Index

• The Problem
  • Summary of the problem
• The Project
  • The Structure of a Module
  • Growth Analysis
  • Camera Structure, Leaf Counting, Height and Green Area Measurement
  • Available plant for testing
  • The irrigation system
  • Thermal Control
  • Humidity Control
  • Luminosity Control
  • The WebApp for accessing the metrics
  • The Cloud API for sending and storing metrics
• Project Diagram

The Problem

Researchers in agronomy and plant sciences often face significant challenges when it comes to accurately monitoring and studying plant growth. Manual data collection, a common practice, can lead to inconsistent measurements and subjective observations, both of which impact the reliability and precision of growth analysis. The lack of real-time monitoring also means that important changes in plant health or growth may go unnoticed, especially when critical events or fluctuations in environmental conditions occur outside regular observation periods. These limitations can introduce biases and errors, slowing down the progress of research and affecting the quality of the insights gained.

Moreover, existing greenhouses often lack adequate control over environmental factors such as light, irrigation, and temperature. Foliage that grows along the greenhouse walls can further obstruct sunlight, creating uneven conditions that complicate the study of plant growth under consistent variables. The absence of automated systems for managing and controlling these elements makes it difficult to maintain a stable environment, which is essential for producing valid and replicable results.

For researchers aiming to compare different crops or conduct long-term studies, the labor-intensive process of manually measuring growth metrics, like leaf area/counting, also adds to the workload and increases the potential for inaccuracy. These challenges highlight the need for advancements in greenhouse technology to support more precise, reliable, and efficient research in plant sciences.

Summary of the problem

• Researchers often face challenges in monitoring plant growth accurately due to manual data collection.
• There's a demand for greenhouses that make it possible to compare different crops.
• Foliage on the walls of the greenhouse can block the entry of light.
• Manual Data Collection – Inconsistent measurements lead to inaccuracies in tracking plant growth.
• Human Error – Reliance on subjective observations
• Limited Real-Time Monitoring – Without continuous monitoring, researchers may miss important changes in plant growth or health.
• Lack of Environmental Control – Difficulty in precisely controlling factors like light and irrigation
• Limited Automation – Current tools often lack the automation needed for long-term studies
• Challenges in Growth Metric Analysis – Manually measuring metrics such as leaf area or color is labor-intensive and lacks precision.

The Project

The project consists of a miniature smart greenhouse, composed of two chambers separated by a wall, each holding a plant for study. The greenhouse is a smaller-scale prototype of a larger greenhouse with bigger chambers, which would accommodate a more comprehensive statistical sampling.