Real-time greenhouse crop monitoring with lightweight deep learning and MPLR
A novel solution combining lightweight deep learning algorithms and Multi-Packet LoRa (MPLR) for real-time greenhouse crop monitoring and management. This system enables efficient data processing and reliable image transmission to enhance precision agriculture.
Overview
Real-time crop monitoring in greenhouses is crucial for optimizing growth conditions and ensuring plant health. This solution leverages lightweight deep learning algorithms alongside Multi-Packet LoRa (MPLR) to create an efficient system for monitoring phenotypic traits and managing crop health remotely. By overcoming the challenges of computational expense and data transmission limitations, this system offers precise, real-time insights into crop conditions.
Technical specifications
- Lightweight Deep Learning: Utilizes a modified DeepLabv3+ network with MobileNetv2, achieving a mean Intersection over Union (IoU) score of 0.99 and high segmentation speeds, with R2 values of 0.91 and 0.96 for canopy diameter and biomass estimation respectively.
- MPLR Protocol: Implemented to enhance image transmission over LoRa networks, allowing efficient data transfer to a central server for processing.
- Applications: Suitable for hydroponic lettuce and strawberry crops, with demonstrated accuracy in maturity classification and weight estimation.
- Interface: Features a customizable, user-friendly interface for real-time monitoring of crop growth and health.
Technology readiness level
This solution is currently at a Technology Readiness Level (TRL) 3, indicating it has been experimentally proven in a lab environment and is ready for further development and testing in operational settings.
About Texas A&M University, College Station
Texas A&M University in College Station is a comprehensive public research university and the flagship of The Texas A&M University System, combining broad academic strengths with a strong applied‑research culture. Industry collaborates on the Texas A&M‑RELLIS campus—an integrated education, research and testing environment that supports large‑scale experimentation and proving grounds—and through the Texas A&M Transportation Institute’s facilities in Bryan‑College Station. A statewide extension network connects university expertise to companies and communities across all Texas counties, enabling rapid piloting and deployment. Research is supported by competitive federal funding from agencies such as NSF, NIH, DOE, USDA and DoD, alongside state and industry sponsorship. Texas A&M Innovation provides IP management, licensing and commercialization pathways across the system.
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