DAPA: data-driven autonomous precision agriculture for field decarbonization
A data-driven precision agriculture platform combining underground networked sensors, UAVs/UGVs, and AI-enabled biophysical modeling to enable autonomous crop management, reduce fossil fuel use, and improve carbon sequestration in large-scale farming operations.
Overview
This research program develops a data-driven autonomous precision agriculture platform aimed at reducing fossil fuel dependence in farming while improving carbon sequestration. By combining below-ground networked sensors with above-ground UAVs and UGVs, the platform delivers continuous, real-time monitoring of soil and crop conditions across large fields. AI-enabled biophysical modeling turns these data streams into actionable insights for autonomous crop management, supporting more sustainable and efficient field operations.
Technical specifications
Core sensing and data capabilities:
- Underground networked sensors for soil moisture measurement at multiple depths and field locations
- Above-ground sensing via UAVs and UGVs for coordinated field data collection
- AI-enabled 3D and 4D soil moisture mapping using artificial neural networks
- Edge control platform for real-time sensor and vehicle coordination
Hardware and prototyping:
- Raspberry Pi and programmable radio testbed simulating underground wireless connectivity in soil-filled transparent Lexan tanks
- Custom PCB-based sensing and communication units under development
- UAVs equipped with drilling manipulation for on-farm soil sampling
- Ground vehicle prototypes with weed detection and laser-based zapping capabilities
Decision-making and modeling:
- Real-time biophysical modeling that couples soil, weather, field, and crop data
- Advanced AI for automated farm management decisions and crop variety recommendations
- Collaboration with agronomists and field practitioners to expand parameter coverage and model accuracy
Technology readiness level
The platform is currently at a proof-of-concept stage. A laboratory testbed has been built to validate below-ground wireless connectivity, and initial PCB sensor hardware and UAV drilling prototypes are under fabrication. Future validation will focus on three thrusts: integrating pervasive soil sensing with real-time biophysical models to improve daily field operations; developing vehicle manipulation capabilities including laser-based weed control and aerial soil sampling; and advancing AI-driven automation to support deployment of resilient, sustainable crop varieties.
About North Carolina State University
North Carolina State University is a large, comprehensive public land‑grant research university in Raleigh. Its on‑campus research and technology park co‑locates corporate R&D groups, government partners, and faculty labs, enabling shared facilities, prototyping, and agile contracting. Located in North Carolina’s Research Triangle, partners tap a dense regional ecosystem while engaging through a statewide extension network and a mature co‑op program that deliver field deployment and workforce pipelines. Multiple pilot and demonstration facilities support scale‑up and validation toward pre‑commercial readiness. Research is supported by competitive funding from major federal agencies, including NSF, USDA, DOE, and DOD, and a dedicated technology transfer office with clear IP pathways helps accelerate commercialization.
Inquire about this partnering listing
Looking for
Industry applications
delivered to your inbox.