Microalgae Artificial Intelligence Network

Personalized Algal Growth Cycles

Optimizing microalgae for lipid content? Biomass? Secondary Metabolites? Our AI collects environmental data and runs experiments in a simulation. After learning, it optimizes any given photobioreactor to reach the desired outcome by adjusting PH and temperature values.

Take the quick test on the right to inform the AI how to help you best.

Meet PhycoNet

An AI-powered system that fine-tunes algae growth using real-time sensor data and physics-based models.

PhycoNet is an open‑source, autonomous control system that turns any simple photobioreactor into a self‑optimizing algae farm. It uses low‑cost sensors and artificial intelligence to continuously monitor your culture, predict growth, and automatically adjust nutrients, lighting, and pH — so you don’t have to.

Designed for citizen scientists, researchers, and small‑scale growers, PhycoNet replaces expensive industrial controllers with a modular, $50‑$150 kit that works on soda bottles, flat‑panel bags, and glass jars. The system tracks pH, temperature, light intensity, and optical density in real time, streaming the data wirelessly to a nearby computer or smartphone. A physics‑based digital twin simulates your exact culture, while an AI brain proposes safe, data‑backed experiments — and a tiny pump executes the winning action automatically.

Key features:

  • Plug‑and‑play setup – Connect the module to your Wi‑Fi using your phone’s browser (captive portal), select your algae strain and goal, and you’re ready to grow in under two minutes.

  • 24/7 autonomous control – The system senses, simulates, decides, and acts without any human intervention. It can dose bicarbonate, add nutrients, adjust LED brightness, and control a heater — all while you sleep.

  • Self‑learning memory – Every experiment and its outcome are logged into a local database. The AI retrieves similar past experiments to avoid failures and repeat successes, getting smarter with every batch.

  • Triple‑layer safety – Hard‑coded hardware clamps on the microcontroller, a mandatory physics‑based simulation gate, and strict AI output boundaries prevent dangerous commands from ever reaching your culture.

  • Open‑source transparency – All hardware plans, wiring diagrams, and software are released under the MIT license. Inspect, modify, and share freely.

  • Global network effect – Multiple PhycoNet reactors can optionally share anonymized optimisation data, so a discovery in one lab can instantly benefit growers anywhere in the world.

Technical overview:
The system consists of a sensor‑rich controller (Raspberry Pi Pico WH), a suite of low‑cost probes (pH, temperature, light, turbidity, optional dissolved oxygen), a peristaltic pump, and MOSFET/relay drivers for lights and heater. Sensor readings are published over MQTT to a local broker (Mosquitto), where a Python listener logs everything to a CSV file. A Droop‑model digital twin (with Beer‑Lambert light attenuation) simulates growth, while the AI engine (powered by a free‑tier large language model) proposes safe adjustments. Only validated commands are sent back to the microcontroller to activate the pump or change lighting.

Applications:
Grow Spirulina for food, Haematococcus for astaxanthin, Chlorella for biofuels, or any photosynthetic microorganism for research. PhycoNet is built for the biohacking community, STEM education, smallholder farmers, and decentralized science (DeSci) initiatives.

Pricing and availability:
The core module (sensors + pump + controller) costs under $50 in parts. A premium kit with touchscreen, dissolved‑oxygen sensing, and a microscope camera is available for around $150. Pre‑assembled kits and DIY build‑plans are available through our website and upcoming crowdfunding campaign.

PhycoNet is the only autonomous photobioreactor controller that combines a physics‑based safety net, an AI experiment designer, and a federated learning database — all for less than the price of a textbook. Ready to grow smarter?


Close-up of a photobioreactor with sensors monitoring algae growth under soft natural light.
Close-up of a photobioreactor with sensors monitoring algae growth under soft natural light.

Privacy Policy and Terms

© 2026 Orr Biologicals. All rights reserved.

Phyconet is an experimental open‑source project. Results will vary depending on your algae strain, reactor setup, and local conditions. We make no guarantees of specific yields. The AI is a research tool, not a certified safety device. By supporting this campaign, you’re helping us test and improve a prototype that we believe will make algae cultivation easier for everyone.

Limitation of Liability
To the fullest extent permitted by law, Orr Biologicals and its owners shall not be liable for any direct, indirect, incidental, or consequential damages arising from your use of the spirulina cultures, the information on this site, or any products derived from them. This includes, but is not limited to, illness, allergic reactions, or economic losses.

Compliance with Local Laws
Spirulina cultivation and sale may be regulated in your area. It is your responsibility to check with your local health or agricultural authority before buying or growing spirulina. We do not certify that our cultures meet any particular legal standard for food safety.

Please note that the creator of MAIN is a minor operating this project

as an educational and non‑commercial open‑source initiative.

Any purchases, donations, or transactions are processed through

third‑party platforms (e.g., Experiment.com, BTCPay Server) and are

subject to those platforms' terms and age requirements. By supporting

this project, you acknowledge that you are engaging with an open‑source

community effort, not a legally incorporated business.