IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

— Cultivation of tiger prawns stands as a crucial sector in Indonesia's fisheries industry, significantly contributing to the country's foreign exchange. However, challenges persist in the cultivation process, particularly concerning suboptimal harvest outcomes. A critical factor in tiger prawn cultivation is the water temperature within shrimp ponds, a parameter directly influencing shrimp growth. The recommended normal temperature range is 28-31°C. Deviations from this range can adversely impact the shrimp's metabolic system and appetite, resulting in stress and potential mortality. Temperature fluctuations can lead to severe issues such as hindered growth, reduced productivity, and increased shrimp mortality. Real-time monitoring of air temperature emerges as a pivotal element in ensuring the success of shrimp farming. This research aims to provide a practical solution for shrimp cultivation by presenting a system that enables farmers to adjust air temperature in ponds in real-time through a user-friendly website application. The ability to promptly respond to abnormal temperature fluctuations empowers farmers to optimize cultivation conditions, thereby reducing shrimp mortality rates. The research focuses on creating a water temperature monitoring system for tiger prawn ponds using cloud storage through the Firebase platform. By implementing real-time temperature monitoring, financial risks for shrimp farmers can be mitigated, preventing losses attributed to temperature-induced shrimp mortality. The research utilizes the DS18B20 temperature sensor and WeMos D1 R2 as the control center. The website displays air temperature measurements, showcasing a high accuracy of 99% with a minimal error of 1.2%. This underscores the system's effectiveness in measuring air temperature both above and below the pond. The incorporation of IoT technology for monitoring water quality in ponds offers a practical and innovative approach to tiger prawn cultivation, with the potential to enhance production outcomes in each harvest.


INTRODUCTION
Cultivation of tiger shrimp is one of the most crucial aquaculture sectors in Indonesia.This cultivation significantly contributes to the national economy and coastal areas such as Pinrang Regency [1] [2].The economic contribution of shrimp cultivation encompasses the value of shrimp production, shrimp exports, and employment in this sector.Increasing shrimp production can enhance regional and national income.One of the primary challenges in cultivating tiger prawns is maintaining pond environmental conditions, including water temperature, within the optimal range of 28-31°C [3].
Inappropriate water temperatures can have adverse effects on shrimp growth and health.The primary challenge is the unpredictability of temperature fluctuations, especially during seasonal changes or extreme weather events.This can induce stress in shrimp and may lead to mortality if not managed properly.Furthermore, shrimp farming faces challenges contributing to crop failure, such as shrimp diseases, irregular water quality management, unstable variations in pond water temperature, environmental pollution, and other issues.Particularly concerning fluctuations in pond water temperature, real-time water temperature monitoring is crucial to address this concern [4].One proposed solution to prevent crop failure arising from unstable shrimp pond temperatures is the application of Internet of Things (IoT) technology for continuous monitoring of pond water conditions [5]- [12].The adoption of IoT-based monitoring facilitates enhanced control for farmers over pond water conditions [13].In instances of deviations from standard water temperatures, such as an increase above the defined threshold or excessively cold temperatures [14], farmers can implement corrective measures to stabilize water temperatures, such as activating water wheels or replacing water within the pond plot.
The automation of pond water conditions monitoring in shrimp or fish farming has extensively incorporated Internet of Things (IoT) technology [15]- [22].Previous studies include the development of a water condition monitoring device for fish farming using Arduino [23], [24] through a web interface [25]- [29] Another study focused on monitoring shrimp pond water conditions using an Android mobile application [30]- [34] based on WSN [35]- [41].Furthermore, research on monitoring temperature and pH levels in vannamei shrimp pond water [7] utilized DS18B20 sensors with an interface for pond water monitoring through a smartphone.Additionally, research on salinity, oxygen  [6], [42].Supporting studies encompass the application of IoT technology in agricultural waste management [43] and soil humidity monitoring in chili cultivation [44].
Although previous research has contributed to the development of monitoring systems in the fisheries and agriculture sectors [40], [45]- [51], there is still a need for further development, particularly the implementation of IoT in shrimp pond with soil construction.The soil-constructed land poses challenges, especially in hot or rainy weather, which can impact the resilience of the electronic components used, and the pond water conditions can change drastically based on the surrounding environment [52].It is necessary to conduct testing for the implementation of IoT technology in these soil-constructed areas, especially in measuring pond water temperature.Changes in pond water temperature are highly influenced by the weather conditions at the pond location.Another challenge in shrimp pond with soil construction is the occurrence of corrosion on electronic devices, which can affect the quality of sensors in conducting measurements.These conditions pose a challenge in the implementation of IoT technology in outdoor environments, especially in traditional shrimp pond.
The proposed research utilizes the WeMos D1 R1 microcontroller, an integrated IoT component with Wi-Fi capabilities [53] for communication with a modem as a data transmission medium to a cloud server [51], [54]- [56].This research also uses the DS18B20 sensor as a component that can provide real-time information on pond water temperature conditions [12].In this research, cloud technology based on Firebase is combined with a Virtual Private Server (VPS) for data storage [57].The cloud data storage is not solely focused on Firebase; instead, data obtained from the sensor will be received by Firebase and subsequently stored in the VPS using the MySQL database management system (DBMS) [51].The aim of this research is to assess the accuracy of the IoT device in measuring pond water temperature and to conduct real-time monitoring processes using smartphones and desktop computers.This study contributes to the control of traditional pond water conditions, enabling farmers to take preventive measures promptly in the event of changes in water temperature that may affect tiger shrimp cultivation.

