Call for Paper
SMART-2026 – International Conference on Sustainable Management and Advanced Research Technologies with primary focus of Sustainable Management—encompassing resource optimization, ethical governance, environmental stewardship, and circular economy principles—and Advanced Research Technologies, including AI, machine learning (ML), data analytics, IoT, and computational modeling, invites original and unpublished research contributions from academia, industry, and research organizations worldwide. The conference aims to bring together researchers, scientists, engineers, and innovators to share their latest findings and technological advancements in the domain of intelligent systems, smart networks, and global digital applications. This includes original research on physics-informed simulations, quantum-inspired methods, and sustainable applications in energy, materials, and intelligent systems.The Conference priotirizes UN SDGs integrated with cutting-edge tech for scalable, real-world impact. Prospective authors are encouraged to submit high-quality full-length research papers that have not been previously published or submitted elsewhere. Submissions may include theoretical studies, experimental research, case studies, industrial applications, or review articles addressing Sustainable Management and Advanced Research Technologies.
Track 1: Sustainable Energy Management and AI-Driven Renewable Technologies
- Physics-informed neural networks for forecasting solar/wind integration and grid stability.
- Quantum-inspired optimization for microgrid energy trading and carbon emission reduction.
- ML-based predictive maintenance in renewable systems for lifecycle sustainability.
- Digital twins for thermodynamic modeling in hybrid energy infrastructures.
- Data analytics for policy-driven transitions to net-zero energy ecosystems.
Track 2: Green Computing and IoT for Resource-Efficient Management
- Energy-aware algorithms and edge computing for low-carbon data processing.
- IoT sensor networks for real-time waste minimization and supply chain traceability.
- AI workload scheduling to optimize computational sustainability in cloud environments.
- Blockchain-IoT hybrids for ethical resource allocation in smart manufacturing.
- Climate-resilient architectures for sustainable digital infrastructure governance.
Track 3: Advanced Materials Management and Nanotechnology for Eco-Innovation
- ML-accelerated discovery of recyclable nanomaterials for circular economies.
- Computational simulations of smart composites for low-waste sustainable production.
- AI predictive modeling for material degradation and ethical sourcing strategies.
- Nanotechnology in water remediation and pollution control for environmental management.
- Robotics-AI integration for zero-defect manufacturing in green supply chains.
Track 4: Biomedical Intelligence and Sustainable Healthcare Management
- AI precision medicine for efficient drug discovery and equitable health resource distribution.
- Wearable IoT for remote monitoring in resource-constrained sustainable healthcare systems.
- Computational biophysics modeling for eco-friendly biomedical device design.
- Ethical AI frameworks for data-driven healthcare policy and global access equity.
- Predictive ML for epidemic management and resilient public health infrastructures.
Track 5: Intelligent Urban Management and Environmental Resilience Technologies
- AI-IoT fusion for sustainable urban planning and mobility optimization.
- Digital twins for climate-adaptive infrastructure and disaster risk management.
- ML algorithms for environmental forecasting and biodiversity resource preservation.
- Remote sensing analytics for earth systems monitoring and sustainable land use.
- 5.Governance models using big data for enforcement of green urban policies.
Track 6: Responsible AI and Ethical Management in Advanced Technologies
- Explainable AI for transparent sustainability audits and decision-making.
- Ethical guidelines for AI automation in labor-equitable industrial management.
- Bias-mitigated ML for fair resource distribution in developing sustainable economies.
- Human-AI collaboration paradigms for innovation in green tech governance.
- Standardization protocols for reproducible AI in scientific computing and ethics.
Track 7: Data Analytics and Quantum Technologies for Sustainable Optimization
- Quantum algorithms for supply chain risk management and ESG compliance.
- Big data analytics for business intelligence in sustainable investment modeling.
- Hybrid quantum-ML simulations for financial forecasting in green markets.
- Reinforcement learning for dynamic pricing and resource optimization in eco-systems.
- Privacy-preserving analytics for international collaborations on sustainability goals.
Track 8: Interdisciplinary Deep Learning Applications in Sustainable Management
- Generative deep learning for climate scenario planning and adaptation strategies.
- DL in satellite imagery for agricultural sustainability and food security management.
- Neural networks for geophysical analysis in ecosystem and resource preservation.
- AI-enhanced robotics for automated sustainable agriculture and forestry practices.
- Photonics-DL integration for energy-efficient sensing in environmental technologies.
