This repository contains the relevant code and prototype for the Aquaponics Hackathon 2023, hosted by the IEEE NUS X IEEE NTU student branch.
Aquaponics Monitoring System for Tilapia and Asian Leafy Greens Farm with an emphasis on inclusivity and social impact.
Aquaponics is a sustainable agricultural system that combines aquaculture with hydroponics. It creates a mutually beneficial ecosystem where fish waste provides nutrients for the plants, and the plants help filter and clean the water for the fish. While aquaponics offers numerous benefits, it requires meticulous care to maintain the delicate balance between fish and plants. To streamline the monitoring process and ensure optimal conditions for both Tilapia fish and Asian leafy greens, we have developed an Aquaponics Monitoring System called CloudSensor.
In this proposal, we outline our vision to enhance the social impact of our Aquaponics Monitoring System, CloudSensor, by also introducing AquaFeeder focused on positively contributing to the community, with a particular emphasis on children in hospitals. This aims to improve the well-being of the children, promote environmental awareness, and offer valuable educational experiences.
With this two-pronged approach, we aim to not only empower local farmers and promote sustainable agriculture but also extend our impact to the broader community, especially children in hospitals who could benefit greatly from the therapeutic and educational aspects of aquaponics.
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Real-time Monitoring: The system aims to provide real-time data on essential parameters to closely monitor the health and well-being of the fish and plants.
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Automation: Automation features are integrated to reduce manual workload and ensure consistent environmental control.
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Data Analysis: The collected data is analyzed to gain insights into the system's performance, enabling informed decision-making for improvements.
Our working proof of concept includes the integration of three key sensors in the prototype, each playing a crucial role in our comprehensive monitoring system. The SEN0161 sensor enables accurate pH measurement, providing valuable insights into the water's acidity or alkalinity. To monitor water temperature variations, we have incorporated the DS18B20 sensor, ensuring we track the aquatic environment effectively. Moreover, we have implemented a color-changing sticker that indicates the concentration of free ammonia in parts per million (ppm), allowing us to assess water quality easily.
To complement this sensor array, we plan to use the ESP32 CAM to monitor the ammonia sticker actively. The ESP32 CAM will capture snapshots, providing visual information about the ammonia sticker's changes and helping us understand the dynamics of ammonia concentration over time.
Additionally, we may attach other peripheral sensors, such as lux sensors, to gather a variety of readings and further enhance our understanding of both aquatic and plant environments. These sensors collectively form the foundation of our monitoring system, empowering us to make informed decisions and take necessary actions to maintain optimal conditions for aquatic life and plants.
The ESP32 microcontroller serves as the central processing unit, efficiently gathering sensor data. To transmit this data to the cloud, we employ the MQTT protocol, a lightweight messaging protocol ideal for IoT applications. Leveraging the robust infrastructure of Amazon Web Services (AWS), we utilize AWS IoT Core as the MQTT broker, ensuring secure and reliable data communication between the prototype and the cloud.
Once in the cloud, the data is efficiently stored in AWS Timestream, a scalable and purpose-built time-series database, allowing us to organize and manage the information effectively. Additionally, historical data is archived in an AWS S3 bucket, ensuring a comprehensive dataset for long-term analysis and reference.
To visualize and interpret the data, we utilize Grafana, a powerful analytics and monitoring platform. Grafana enables stakeholders to access real-time and historical data, empowering them to make informed decisions based on dynamic visualizations and dashboards.
Furthermore, to ensure prompt action in critical scenarios, we have implemented alert mechanisms that trigger notifications when specific threshold values are exceeded. This enables swift responses to potential issues, maintaining the system's health and productivity.
As an extension of the Aquaponics Monitoring System, CloudSensor, the AquaFeeder prototype aims to enhance the social impact of the project by introducing a unique and inclusive feature focused on positively contributing to the community, especially children in hospitals. AquaFeeder is designed to offer a therapeutic and educational experience for children by allowing them to interact with the aquaponics system through fish feeding. This engagement can improve the well-being of the children, promote environmental awareness, and provide valuable educational opportunities.
To ensure fairness and manage patient participation, AquaFeeder incorporates a queue system. A maximum of 10 people can join the queue to feed the fish at any given time. In cases where the queue is full, AquaFeeder employs a random lucky draw to select the next participant. This adds an element of surprise and anticipation, making the experience even more exciting for the children. Otherwise, if the queue is empty, AquaFeeder automatically dispenses the feed to ensure the fish are adequately nourished. This automated process ensures the well-being of the aquatic life, even when there are no participants in the queue.
The AquaFeeder system comprises several essential components that facilitate an interactive and engaging experience for patients, particularly children in hospitals. These components work in harmony to ensure a seamless and enjoyable fish-feeding process while promoting environmental awareness and education.
At the heart of AquaFeeder lies the Feeder Trigger, a user-friendly mechanism that patients can effortlessly press to initiate the fish-feeding process. This trigger is intelligently connected to the ESP32 microcontroller, which acts as the central coordinator, ensuring the smooth execution of the feeding activity.
Accessible through a user-friendly Front End interface, AquaFeeder allows patients to immerse themselves in the aquatic world. They can marvel at the live video stream of the fish and eagerly participate in the feeding queue by simply pressing the designated button on the interface.
Behind the scenes, the Web Server efficiently manages the queue system, handles user requests, and even orchestrates the random lucky draw process when needed. This meticulous organization ensures fair and inclusive opportunities for all participants.
Driving the visual experience is the ESP32 (CAM) board, which diligently connects the feeder trigger and the camera module. As the patients engage in fish feeding, the ESP32 (CAM) captures delightful snapshots of the fish during the process, creating a beautiful visual record of their interactions with the aquatic life.