Cloud-connected iot sensor monitoring solution for smart agriculture
A cost-effective, high-accuracy cloud-connected IoT sensor network for real-time greenhouse gas monitoring in crop fields. Uses FPGA-based edge computing and cloud processing, with solar-powered operation and intelligent switching between local and cloud analytics based on energy availability. Designed to support wired and wireless sensors for continuous environmental monitoring in remote agricultural settings.
Overview
This solution delivers a cost-effective, high-accuracy cloud-connected IoT sensor network designed for real-time monitoring of greenhouse gas (GHG) emissions in crop fields. Built for smart agriculture applications, the system combines FPGA-based edge computing with cloud processing capabilities to provide reliable, continuous environmental monitoring. The platform is powered by a reliable, low-cost 5V solar battery charger, making it suitable for deployment in remote agricultural settings without access to grid power.
The system enables tracking of GHG levels in real time to support better-informed decisions about crop management, soil health, and environmental compliance. By balancing local processing with cloud-based analytics, the solution aims to optimize both performance and energy efficiency.
Technical specifications
Core architecture:
- FPGA dual-core embedded processing (Cyclone V chip) for local edge computing
- Integration with Intel-Microsoft cloud edge computing technology
- Microsoft Azure cloud processing capability for advanced analytics
- Support for 20-30 wired and wireless sensors per kit, with expandability through card extension and sequential processing cores
- Integrated sensors from Analog Digital for high-accuracy GHG measurement
- 5V solar battery charger for off-grid power reliability
Intelligent processing modes:
- Local processing during periods of rich solar radiance (sunny days) when battery power is abundant
- Cloud-based processing during low-battery conditions or extended periods without solar availability (rainy days)
- Automatic switching based on energy availability and processing requirements
Design versatility:
The components are designed for edge solutions across multiple industries including agriculture, oil and gas, automotive, and transportation, making the platform adaptable for various field deployment scenarios.
Technology readiness level
The solution has been validated through prior experience with the FPGA kit in another Intel project. The research team brings established expertise in smart grid, cloud computing, edge computing, IoT, and FPGA-based embedded systems. Future validation includes a one-year field implementation with a smart agriculture organization, covering software development and comprehensive field testing. The university offers extensive experience in smart agriculture research and field demonstration capabilities through its statewide Cooperative Extension network, positioning the solution for practical agricultural deployment and scaling.
About North Carolina A&T State University
North Carolina A&T State University is a public land‑grant research university and nationally recognized HBCU in Greensboro, North Carolina, coupling significant enrollment with a mission‑driven research and innovation culture. Industry engagement is enabled by co‑located labs and pilot‑scale facilities, a research and technology park hosting corporate collaborators, and structured co‑op pipelines. Its statewide Cooperative Extension network connects campus expertise with communities and companies for field demonstrations and workforce upskilling. Located in the Piedmont Triad, the university offers convenient access to major manufacturing and logistics corridors. Research is supported by competitive federal funding from NSF, USDA, DoD, and DOE; a dedicated technology transfer office streamlines IP, licensing, and startup formation.
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