Grok The Fly Trap

Version 0.1.1.0

Development Roadmap

Development roadmap for the Grok The Fly Trap system. Phases are implemented incrementally with each version building on verified functionality from previous releases.

Beta: Current Development Milestones

Completed Foundation Work

API Infrastructure

  • FastAPI server operational with RESTful endpoints
  • Environment setup and dependency management configured
  • Structured error handling with proper HTTP status codes

Read Operations [Complete]

  • Sensor data retrieval endpoints verified with real hardware
  • Controller listing and status monitoring
  • Port status and device type detection
  • Error handling with appropriate HTTP status codes for missing resources

Device Control [Complete]

  • Single and batch control endpoints implemented
  • Control persistence verified across device modes
  • Multi-mode support foundation (On, Off, Auto, VPD, Timer, Cycle, Schedule)
  • Validation guardrails for control keys and value ranges

Safety & Validation [Partial]

  • Unknown control key rejection with early validation
  • Value range validation for all control parameters
  • Read-only control protection
  • Auto mode with humidity triggers tested and verified
  • [In Progress] Additional mode-specific controls testing (VPD, Timer, Cycle, Schedule)

AI Integration [Partial]

  • Grok orchestrator implemented with tool-based API integration
  • VPD management automation (maintains 0.89-1.0 kPa range)
  • Decision engine for automated control adjustments
  • [In Progress] API usability testing and response tuning
  • [In Progress] Additional Grok-driven use cases

Livestream Overlay [Complete]

  • Real-time dashboard deployed
  • Sensor telemetry display (temperature, humidity, VPD)
  • Trap status visualization with digestion progress tracking
  • System metrics and device control status
  • Computer vision output placeholders
  • Responsive design for streaming integration

Version 1.0: Foundation & Core Integration

Core Objectives

  • Establish RESTful API infrastructure for AC Infinity controller integration
  • Implement sensor data retrieval and device control capabilities
  • Integrate AI-driven decision making via Grok API
  • Deploy real-time livestream overlay for monitoring

API Foundation

  • [Complete] Read-only sensor endpoints, device status monitoring, and control interfaces
  • [Complete] Structured error handling with proper HTTP status codes
  • [Complete] Device type detection and port management

Device Control

  • [Complete] Multi-mode support (On, Off, Auto, VPD, Timer, Cycle, Schedule) with validation guardrails
  • [Complete] Batch control operations for efficient device management
  • [Complete] Control persistence verification

AI Integration

  • [Complete] Grok orchestrator for intelligent automation and VPD management
  • [Complete] Cost-efficient API usage with batch processing and rate limiting
  • [Complete] Tool-based integration for sensor reading and conditional control

Livestream Overlay

  • [Complete] Real-time dashboard displaying sensor telemetry, trap status, and system metrics
  • Computer vision output integration points
  • [Complete] Responsive design optimized for streaming platforms
Status: In Development

Version 2.0: Automation & Monitoring

Core Objectives

  • Implement time-series data collection and historical tracking
  • Deploy scheduling and rule-based automation systems
  • Integrate soil moisture-based watering automation
  • Enable trap system integration and digestion cycle tracking

Historical Data Logging

  • Time-series sensor data storage
  • Trend analysis and reporting dashboards
  • Data visualization and export capabilities

Alert System

  • Threshold-based notifications via email, SMS, or push services
  • Configurable alert rules and escalation
  • Real-time monitoring of critical parameters

Automated Scheduling

  • Timer-based schedules for devices
  • Rule-based triggers with if-then logic
  • Sunrise/sunset synchronization for Phoenix location
  • Heater safety rules and auto-shutoff

Watering Automation

  • Soil moisture threshold triggers
  • Automated watering cycles with configurable durations
  • Water usage tracking and reporting
  • Per-plant solenoid control

Trap System

  • Integration with image recognition models
  • Dynamic trap detection via computer vision
  • Digestion cycle monitoring and progress tracking
  • Feeding automation and trap state recognition
Status: Planned

Version 3.0: Advanced AI & Computer Vision

Core Objectives

  • Deploy predictive analytics and trend-based forecasting
  • Integrate computer vision systems for plant health monitoring
  • Expand third-party integrations and extensibility
  • Implement advanced diagnostics and optimization tools

Predictive Analytics

  • Trend-based predictions for environmental adjustments
  • Preemptive system responses to forecasted conditions
  • Weather-aware forecasting with Phoenix-specific optimizations
  • Predictive watering based on soil trends and external weather data

Computer Vision Integration

  • RGB and MSI camera systems for plant health assessment
  • Deficiency detection and automated response triggers
  • Plant health overview combining sensor data with visual analysis
  • Trap state recognition and dynamic trap detection

AI-Driven Insights

  • Advanced Grok integration for optimization recommendations
  • Intelligent decision-making with cost-sensitive API usage
  • Image processing for growth pattern analysis
  • Automated insights and system tuning suggestions

Third-Party Integrations

  • Webhook support for real-time event pushes
  • Integration with other grow control platforms via REST APIs
  • Weather API integration for location-specific automation
  • User profile management with custom presets
  • Configuration backup and restore capabilities

System Diagnostics

  • Firmware update management for controllers and devices
  • Error detection and troubleshooting automation
  • Energy consumption tracking and efficiency reports
  • Simulation/dry-run mode for testing automations
  • System health auditing and performance monitoring
Status: Future Development

Technical Architecture

Built on FastAPI with RESTful endpoints for sensor data retrieval and device control. AI integration via Grok API with rate limiting and batch processing for cost optimization. Real-time dashboard serves as primary interface; web dashboard with historical data access planned.

Development follows a phased approach with each version building on verified functionality. Input validation and safety guardrails implemented at each stage to ensure system reliability and prevent unintended device operations.

Key Technologies:

  • • FastAPI for RESTful API infrastructure
  • • Python with async/await for efficient I/O operations
  • • Grok API (xAI) for intelligent automation
  • • AC Infinity Cloud API integration
  • • Real-time web interfaces with polling and future WebSocket support