A. Research Stages
This research uses several important stages which are carried out in stages.The process initiates with 1) Device Preparation, 2) System Analysis, 3) System Design, 4) System Testing, 5) Implementation.Specific details for each stage are elucidated in Fig. 1.
Device Preparation: This stage involves the preparatory measures for devices, commencing with input devices like the DS18B20 water temperature sensor.Subsequently, processing devices, specifically the WeMos D1 R1, along with the MiFI Modem serving as the Gateway, are configured to act as a pivotal intermediary facilitating communication between the microcontroller device and the cloud server.
System Analysis: In this stage, the analysis commences by scrutinizing the data or information acquired during the data collection phase through a comprehensive literature review concerning the implementation of IoT technology for monitoring pond water temperature in shrimp farming.

System Design:
The design of the system commences based on the collected data, incorporating the implementation of the DS18B20 sensor-based WeMos D1 R2.Activities in this stage involve creating a block diagram, a system flowchart, and schematic diagrams.Additionally, it includes the development of the equipment box design, which will be implemented in traditional shrimp ponds.
System Testing: The system testing is conducted in the laboratory.Testing is performed using samples of pond water placed in a container, with the IoT device positioned on top of the container.The IoT device is then activated to determine its functionality.Sensor testing is carried out by comparing the IoT device with a standard water temperature measuring instrument.

Implementation:
In this phase, the device is deployed at the location of the shrimp pond with soil construction.The protective material for the device is designed using acrylic and coated with Styrofoam to enable the device to float on the surface of the pond water.During this stage, field trials are conducted at the pond location, and water temperature data is collected.Subsequently, the accuracy of the IoT device is tested using a standard water temperature measuring instrument.This is done to determine the error value of the sensor measurements.

System Analysis:
Initial analysis processes such as data collection for research

System Design:
This process involves the documentation creation for the tool.

System Testing:
This process involves testing the tool on a laboratory scale

Implementation:
This process involves implementing the tool at the pond location This water quality information can be used by farmers to ensure optimal growth and health for shrimp.Government officials can use this data to manage aquatic resources and make policy decisions based on actual conditions in the shrimp farming industry.Academics have access to data that can be used for scientific research in the fields of aquaculture and the environment.They can analyze long-term trends, understand the impact of environmental change on shrimp farms, and contribute to scientific knowledge.Exporters can use this information to ensure the quality of shrimp farm products before export.This involves monitoring water conditions to ensure compliance with international standards required for export.

C. Schematic Diagram and Illustration Sensor Data Transmission
This research utilizes several devices in the design process of IoT technology for tiger prawn ponds, including WeMos D1 R2, DS18B20 sensor, jumper cables, and the use of a Portable Wi-Fi.All these IoT devices will be interconnected and interact with each other.The schematic diagram of these IoT devices can be observed in Fig. 4.
The transmission of pond water temperature data will be read by the DS18B20 temperature sensor and then forwarded to the cloud server.The temperature data stored on the cloud server will be displayed through a website-based interface.Users will observe real-time pond water temperature conditions through the website interface.The stages of data transmission from the sensor to the cloud server and then displayed on the web interface can be seen in Fig. 5.

