This study explores integrating artificial intelligence (AI) and Internet of Things (IoT) sensor technologies to optimize temperature control in vermicomposting. Effective temperature regulation is crucial for maintaining the health of composting worms and ensuring efficient organic waste decomposition. AI-based systems enable continuous monitoring and predictive analysis, streamlining the composting process while reducing manual oversight. This research examines the impact of AI-powered temperature regulation, the development of an IoT-based monitoring system, and barriers to AI adoption in vermicomposting. A mixed-methods research approach is employed, incorporating qualitative and quantitative methodologies such as surveys, observational studies, and literature analysis. AI algorithms assist in predicting optimal conditions, and data collection is facilitated through IoT sensors. The study discusses the potential benefits of AI intervention, including improved compost quality, enhanced decomposition rates, and worm health sustainability. The findings contribute to understanding the scalability of AI applications in sustainable waste management. Additionally, the broader implications of AI in agriculture and environmental monitoring are discussed, highlighting best practices for implementation and dissemination of research findings.