Climate Smart Technologies

Abstract

Aquaculture is increasingly recognized as a critical pillar for food security and economic growth, especially in emerging economies where population growth and dietary transitions drive high demand for affordable protein. However, aquaculture faces significant environmental challenges such as fluctuating water quality, pollution, climate variability, and infrastructural constraints. Traditional monitoring systems often fail to provide timely insights, resulting in poor management practices and losses in productivity. This chapter explores the transformative potential of artificial intelligence (AI) integrated with the Internet of Things (IoT) for environmental monitoring in aquaculture. By enabling real-time sensing, predictive analytics, and intelligent decision-making, AI-enhanced IoT systems offer a resilient approach to water quality management, operational efficiency, and sustainability in resource-constrained settings. The chapter discusses critical parameters for monitoring, architectural designs, machine learning applications, governance and ethics, and practical implementation strategies, supported by illustrative case examples. It concludes with recommendations for future research and policy directions that emphasize inclusivity and sustainability.