D. Design of IoT Device Protective Box
The IoT devices will be positioned on the surface of the pond water.Based on this, a design suitable for such conditions is necessary.In this research, Styrofoam is used as the outer protection for the IoT devices.The IoT components are placed inside an acrylic box designed in a cubic shape.The dimensions of the acrylic box are 10×20×25 cm.Subsequently, this acrylic box is equipped with an outer protector that prevents pond water or rainwater from entering it.This outer protective box is made of Styrofoam with dimensions of 14×25×39 cm.The outer protective box also has a cover to shield the IoT device from rain.The design of the device can be seen in Fig. 6.

E. Layout of Device Placement in the Pond and Location of
Temperature Sensor Placement Fig. 7 illustrates the layout of the location for the earthconstructed tiger shrimp pond.This location spans 0.6 hectares and contains several plots within the area.Sensor placement is strategically positioned within the cultivation plot.These cultivation plots are deemed representative of the entire pond.The study assumes that the plots in this pond share similar water conditions.Based on this assumption, sensor placement is conducted in only one specific plot.
The placement of sensors can be seen in Fig. 8, where the temperature sensor for the upper part will be positioned near the water surface at a depth of 30 cm, while the temperature sensor for the lower part will be placed at a distance of 30 cm above the pond's bottom.The water height from the pond's bottom to the surface is 80 cm.This is done to determine the water temperature above the surface and at the bottom of the pond.The determination of sensor points is based on the water height according to the standards in traditional pond construction, which ranges from 60-80 cm.Thus, to determine the water temperature near the surface, it is placed at a depth of 30 cm from the surface, while to determine the temperature at the bottom, it is placed 30 cm above the pond's bottom.This study assumes that by placing the sensors at this 30 cm interval, it can represent the water temperature conditions above the surface and at the bottom of the pond.Fig. 9 shows the implementation of the IoT device when placed on the surface of the pond water.The device is positioned inside Styrofoam so that it can float on the water surface.Based on Fig. 9, it can be observed that the

A. Internet of Things (IoT) Device Design
The study has successfully developed an IoT-based system for monitoring the water temperature in ponds for the cultivation of giant tiger shrimp.The IoT system initiates by initializing DS18B20 temperature sensor using the 1Wire library and the Dallas Temperature library to enable communication with the microcontroller.The device then identifies and connects to a wireless network.Subsequently, the device collects water temperature data from the giant tiger shrimp pond.In case the device fails to connect to the network, it will attempt reconnection.However, if the device successfully connects to the network, it will link to the Firebase Cloud.The device will then send real-time data every second to the Firebase Cloud database.Following that, the Firebase Cloud will forward the data to the VPS server.The web interface will display the received data from the VPS server.The system's flow is illustrated in Fig. 10.

C. Website User Interface for Monitoring Pond Water
Temperature Fish farmers can view real-time water temperature conditions through the website.The web interface offers several features, including displaying pond water temperature as shown in Fig. 11.Another feature is to show the log data of temperature sensor readings, as indicated in Fig. 12.The next feature is to display a line graph of real-time recorded water temperature conditions, as shown in Fig. 13.Fig. 12 displays real-time observations of the pond water temperature.The observations indicate that the pond water conditions during testing are within the normal range, in accordance with the temperature standards of approximately 28-31°C.Changes in this data will occur if the surrounding weather conditions change, as shown in Fig. 13, where the temperature log indicates the highest value reached 32.31°C, while the lowest water temperature is 27.69 °C.This indicates that there has been a temperature change due to the weather conditions around the pond.temperature to 32.31°C near the surface and 30.81°C near the bottom of the pond.The cause of this temperature rise is attributed to the hot weather conditions surrounding the pond.However, in iteration 13, there is a decrease in water temperature due to cold weather around the pond, registering a value of 27.69°C.

