TY  - JOUR
AU  - Panda, Snehal
AU  - Jana, Atanu
AU  - Nahak, Manoswini
AU  - Singaravel, G.
AU  - Mallik, Sandipan
AU  - Swain, Kunjabihari
PY  - 2026
DA  - 2026/06/30
TI  - Waste Management and Circular Economy: A Comprehensive Review of AIoT Applications in Intelligent Waste Sorting, Data Analytics for Resource Recovery, and Sustainable Infrastructure Development
JO  - Next-Generation Computing Systems and Technologies
T2  - Next-Generation Computing Systems and Technologies
JF  - Next-Generation Computing Systems and Technologies
VL  - 2
IS  - 2
SP  - 64
EP  - 69
DO  - 10.62762/NGCST.2026.790821
UR  - https://www.icck.org/article/abs/NGCST.2026.790821
KW  - AIoT
KW  - circular economy
KW  - intelligent waste sorting
KW  - resource recovery
KW  - sustainable infrastructure
KW  - smart waste management
KW  - predictive analytics
AB  - 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 35.5% better bin utilization. These technologies enhance material recovery, reduce landfilling, and support closed-loop resource flows. Challenges—including high costs, data privacy, and limited model generalizability—are discussed alongside future directions such as edge-AI, blockchain, and multi-modal sensing. AIoT shows strong potential to advance UN SDGs 11 and 12, offering a roadmap for scalable urban circular economy transitions.
SN  - 3070-3328
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Panda2026Waste,
  author = {Snehal Panda and Atanu Jana and Manoswini Nahak and G. Singaravel and Sandipan Mallik and Kunjabihari Swain},
  title = {Waste Management and Circular Economy: A Comprehensive Review of AIoT Applications in Intelligent Waste Sorting, Data Analytics for Resource Recovery, and Sustainable Infrastructure Development},
  journal = {Next-Generation Computing Systems and Technologies},
  year = {2026},
  volume = {2},
  number = {2},
  pages = {64-69},
  doi = {10.62762/NGCST.2026.790821},
  url = {https://www.icck.org/article/abs/NGCST.2026.790821},
  abstract = {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 35.5\% better bin utilization. These technologies enhance material recovery, reduce landfilling, and support closed-loop resource flows. Challenges—including high costs, data privacy, and limited model generalizability—are discussed alongside future directions such as edge-AI, blockchain, and multi-modal sensing. AIoT shows strong potential to advance UN SDGs 11 and 12, offering a roadmap for scalable urban circular economy transitions.},
  keywords = {AIoT, circular economy, intelligent waste sorting, resource recovery, sustainable infrastructure, smart waste management, predictive analytics},
  issn = {3070-3328},
  publisher = {Institute of Central Computation and Knowledge}
}