Water, as the most vital resource for life, is increasingly threatened by chemical and environmental pollution. Traditional methods of water quality monitoring, while useful, are often costly, time-consuming, and limited in efficiency. To address these challenges, researchers have turned to innovative approaches such as biomonitoring—a technique that uses living organisms, especially fish, as sensitive indicators of environmental changes. In recent years, the integration of biomonitoring with modern technologies like image processing and machine vision has opened new horizons for real-time and accurate water quality assessment. This combination not only improves efficiency but also provides continuous, non-invasive, and highly sensitive monitoring, making it a promising solution for ensuring safe and sustainable water resources.
Global studies show big progress in using living organisms for water biomonitoring. Fish, daphnia, and other aquatic animals can act as early warning systems for pollution, showing changes in the environment before chemical tests can. But there are still many challenges, especially in bringing these systems to developing countries where equipment and expertise are limited.
Commercial platforms like FishToximeter and DaphniaToximeter work very well in laboratories and are highly accurate. However, they are expensive, need special conditions, and are hard to use outside controlled labs. They also depend on special hardware, private software, and expert operators, which makes them difficult to expand or use locally. To solve these issues, we need more affordable and flexible systems that can work in different environments and be easier to use in places with fewer resources.
The Aicer research team has developed an intelligent biomonitoring system named BIO AI. The main objective of this study is the design and implementation of an intelligent biomonitoring system based on the behavioral analysis of zebrafish, capable of detecting real-time changes in water quality and providing early warnings of potential pollutants. Using advanced machine vision algorithms, the system records and analyzes fish movements under both normal and contaminated conditions, enabling the identification of abnormal behavioral patterns caused by toxic substances. In addition to the visual monitoring module, the project also introduces an independent environmental control system built on the ESP32 microcontroller. This module continuously monitors and regulates aquarium conditions such as water temperature, level, flow rate, and aeration. It integrates a DS18B20 temperature sensor with a PID controller, a water level sensor for maintaining a fixed volume (8 liters), a YF-S201C flowmeter for real-time flow measurement, and a timer-controlled relay for aeration.
By combining behavioral image analysis with automated environmental control, the proposed system delivers a comprehensive and fully automated biomonitoring solution that can be applied in water treatment industries, aquaculture, environmental research, and water resource management.
Electronic Schematic
This diagram shows how the ESP32 microcontroller is connected to different sensors and modules. The DS18B20 sensor measures water temperature, while a water level sensor checks both high and low levels. A 4-relay module controls devices such as the heater, the air pump (bubble maker), and the water level pumps. With this setup, the ESP32 can read the conditions of the tank and automatically switch equipment on or off to keep the water environment stable.
Control Board & Wiring
This part highlights the power supply, relay module, and wiring connections inside the device. The power supply provides stable voltage, the relay module acts as a bridge between the ESP32 and high-power devices, and the wiring links everything together. In short, this is the “hardware core” of the system that makes it possible to automatically manage temperature, water level, and aeration.
Final Device
The finished unit, branded BIOAI – AICER201, represents the final stage of development where all hardware and software components are fully integrated into a compact system. Designed for both industrial and research applications, this device combines automated water monitoring, intelligent control, and real-time image analysis in one unit. Its modular design ensures that sensors, actuators, and processing units are arranged neatly for reliability and ease of maintenance.
On the outside, the BIOAI – AICER201 has a protective enclosure that provides durability in different environments, while the internal structure organizes tanks, pumps, and control electronics into separate compartments. This design not only improves functionality but also enhances user safety and operational efficiency. The system is versatile enough to be deployed in laboratories, aquaculture farms, and industrial facilities, making it a practical solution for continuous biomonitoring.
Conclusion
The development of BIOAI – AICER201 demonstrates how advanced technologies such as image processing, intelligent control, and real-time data collection can be combined to create a fully automated biomonitoring solution. By integrating hardware and software into a single compact unit, the system addresses key limitations of traditional monitoring methods, offering improved efficiency, lower operating costs, and greater adaptability.
In the bigger picture, this device highlights the importance of interdisciplinary research, where electronics, computer vision, and environmental science work together to protect vital water resources. As industries and communities face growing challenges of pollution and sustainability, solutions like BIOAI – AICER201 provide a clear pathway toward safer, cleaner, and smarter water management for the future.
Developed and researched by Arvin Zaheri – Aicer Lab