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Future Work

This document outlines the planned features and improvements for the GreenThumb project.

Short-term (Current Phase)

Physical Construction

  • [ ] DWC Greenhouse Construction

    • Build the physical Deep Water Culture greenhouse
    • Install aeration system (air pumps, air stones)
    • Set up reservoir and growing stations

  • [ ] Cherry Tomato Cultivation

    • Start cherry tomato cultivation for data collection
    • Establish baseline growth metrics
    • Document environmental conditions

Hardware Integration

  • [ ] pH Sensor Integration

    • Add pH sensor to monitor nutrient solution acidity
    • Target range: 5.5-6.5 for hydroponics

  • [ ] EC Sensor Integration

    • Add electrical conductivity sensor
    • Monitor nutrient concentration
    • Target range: 1.5-2.5 dS/m

  • [ ] LED Control

    • Full-spectrum LED panel integration
    • PWM control for light intensity
    • Automated photoperiod management

  • [ ] Water Pump Control

    • PWM-controlled circulation pump
    • Automated nutrient delivery

Software Development

  • [ ] Cloud Database Sync

    • Daily sync to Supabase PostgreSQL
    • Handle offline-first with eventual consistency

  • [ ] Image Storage

    • Upload photos to Cloudflare R2
    • Optimize storage costs

  • [ ] Computer Vision (Basic)

    • Plant detection in images
    • Leaf area estimation
    • Color analysis for health monitoring

Medium-term (Until August 2026 - PIBITI End)

Research Focus

The primary goal during the PIBITI period is consistent and precise data collection for future machine learning models.

Data Collection

  • [ ] Reliable Sensor Data

    • Continuous environmental monitoring
    • Automated data validation
    • High data quality standards

  • [ ] Image Dataset

    • Systematic photo collection
    • Consistent lighting and angles
    • Proper labeling and metadata

Machine Learning Preparation

  • [ ] Dataset Curation

    • Clean and organize collected data
    • Create training/validation splits
    • Document data characteristics

  • [ ] Initial Model Experiments

    • Prototype growth prediction models
    • Test anomaly detection approaches
    • Validate optimal conditions patterns

Long-term (After PIBITI)

Fleet Management

  • [ ] Device Registration System

    • Register multiple Raspberry Pi devices
    • Central management dashboard

  • [ ] Multi-Greenhouse Support

    • Monitor multiple greenhouses from single interface
    • Aggregate data visualization

Mobile Application

  • [ ] React Native App
    • Real-time monitoring
    • Push notifications
    • Remote control

Machine Learning

  • [ ] Growth Prediction

    • Train models on collected PIBITI data
    • Predict harvest time based on conditions

  • [ ] Anomaly Detection

    • Detect unusual sensor readings
    • Alert on potential problems

  • [ ] Optimal Condition Discovery

    • Identify best conditions for each plant species
    • Automated recommendations

Research & Publications

  • [ ] Research Paper
    • Publish findings on growth optimization
    • Share insights from PIBITI data

Project Timeline

gantt
    title GreenThumb Development Timeline
    dateFormat YYYY-MM

    section Current (2025)
    Software architecture    :done, 2025-06, 2025-12
    Software development     :active, 2025-09, 2026-03

    section Short-term
    Component acquisition    :2025-12, 2026-02
    DWC construction        :2026-01, 2026-03
    Cherry tomato start     :2026-02, 2026-04
    pH/EC integration       :2026-03, 2026-05

    section PIBITI (Until Aug 2026)
    Data collection         :2026-04, 2026-08
    Dataset curation        :2026-06, 2026-08

    section Post-PIBITI
    ML models               :2026-09, 2027-03

Last updated: December 2025