situation report

We have selected a Hydroponic Farm in South East Austin for our area of operation. This location is an excellent environment for growing the seeds needed to continue proper research, develop different solutions for remote system operations and a perfect fit for an office for future production.

Staff needed to continue project (as of March 2, 2017 – pre-crowd-source bootstrap) :

  1. Research and Planning

    runway for
    runway for
  2. Prototype – R&D
  3. MVP – feature definition
  4. User Experience
  5. Library & repository
  6. Cognitive computing
  7. Greenhouse
  8. Shipping Container(s)
  9. Virtual Reality
  10. Back-end infrastructure
  11. Socialization
  12. Crowd-sourcing
  13. Forums


How do we get there?

MIT-OpenAg Community
MIT-OpenAg Community
openAg Community
openAg Community
  1. Join the OpenAgriculture community at M.I.T.
  2. Employ Veterans – Hire Veterans to build and maintain Automated Enclosed Gardens.
  3. Mentor Youth Program – Start supporting current youth mentoring programs in local communities through Automated Enclosed Garden launching and maintenance.
  4. Community Gardens – Employee Veterans and Farmers to collaborate in Automated Enclosed Gardens as well as existing rural farms that can cooperate in joint food cultivation ventures.
  5. Sharecropping for food banks – Working with local food banks in trade off for fresh produce, could cultivate a relationship with those who receive the healthy food, who in turn, could also work in the gardens that produce it.
  6. Farm to Table Solutions – Minimizing the Farm to Table footprint will help food desert areas in urban environments continue to provide fresh produce with less travel time from the farm to the kitchen table.
  7. Farmer’s Markets – Partnering with local farmers who can sell their produce locally at venues that cater to organic farm produce, whilst allowing a self sustaining market rate, that is set on the conservation properties gained in enclosed garden environments, can help farmers see the benefits of Enclosed and Automated Food production.
  8. Restaurants – Local restaurants can purchase these units to be housed on site at their fine dining establishment and have previews of their food grown in house, from seed to table, specifically for the customer’s dining experience. Labeling a seed with an ip address and Monitoring it Live can be a novel way to ensure the end customer is educated as to where the food came from.
  9. Universities– Academia who already have existing gardens for Horticulture and Agriculture courses would benefit greatly from sharing data with other Universities to communicate the diversity of problems and solutions the entire globe are researching. The end goal is to grow the best, most healthy and sustainable food ever.
  10. Hospitals – Modern Medicine is in need of plant nutrition recipes prescribed to their human patients for maximum healing and symptom problem solving and disease causation. Knowing what goes into the plant and what the human recipient needs nutritionally is valuable for maximum health. Having specific foods that target the needs of a malnourished person that are grown in a custom recipe of nutritional value is the future of medicine. Growing medicine with machine learning and predicting potential plant values for food is the end goal for use in Hospitals. Enter in symptoms into the User Interface of the application, machine learning predicts a suggested diet, specific foods are recommended, and if grown in the patients area, can be attained at a local garden. If no food is available in the area of recommendation, a recipe can be made for the patient to grow their own food in an Automated Enclosed Garden or partnering organic garden.

Building a Recipe

scalability & infrastructure

MIT foodcomputer recipe ux
M.I.T.’s Open Ag Food Computer

“Inside of a Food Computer, climate variables such as

  • carbon dioxide,
  • air temperature,
  • humidity,
  • dissolved oxygen,
  • potential hydrogen,
  • electrical conductivity,
  • root-zone temperature, and more can be controlled and monitored.

Usage specifications such as

  • operational energy,
  • water use,
  • and mineral consumption can also be monitored and adjusted through, electrical meters, flow sensors, and controllable chemical dosers throughout the growth period.

The complete set of conditions throughout a growth cycle can be thought of as a climate recipe, and each recipe produces unique phenotypic expressions, or physical qualities in different plants.”

MIT foodcomputer recipe
MIT foodcomputer recipe

“Plants grown under different conditions may vary in color, size, texture growth rate, yield, flavor, and nutrient density.

Food computers could be used program biotic and abiotic stresses, such as an induced drought, to create desired plant-based expressions.

