SpiCEN – Micro Algae-based Carbon Emission Neutralizer

A next-generation IoT-enabled photobioreactor engineered to neutralize carbon emissions using artificial photosynthesis and microalgae cultivation.

SpiCEN Hero Image

My Role

Research & Patent Contributor

Category

Patent Case Study

Filed

May 9, 2023

Tools & Tech

IoT Sensors · LED Arrays · Artificial Photosynthesis · Microalgae Systems

The Problem / Objective

Industries emit vast quantities of CO₂ with few scalable bioconversion options. Traditional photobioreactors struggle with uneven light distribution and inconsistent nutrient supply, reducing productivity.

Objective: Develop a high-efficiency microalgae-based carbon neutralizer with automated monitoring and artificial photosynthesis to maximize algae productivity and carbon capture.

Discovery & Research

The challenge was maintaining uniform light exposure and ideal growth conditions. The team discovered that cuboidal LED-distributed designs enabled even illumination across all algae cells.

Key Insight: Multidirectional LED lighting ensures uniform photosynthesis, significantly boosting growth efficiency compared to cylindrical PBRs.

  • Studied Spirulina growth under controlled environments.
  • Integrated real-time sensors for pH, turbidity, and nutrient levels.
  • Designed auto-adjusting nutrient and CO₂ flow systems.

Solution & Design Process

SpiCEN features a cuboidal photobioreactor with LED arrays mimicking daylight. IoT modules continuously monitor water chemistry and environmental variables, optimizing growth without manual intervention.

Low-fidelity mockups High-fidelity mockups

Architecture & Technical Challenges

A major challenge was designing sensor calibration that remained accurate across varying algae densities.

Technical Challenge: Turbidity changes distorted sensor readings, requiring adaptive calibration algorithms for stable automated control.

Analysis & Strategic Recommendations

SpiCEN is ideal for industries seeking natural carbon-neutralizing systems.

Recommendation: Implement an AI-based growth prediction model and expand modular designs for multi-unit deployments.

Results & Impact

High

CO₂ Absorption Efficiency

24×7

Automated IoT Monitoring

Uniform

Photosynthetic Illumination

Learnings & Next Steps

Lesson Learned: Uniform light distribution and real-time sensing are the largest contributors to consistent algae growth.

Next steps:
• Integrate ML-based prediction
• Deploy in industrial CO₂ zones
• Enable biomass harvesting automation