This study checks on emerging research trends and conducts a bibliographic analysis on smart waste bins as foundational elements for cost-effective, automated waste management solutions. The escalating urbanization and environmental pressures necessitate advanced waste management technologies, where smart trash bins equipped with IoT (Internet of Things), AI (Artificial Intelligence), and robotics offer transformative solutions such as automated segregation, real-time monitoring, and optimized collection routes. Employing a systematic literature review facilitated by Scopus AI, the study identifies consistent, rising, and novel themes in smart bin research. IoT-enabled systems consistently emerged, underscoring their role in operational efficiency and sustainability. Rising trends prominently featured AI integration, robotic automation, and advanced waste segregation methods, indicating a clear shift towards intelligent automation. Security and privacy issues constitute novel themes, reflecting the growing importance of ensuring trust and reliability in technology adoption. The bibliometric analysis revealed significant global research contributions with notable peaks aligning with heightened global sustainability goals. Additionally, the study proposes a conceptual prototype integrating sensors, AI-driven categorization, and autonomous collection mechanisms, validated through simulation testing. Findings demonstrated improved operational efficiency, higher recycling accuracy, and substantial cost savings. Addressing integration challenges, infrastructure compatibility, and public acceptance, the study provides critical insights for urban planners, policymakers, and stakeholders. This work significantly contributes to the discourse on sustainability and smart city initiatives, highlighting technological innovation as pivotal in solving contemporary environmental management issues.