D. Testing the Error and Accuracy of DS18B20 Sensor Measurements
The testing of the DS18B20 temperature sensor aims to determine the level of accuracy and the extent of temperature data error obtained from the sensor.Measurements are conducted by comparing the DS18B20 temperature sensor with a standard water temperature measuring device.Both the DS18B20 sensor and the standard water temperature measuring device are immersed in the same water, and then the temperature measurement process is carried out.The temperature readings from the sensor will be displayed on the website's data log.
The results of the DS18B20 temperature sensor readings are presented in Table II and Table III.To determine the difference in sensor measurements when measuring water temperature, the equation ( 1) is employed.Based on the difference measurement results from equation (1), further steps are taken to assess semantic errors using the equation (2).Systematic errors are a type of error that occurs consistently and can be identified in each measurement or experiment.In addition to measuring errors, this research also conducts an accuracy assessment of the sensor using equation (3).
In equation ( 1), there are variables X, representing the temperature measured using the standard temperature measuring device.Subsequently, variable Xi represents the measured values using the DS18B20 sensor.As for the semantic error value, it is denoted by the variable %error.III, the level of error and accuracy of DS18B20 sensor measurements reached an error value of 5.26%, with an accuracy of 94.734%.In another study [58] reported an error of 0.29%; [59] achieved a 5% error; [60] reported a 0.2% error; [61] error is 0.829%; [62] had a 3.00% error with accuracy below 85%.In the study [63], the sensor accuracy ranged from 95% to 99%.Furthermore, in the research [58] accuracy was reported to be 99.71% and 99.83%.Based on this comparison, it is evident that the average measurement error rate of the DS18B20 sensor ranges from 0.05% to 0.5%, with accuracy levels ranging from 85% to 99%.

Based on Table II and Table
In the research that we have conducted, the measurement results of the DS18B20 sensor showed a temperature range of 28-31°C.Research conducted by [58] showed water temperature values ranging from 20-60°C.Other studies achieved temperatures of 26.2°C-27°C [64].Subsequently, the research [65] showed temperatures of 25 -30 °C; [66] 23.89°C-32.22°C.This indicates that the temperature readings of the DS18B20 sensor under various conditions in different research locations are within the range of 20-31°C.
The research we conducted also utilized the ESP8266 microcontroller, aligning with several previous studies [67]- [76] that also used the same microcontroller as the central data sensor management.Previous studies have also utilized cloud technology [77]- [81] for cloud-based data storage and monitoring through a website interface [57].Based on previous research, there is compatibility in the technology used in this study, demonstrating that the implementation of IoT for monitoring the water temperature quality of ponds is a continuously evolving aspect, adaptable to the needs of other observed parameters such as pH, water oxygen levels, water height, and salinity.

IV. CONCLUSION
This investigation has effectively harnessed the capabilities of IoT devices, specifically employing DS18B20 temperature sensors integrated with WeMos D1 R2 controllers, to monitor water temperatures in conventional shrimp ponds.The system demonstrated significant accuracy, with measurements at 93.42% near the water's surface and 94.74% at the pond's bottom, alongside a sensor error rate of 5.26%.The advancement of this study also lies in its realtime temperature monitoring through a user-friendly web interface.
Despite these achievements, the study acknowledges certain limitations, including a sensor error margin that necessitates reduction and an accuracy level that aspires to reach the 99% benchmark.Consequently, future work is suggested to enhance the observational precision of sensor data and to expand the monitoring network by integrating multi-path routing in Wireless Sensor Networks (WSN).Further research should also consider additional water quality metrics such as pH, oxygen levels, and salinity.The potential application of Artificial Intelligence (AI) in subsequent studies promises to refine aquaculture practices through the analysis of water quality and meteorological time-series data, stored in the cloud for advanced predictive insights.

Fig. 2 .
Fig. 2. Detailed Components in the Proposed Internet of Aquaculture Things (IoAT) Architecture for Traditional Shrimp Ponds

Fig. 3 .
Fig. 3. Proposed Layered Architecture Modeling of the Internet of Aquaculture Things (IoAT) for Traditional Shrimp Pond Cultivation

TABLE I .
COLLECTION OF DATA RESULTS

TABLE II .
COMPARISON OF THERMOMETER WITH DS18B20 FOR WATER UPPER TEMPERATURE MEASUREMENT Ramdan Satra, IoAT: Internet of Aquaculture Things for Monitoring Water Temperature in Tiger Shrimp Ponds with DS18B20 Sensors and WeMos D1 R2

TABLE III .
COMPARISON OF THERMOMETER WITH DS18B20 FOR WATER BOTTOM TEMPERATURE MEASUREMENT