AgriTwin: Real-Time Digital Twin Framework for Climate-Smart Farming
PI: Dhananjay Singh (IST)
AgriTwin is a scalable, AI-enabled Digital Twin platform designed to support emission sustainability in agriculture. An industry responsible for over a quarter of global GHG emissions, yet among the least digitized. This project integrates IoT air quality sensors, an AgriTwin-based data platform, and AIenhanced modeling (including CHIMERE-WRF simulations and Monte Carlo analysis) to estimate methane (CH₄) and ammonia (NH₃) emissions from fertilizer use and crop residue burning. By generating real-time, hyperlocal emission data and combining it with 3D interactive visualizations developed with MetaWorldX, AgriTwin enables farmers and policymakers to simulate and evaluate sustainable land-use scenarios. The project brings together key partnerships: Penn State (Academia) engages researchers and students in research, entrepreneurship, and innovative applications, while MetaWorldX & Libelium (Industry) contribute expertise in environmental technologies, IoT, and digital twin systems to advance sustainable agricultural practices. Open-source architecture promotes extensibility and community adoption, aiming to accelerate data-driven climate resilience through interdisciplinary collaboration across AI, Digital Twins, and agricultural science.
Desired Skills/Expertise:
Machine learning for time series analysis, environmental sensor data processing, AI-based simulation modeling, data visualization (3D), and knowledge of AgriTwin-based IoT data platforms.
Other Requirements or Expectations:
Availability for weekly meetings; post-comps graduate student status; experience or interest in Digital Twin, emissions modeling, or agricultural analytics.
Specific Objectives:
• Deploying IoT sensors in experimental crop fields
• Build a FIWARE-based data platform
• Model emission discrepancies using AI
• Develop a 3D visualization tool
• Publish results in open-source repositories
• Disseminate outcomes via ICDS and academic forums
Medium/Long-Term Goal:
Submit a competitive proposal for the USDA/NIFA and NSF Smart Agriculture Program in 2026.
Connection to ICDS Mission:
This project advances the ICDS mission by leveraging Digital Twin technologies to address agricultural emissions, a critical challenge in sustainability and global food systems.
Engagement with ICDS:
This project will actively participate in ICDS activities, including talks, symposia, and collaborative forums.