INTELLIGENT SYSTEM OF FISH COMPATIBILITY CONTROL IN AN AQUARIUM
Authors:
1.
Kazan State Energy University
2.
Kazan State Power Engineering University
(Associate Professor)
Kazan, Russian Federation
Kazan, Russian Federation
Type:
Article
eLocation:
Status:
Published
Received:
04.08.2025
Accepted:
07.08.2025
Published:
07.08.2025
Language:
Russian
Keywords:
AQUARISTICS, SOFTWARE, INTELLIGENT SYSTEM, HYDROBIONTS, ECOSYSTEM, FISH COMPATIBILITY, MACHINE LEARNING
Abstract (English):
The current level of development of digital technologies opens up new opportunities for their application in the field of aquaristics, namely to ensure harmonious interaction of species in artificial ecosystems. One of the promising tools in this area is an intelligent fish compatibility control system designed to help aquarium owners make informed decisions when forming communities of aquatic inhabitants. The article deals with the development and application of such a system, which analyses biological characteristics, behavioural features and requirements to the conditions of different fish species. Based on these data, the system generates personalised recommendations, including advice on species compatibility, optimal water parameters, feeding, and warnings of potential conflicts or health risks to the inhabitants. Using clustering and regression analysis techniques, a model predicting aquarium fish species compatibility with 92% accuracy is developed. It is proposed to implement this system in pet shops and aquarium complexes to improve the quality of customer service and reduce errors in the selection of hydrobionts. The article emphasises the role of an intelligent system in maintaining the balance of the aquarium ecosystem and analyses its benefits: increased fish survival, simplified aquarium maintenance and increased user satisfaction. The implementation of such technologies contributes to the development of responsible aquaristics and minimises the negative impact on biodiversity.
The current level of development of digital technologies opens up new opportunities for their application in the field of aquaristics, namely to ensure harmonious interaction of species in artificial ecosystems. One of the promising tools in this area is an intelligent fish compatibility control system designed to help aquarium owners make informed decisions when forming communities of aquatic inhabitants. The article deals with the development and application of such a system, which analyses biological characteristics, behavioural features and requirements to the conditions of different fish species. Based on these data, the system generates personalised recommendations, including advice on species compatibility, optimal water parameters, feeding, and warnings of potential conflicts or health risks to the inhabitants. Using clustering and regression analysis techniques, a model predicting aquarium fish species compatibility with 92% accuracy is developed. It is proposed to implement this system in pet shops and aquarium complexes to improve the quality of customer service and reduce errors in the selection of hydrobionts. The article emphasises the role of an intelligent system in maintaining the balance of the aquarium ecosystem and analyses its benefits: increased fish survival, simplified aquarium maintenance and increased user satisfaction. The implementation of such technologies contributes to the development of responsible aquaristics and minimises the negative impact on biodiversity.
Keywords:
AQUARISTICS, SOFTWARE, INTELLIGENT SYSTEM, HYDROBIONTS, ECOSYSTEM, FISH COMPATIBILITY, MACHINE LEARNING
AQUARISTICS, SOFTWARE, INTELLIGENT SYSTEM, HYDROBIONTS, ECOSYSTEM, FISH COMPATIBILITY, MACHINE LEARNING
