Personalized context-aware systems for sustainable agriculture development using ubiquitous devices and adaptive learning

Abstract

Advanced technologies offer a promising answer, especially integrating personalized context-aware systems through ubiquitous devices and adaptive learning. This paper explores the ability of these technologies to transform agricultural practices, improving performance and sustainability. This study aims to analyze the effect of integrating context-aware structures in agriculture using ubiquitous gadgets and adaptive learning fashions. It specializes in assessing the upgrades in helpful resource control, crop yield, and environmental sustainability and explores the farming community's economic, social, and academic advantages. Utilizing a combined-methods approach, the studies combine intensive literature with empirical statistics series, including discipline experiments, surveys, and interviews with key agricultural stakeholders. It examines contemporary farming practices, the capabilities of rising technology, and the conditions for enforcing robust context-aware systems in farming. Implementing context-aware systems improves agricultural practices by optimizing water and chemical usage, enhancing soil health, and increasing crop yields. Ubiquitous devices and adaptive learning models facilitate specific, real-time selection-making, leading to extra sustainable and green farming operations. Feedback from the rural community similarly underscores the positive effect of technology on improving accessibility to facts and collaborative learning. The study demonstrated that integrating personalized, context-aware systems with IoT and adaptive learning significantly improves agricultural efficiency and sustainability, evidenced by enhanced resource management and increased crop yields. This study contributes to the discourse on leveraging advanced technology to reap agricultural sustainability and units the groundwork for destiny research and coverage development in era-better farming.