Artificial Intelligence of Things (AIoT) is transforming linear waste management into intelligent, data-driven solutions that support circular economy (CE) principles. This narrative review synthesizes peer-reviewed studies from 2020–2025 on AIoT applications across intelligent waste sorting, data analytics for resource recovery, and sustainable infrastructure development. The review examines IoT-enabled smart bins, computer-vision robotic sorting, machine learning classifiers (VGG-16/19: 97.11–99.7% accuracy, ResNet: 91.5–98.16%), predictive analytics, and graph-based route optimization. Reported improvements include up to 50% reduction in overflow events, 15.5–30% fuel savings, and... More >

The integration of artificial intelligence and the Internet of Things (AIoT) enables advanced edge computing but creates significant energy challenges for resource-constrained devices. To address these challenges, this paper introduces a novel comparative taxonomy and a systematic gap analysis matrix that directly maps hardware-aware TinyML paradigms to network-layer scheduling in sustainable AIoT systems. Synthesizing recent empirical studies (2023–2026) on power consumption models for IoT edge devices, machine learning techniques for energy optimization, and sustainable deployment strategies, we demonstrate that additive and regression-based models achieve low prediction error (MAPE 4–... More >