TY  - JOUR
AU  - Banik, Barnali Gupta
AU  - Boddula, Hari Priya
AU  - Chatiri, Shreethu
PY  - 2026
DA  - 2026/03/12
TI  - SAWAOS: Smart Agri-Waste Analysis and Optimization System
JO  - Digital Intelligence in Agriculture
T2  - Digital Intelligence in Agriculture
JF  - Digital Intelligence in Agriculture
VL  - 2
IS  - 1
SP  - 12
EP  - 18
DO  - 10.62762/DIA.2025.690210
UR  - https://www.icck.org/article/abs/DIA.2025.690210
KW  - agricultural waste management
KW  - applied AI
KW  - decision-support systems
KW  - circular economy
KW  - sustainable agriculture
AB  - The growing volume of agricultural residues poses significant environmental and economic challenges, while existing waste management practices remain inefficient and unsustainable. This paper presents SAWAOS (Smart Agri-Waste Analysis and Optimization System), an applied AI-based decision-support framework for intelligent agricultural waste utilization. SAWAOS integrates waste characteristics, location information, and domain knowledge to generate context-aware recommendations for composting, bioenergy conversion, and industrial reuse. The system employs an explainable, rule-enhanced AI decision logic suitable for low-data rural environments and incorporates a digital marketplace that directly connects farmers with industries and consumers, supporting circular economy principles. The framework is validated through a functional prototype and case-study-based evaluation using representative agricultural residues. A comparative analysis with existing waste management approaches highlights the advantages of SAWAOS in terms of decision support, stakeholder integration, and scalability. The SAWAOS demonstrates how applied AI can transform agricultural waste from a disposal challenge into a sustainable economic resource.
SN  - 3069-3187
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Banik2026SAWAOS,
  author = {Barnali Gupta Banik and Hari Priya Boddula and Shreethu Chatiri},
  title = {SAWAOS: Smart Agri-Waste Analysis and Optimization System},
  journal = {Digital Intelligence in Agriculture},
  year = {2026},
  volume = {2},
  number = {1},
  pages = {12-18},
  doi = {10.62762/DIA.2025.690210},
  url = {https://www.icck.org/article/abs/DIA.2025.690210},
  abstract = {The growing volume of agricultural residues poses significant environmental and economic challenges, while existing waste management practices remain inefficient and unsustainable. This paper presents SAWAOS (Smart Agri-Waste Analysis and Optimization System), an applied AI-based decision-support framework for intelligent agricultural waste utilization. SAWAOS integrates waste characteristics, location information, and domain knowledge to generate context-aware recommendations for composting, bioenergy conversion, and industrial reuse. The system employs an explainable, rule-enhanced AI decision logic suitable for low-data rural environments and incorporates a digital marketplace that directly connects farmers with industries and consumers, supporting circular economy principles. The framework is validated through a functional prototype and case-study-based evaluation using representative agricultural residues. A comparative analysis with existing waste management approaches highlights the advantages of SAWAOS in terms of decision support, stakeholder integration, and scalability. The SAWAOS demonstrates how applied AI can transform agricultural waste from a disposal challenge into a sustainable economic resource.},
  keywords = {agricultural waste management, applied AI, decision-support systems, circular economy, sustainable agriculture},
  issn = {3069-3187},
  publisher = {Institute of Central Computation and Knowledge}
}