrained environments.

tools into agriculture can enhance food security and economic resilience among underserved farming

communities [36].

Fig. 1 A cycle in an aquaponic system

As outlined in Figure 1, an aquaponic system requires a balanced interaction between its components, which can

be achieved through monitoring the encompassing environmental conditions. The main parameters that define

an aquaponic ecosystem are as follows: pH, temperature, Dissolved Oxygen (DO), Electrical Conductivity (EC),

Ammonia (NH4), Nitrite (NO2-) and Nitrate (NO3-) [11]. Each one of these parameters plays a pivotal role in

maintaining optimal conditions for the health and growth of both aquatic species and plants within the system

and significant deviation in any of them will lead to a failure of the system.

the system, as different fish and plant species thrive under specific pH conditions. The suitable pH range for the

growth and survival of plants and fish inside the system is between 6.5-8 [12], with the nitrification process

range of 22°C to 32°C is essential for ensuring the well-being of both fish and plants [16]. Although an aquaponic

system can tolerate a temperature range of 15°C to 35°C [10], it is best to keep the water temperature at an

average of 26 °C, which ensures a balance between the fish and plants populations [17]. Finally, Electrical

Conductivity (EC) expressed as the concentration of dissolved ions in the water and influenced by the

concentration of dissolved salts and minerals, is a measure of the water's ability to conduct electricity [11] The

optimum EC range for fish is 100-2000 µS/cm, but the ecosystem can function within a wider range (30-5000

µS/cm) [18]. Polluted water will have higher levels of EC indicate and may cause death to the fish population

[13].

A considerable amount of literature has been published on IoT-based aquaponic monitoring systems with

power usage [26]. The relayed information being displayed to the users are usually privately hosted with their

own database [10, 20, 23] or on an IoT platform such as Blynk [19, 27], Favoriot [12] or Amazon Web Services

(AWS) [6, 21] to provide tools and services to facilitate the development, deployment, and management of IoT

applications. In rural areas and off-grid situations, integrating solar power for aquaponics monitoring system

was also considered [28]. In addition, Artificial Intelligence (AI) and machine learning (ML) were included in

the ecosystem to optimize water treatment and monitoring applications [25], data visualization tools and smart

health monitoring [29] and aquaponics yield estimation [30]. Table 1 shows a summary of previous work that

has used microcontrollers in the aquaponic monitoring system.

TABLE I: Summary of the previous work in aquaponicmonitoring system with IoT

of aquaponic environments in while being cost-effective. This is done by monitoring basic important parameters

which are water temperature, water levels and pH levels. Similar to other IoT-enabled systems using ESP32 or

sensor, HC-SR04 ultrasonic sensor and a liquid pH value detection sensor with electrode probe. The hardware

design circuit is shown in Figure 2. ESP32 which acts as a microcontroller, is used to connect and collect data

from sensors measuring pH, water level, temperature, and humidity. The data is sent to a local database where it

will be stored and displayed on a website, as well as compared to a set threshold to determine whether the current

conditions are within a safe range.

Figure 3 shows the prototype of the aquaponic monitoring system being tested in a real environment. Once the

ESP32 microcontroller is powered, all sensors will start the monitoring process immediately. The data will be

sent to a database every two minutes.

Fig. 3 Testing the prototype of aquaponic monitoring system

The test phase comprises performance testing and system usability testing. During the performance testing, the

IoT-based monitoring system is used to capture the readings of the various sensors and configurations to

determine its accuracy and reliability in monitoring an aquaponic system. For the system usability testing, 19

aquaponics farmers and users were asked to evaluate the system to assess its effectiveness, efficiency, and user

satisfaction.

dashboard is provided in Figure 4.

find the system easy to use and are satisfied with its functionality.

Compared to [12], which utilized Favoriot and did not implement real-time alerts or usability evaluation, the

proposed system integrates Telegram messaging, providing timely alerts when sensor readings exceed safe

Another notable contribution is the inclusion of usability testing using the System Usability Scale (SUS). The

score of 77.11% places the system within the "Good" usability rating, indicating a high level of user satisfaction.

This is particularly relevant for aquaponic farmers who may not be technologically savvy and require intuitive

interfaces.

In summary, the proposed system makes the following contributions:

works that used proprietary platforms without notification mechanisms or usability testing [6, 12, 19], our system