Climate-Adaptive Farming: Strategies for Food Security and Adaptation Models Amid Rising Droughts and Population Pressures

The convergence of digital technologies with agricultural practices has catalysed a paradigm shift in contemporary farming systems, giving rise to precision agriculture as a transformative approach to sustainable food production. The technological foundations of precision agriculture rest upon three interconnected pillars: the Internet of Things (IoT), artificial intelligence (AI), and remote sensing. This comprehensive review examines the integration of Internet of Things (IoT), artificial intelligence (AI), and remote sensing technologies in precision agriculture, synthesising current knowledge and identifying future research trajectories. The proliferation of smart sensors, unmanned aerial vehicles, satellite imaging systems, and machine learning algorithms has enabled unprecedented capabilities for real-time monitoring, predictive analytics, and automated decision-making in agricultural contexts. Through systematic analysis of peer-reviewed literature published between 2005 and 2025, this review evaluates the technological frameworks, practical applications, and implementation challenges associated with digital agriculture. Key findings indicate that IoT-enabled sensor networks have achieved water savings of up to 30% through precision irrigation management, whilst AI-driven crop yield prediction models demonstrate coefficient of determination values exceeding 0.85. Remote sensing technologies, particularly when integrated with machine learning algorithms, have attained disease detection accuracies ranging from 81% to 95% in field conditions. However, significant barriers to widespread adoption persist, including high infrastructure costs, limited digital literacy among farming communities, data interoperability challenges, and concerns regarding data privacy and ownership. Future developments in deep learning, reinforcement learning, and digital twin technologies are expected to further enhance decision-making capabilities in agriculture. This review provides critical insights into the current state of precision agriculture technologies, identifies research gaps, and proposes future directions for advancing sustainable and efficient agricultural production systems in the face of growing global food security challenges.