Modular Smart Incubator System with AI + Camera + IoT

1.1 Base unit — the ecosystem brain

The base unit provides the computational and connectivity backbone for every chamber in the system:

• Main controller and processing
• Network connectivity (Wi-Fi / Bluetooth)
• User interface (integrated touch display + mobile app)
• Cloud synchronization and secure data storage
• AI processing engine interface to cloud models

This central controller auto-detects attached chambers, applies appropriate templates, and orchestrates synchronized workflows.

1.2 Add-on chamber modules

Multiple chamber types can be docked to the base unit via a universal interface enabling power, data, and automatic detection:

• Standard chamber — microbiology (37°C), yeast culture, basic workflows
• Shaker module — orbital shaking + temperature control for bacterial growth, protein expression, and liquid culture incubation
• Humidity-controlled module — plant tissue, fungi, environmental growth simulation
• CO₂-enabled module — mammalian cell culture workflows
• Refrigerated module — cold incubation experiments (+4°C to +20°C)
• Light-controlled (photobiology) module — seed germination, algae growth, circadian rhythm studies

Each chamber supports:

• Data communication and health reporting
• Automatic detection and configuration
• Software-level prediction and template matching

2. Time-lapse & remote viewing

Visual data is captured with tunable schedules and rules:

• Fixed time intervals
• Application-specific templates
• User-defined triggers and events

Users can review:

• Colony formation and morphology
• Color and turbidity changes
• Growth curves and expansion rates
• Sample stability over time

Live feeds and the latest frames are available via mobile and desktop applications for real-time inspection from anywhere.

2.1 Vision-based analysis features

Embedded AI models turn images into quantified insights:

• Colony or culture growth prediction
  • Tracks colony size and edge spreading
  • Monitors optical density changes
  • Follows fungal hyphae expansion
• Contamination detection
  • Unusual colors or texture changes
  • Multiple colony types emerging
  • Early fungal contamination
  • Moisture imbalance and condensation patterns
• Reaction & workflow monitoring
  • PRF/PRP clot formation & maturity detection
  • Template-based visual comparisons
  • Plant leaf stress, wilt, yellowing, and mold detection
  • Food lab spoilage and microbial bloom recognition
• Pattern-deviation alarms
  • Per-template “normal trajectory” baselines
  • Alerts when observed images deviate from expectation

3.1 Per-chamber sensor data

Users can monitor critical conditions for each chamber from a unified dashboard:

• Temperature and humidity
• CO₂ concentration and gas control
• Airflow and mixing
• Vibration (for shaker modules)
• Door/open events and access history
• Light cycles and intensity profiles
• Heating and cooling performance metrics

All parameters are visible in real-time, with historical trends and export-ready logs.

3.2 Remote control capabilities

Authorized users can remotely:

• Change temperature setpoints
• Adjust humidity and CO₂ levels
• Start/stop shaker movement
• Modify light cycles and intensity
• Trigger manual image capture
• Perform chamber-specific resets and diagnostics

This is especially valuable for multi-site facilities, offsite researchers, remote diagnostics, and clinical monitoring scenarios.