Published Paper Details:

Abstract: The degree of acidity(pH) and total dissolved solids (TDS) is very important for the fish's health. The Fish in the aquarium release their waste in the form of ammonia. Ammonia is toxic to all other aquatic organisms. The high level of ammonia in water will affect the pH and TDS levels of water. If pH and TDS levels in the water are not good then it will affect the fish's health. Usually, the pH sensor and TDS sensor are used to monitor the pH value and TDS value. The fish requires a 7-7.5 pH value and 400ppm-450ppm of TDS value. If these sensors are not working properly, then it will affect the fish in the aquarium. This proposed system stores these sensor values for one day in a CSV file(dataset). The isolation forest algorithm is used for detecting the outlier in the dataset. The Linear regression algorithm is used for predicting the pH value and TDS value range. Based on the prediction, the pH level and TDS level of water can be checked once again and then can be changed. By detecting the outlier we can identify the hardware faults in the system. By predicting the pH value and TDS value, the water can be changed on time to save the aquatic organisms.