Microbiological response and treatment outcomes among multidrug-resistant tuberculosis patients at Allied Hospital, Faisalabad, Pakistan: A prospective cohort study

Review article | https://doi.org/10.47262/BL/12.1.20260316

IoT and artificial intelligence applications in aquaculture: Implications for water quality, fish health, food safety, and human health

Maheen Tofeeq¹*, Maryam Toufiq²

¹Department of Computer Science & IT, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan

²Department of Zoology, Cholistan Institute of Biological Sciences, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan

Abstract

Aquaculture is one of the fastest-growing food production sectors worldwide and plays a key role in meeting the increasing global demand for seafood. Water quality is essential for the health, growth, and survival of fish. Conventional methods for monitoring water are excessively time-consuming and cannot provide the real-time information required for good management. A comprehensive review of Internet of Things (IoT) based fishpond systems is given, concentrating on hardware devices, sensor technologies, communication protocols, data management and Artificial Intelligence (AI) / Machine learning (ML) integration. Research papers published from 2015 to 2025, which report on sensor devices or water parameters, including AI-ML techniques, were considered. Information on hardware platform (cameras, acoustic, or other) monitored fish species, examined parameter connectivity , biological impact and key findings was recorded. IoT-based systems can continuously measure parameters such as temperature, pH and dissolved oxygen, and in some cases ammonia and nitrates directly from the source. It is cloud computing and AI/ML compatible for real-time monitoring, predictive analysis and intelligent decision making. System cost, connectivity and scalability vary, from inexpensive solutions for small farmers to alternatives that emphasize automation and high precision. To date, there are still challenges for the monitoring of biological markers, low-power connectivity and predictive capabilities. For smart aquaculture, the application of IoT technologies holds transformational power in that it can improve water quality control, fish well-being and commercial value. Future work should consider the development of integrated and adaptive systems that combine environmental and biological sensing, low-power networks as well as AI/ML support for predictive management in sustainable and profitable aquaculture.