International Journal of Science, Engineering and TechnologyAuthors: Taranjeet Singh, Manu Raj Moudgil
Abstract: India faces interconnected challenges of agricultural residue mismanagement, environmental pollution, and increasing demand for sustainable infrastructure materials. Large quantities of rice straw are generated annually after paddy harvesting, particularly in northern India. Due to limited management alternatives, farmers frequently resort to open-field burning, resulting in severe air pollution, soil degradation, and public health impacts. Simultaneously, the road construction sector depends heavily on petroleum-based bitumen, contributing to greenhouse gas emissions and economic vulnerability due to crude oil imports. This paper proposes DirectSmart, a comprehensive Artificial Intelligence (AI)-driven resource management framework aligned with circular economy principles and the Swachh Bharat Mission. The framework integrates satellite-based identification of rice-growing regions, machine learning-based biomass forecasting, mathematical optimization of collection and logistics, AI-assisted bio-bitumen quality prediction, and governance-level environmental impact assessment. Unlike conventional approaches where AI is loosely associated with sustainability, this study demonstrates how AI functions as the central enabling mechanism that ensures technical feasibility, economic viability, environmental sustainability, and social acceptance of rice straw-based bio-bitumen production in India. The proposed framework is suitable for scalable implementation and policy-level adoption in developing economies.
DOI: http://doi.org/10.5281/zenodo.18631488