It would even be possible to monitor existing natural climates and program them into downloadable recipes that could be shared around the globe.

With the creation of climate recipes, food computer users can import successful climates that have been created, tested, and perfected by other users.

The recipes can be customized and optimized for different taste or yield preferences and for various food production needs.” – Open Ag Climate Recipes – Massachusetts Institute of Technology


food recipes tradeoff
food recipes tradeoff

“Beyond food, we are now applying this research in other industries. A system that can model human preferences and generate new ideas has many applications outside of food and the opportunity to transform customer experience.

Truly superior customer experiences are based on perception—appealing taste,

appearance and design, to name a few—and represent a major differentiator in a variety of industries, including retail, consumer goods, hospitality and travel.

As companies race to bring new products to mark computational creativity can accelerate how quickly they can bring products to market, reduce the cost of R&D, while helping them design what differentiating features should be prioritized for competitive edge.” – Cognitive Cooking Fact Sheet – IBM


automated greenhouse technology

workflow predicts whole plant and individual organ growth data Input
workflow predicts whole plant and individual organ growth data Input

Being able to predict future growth with Tradeoff Analytics – “Trade-offs, by which we mean exchanges that occur as compromises, are ubiquitous when land is managed with multiple goals in mind. Trade-offs may become particularly acute when resources are constrained and when the goals of different stakeholders conflict (Giller et al. 2008).

In agriculture, trade-offs between output indicators may arise at all hierarchical levels,

  • from the crop (such as grain vs. crop residue production),
  • the animal (milk vs. meat production),
  • the field (grain production vs. nitrate leaching and water quality),
  • the farm (production of one crop vs. another),
  • to the landscape and above (agricultural production vs. land for nature).
    An individual farmer may face trade-offs between maximizing production in the short term and ensuring sustainable production in the long term. Within landscapes, trade-offs may arise between different individuals for competing uses of land…

Understanding the system dynamics that produce and change the nature of the trade-offs is central to achieving a sustainable and food secure future.” –Measurement Methods for environment–productivity trade-off analysis in agricultural systems
M.T. van Wijk3, h.J. Klapwijk1,2*, Todd S. Rosenstock4, Piet J.A. van Asten2, Philip K. Thornton5 and Ken E. Giller1


data collection and recipe variables

Neural network example
Neural network example

By collecting and aggregating the automated garden’s data, a grow recipe can be tweaked and shared with a community..

A grow recipe incorporates the variables required to grow a specific plant. Some of the variables that would be included:

  • what nutrients/amendments are used
  • light cycles
  • environmental temperatures
  • root zone temperatures
  • water temperatures
  • humidity
  • C02 levels.


Unique Opportunities

AEMC (Advanced Environmental Monitoring and Control)
AEMC (Advanced Environmental Monitoring and Control) Bioregenerative Life Support project at NASA is using Neural Network to control the on board green machine and keep it humming at peak efficiency.

There are several applications that already use automated greenhouse technology.

There is no need to re-invent these systems for what they are designed to do, which is mostly grow lettuce, tomatoes and other hydroponic favored varieties. Hydroponics is the easiest method to get Organic Certified, and is the most common method for large scale food production, which enables food to stay more fresh longer, thus spending a longer time in the supply chain.

What is needed is a safe, secure, affordable, and consistent way to log / interact with the greenhouse data that is produced from the length of the food’s production.

The Next Generation of Automated Greenhousing

US botanic gardens Washington DC 2016
US botanic gardens Washington DC 2016

By collecting and aggregating the automated garden’s data, a grow recipe can be tweaked and shared with a community.

A grow recipe incorporates the variables required to grow a specific plant. Some of the variables that would be included:

  • nutrients/amendments which are used
  • light cycles
  • environmental temperatures
  • root zone temperatures
  • water temperatures
  • humidity

Task & Purpose

The system’s scalability is key in providing personal as well as commercial applications for automated gardening.

Building a customized set of different sized gardens for home and commercial use:

  • Window Herb Garden
  • Backyard Greenhouse
  • 20’ Shipping Container
  • 40’ Shipping Container
  • Commercial Nursery