Automated greenhouse monitoring system using machine learning
An innovative greenhouse monitoring system using low-cost cameras and machine learning for real-time plant health assessment. Ideal for large-scale greenhouse operations, it offers scalable, cost-effective monitoring and early intervention capabilities.
Overview
This automated greenhouse monitoring system leverages low-cost cameras and advanced machine learning models to provide real-time insights into plant health, development, and space occupancy. By capturing RGB images, this system allows for reliable estimates of plant status, facilitating early intervention and reducing manual inspection efforts. Designed for scalability, it supports large greenhouse operations, offering a cost-effective and efficient solution for plant monitoring.
Technical specifications
- Low-cost cameras: Utilizes cameras priced at approximately $100 each, making it an affordable option for extensive greenhouse coverage.
- Machine learning models: Pre-trained on RGB images to estimate plant health, growth, and space occupancy.
- Real-time visualization dashboard: Displays data and alerts users for early intervention.
- Wireless image transmission: Images are transmitted over WiFi to a local computer for processing.
- Scalable architecture: Suitable for large greenhouse environments.
Technology readiness level
The system is at Technology Readiness Level 5, with a functional prototype ready for validation. The project will be validated over a 6-month period, involving case studies and technical reporting to refine and confirm its capabilities in a real-world greenhouse setting.
About The University of Melbourne
The University of Melbourne is a comprehensive institution spanning STEM, health and clinical practice, business and law, and the creative and social disciplines. Co‑located hospital and research precincts, together with an inner‑city innovation ecosystem, place companies, startups, and researchers in shared labs, prototyping spaces, and studios. Engineering and technology programs connect with advanced manufacturing facilities, while structured industry projects and placements link partners with talent and translational problem‑solving. Work is supported by competitive funding from the Australian Research Council and the National Health and Medical Research Council, with additional backing from state programs and industry partners; a dedicated technology transfer office manages IP, licensing, and startup formation.
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