Smart Farming

Team: 60

School: New Mexico Tech Upward Bound Math & Science

Area of Science: Agriculture

Interim: Smart Farming
Area of Science: Agriculture

Team Number: 60

Team Members:
Manoj Subedi­ subedimanoj122@gmail.com
Jerrel White­ WhiteJerrel@gmail.com
Alex Phommachack­ phommachack.alex@gmail.com Naomi Ramos­ ramos.naomi1016@gmail.com
Nigone Phommachack­ owenfoam@gmail.com Sponsors:
Kurtis Griess: kurtis.Griess@gmail.com
Karen Glennon: kglennon25@gmail.com
Mentors:
Sheree Lunbsford: lunsford@aps.edu
Kaley Goatcher: Kaley.Goatcher@gmail.com
Minor Morgan: minormorgan@northvalleyorganics.com Patty Meyer: pmeyer2843@gmail.com
Stephen Mcguinness­ mcguinness@aps.edu

Problem Definition­
Arable soil is the golden ticket of producing food. Arable soil is a type of soil that we are able to farm on but for a limited time. Once it’s not arable, we must search for new lands to farm in and that’s exactly the problem. Our world has little new lands to discover and that is why we are searching for alternatives. Our idea, Smart Farming, is the smart choice moving forward. Smart Farming is a way to use natural resources instead of products that negatively affect our environment. In other words, our team is finding what is better for our environment.

Coding ­
There are various ways to get into object/model oriented programing, for our project we plan to use Python. We chose Python because it is very well documented and there are lot of tools within the program that is designed for data processing on top of Python. As part of a separate project we are researching parallel computing which might be better way to process our code is to simulate environmental factors. For finding the most efficient way to farm we can use tables that help us compare and contrast between different farming conditions to see how the plants grow. Machine Learning and AI are a big buzz words within media, but they are also functional methods of creating simulations and processing data. Our goal is to be able to create realistic models and simulation through Machine Learning, this can be achieved by using pre-­made add ons to Python such as tensor flow and Python. We expect to create realistic simulations that can be used to determine the condition of farmlands and the surrounding areas.

Problem solution­
Rendering the effects of farming malpractices is a difficult thing. Simply, our goal is to try and simulate a farming model. If everything goes as planned, we will use Minecraft as a visual aid to represent all of the damages being done to the environment by farming practices. A key part to making a farming model is to make a weather/environment prediction system showing the effects on biogeochemical cycles from farming. This will be key to revealing inefficient farming practices.

Progress to date­
From our research we gathered general knowledge of farming through an organic farmer named
Minor Morgan. He gave our team his perspective and different ideas of farming. Using this data we compared and contrasted it to other ways of farming which gave us the pros of some types of farming and the flaws to other types.

Expected results­
We expect to find the best farming method that benefits the earth. The best way to farm will be decided by the energy cost of the farm. This algorithm will level the playing field among farming methods. consider energy cost, carbon footprint, productivity, types of pesticides, energy to produce product. We do in the present. We have looked into smart farming as a possible solution, not to jump the gun we are expecting to land on variation of smart/vertical farming as our final solution. We want to take a smart way to farm; using technology to create a better way to use and control our crops. We want to take every perspective of farming to gather info on the pros and cons of each way to farm so that later we can compare to other options.

References
Briseño, Elaine D. “County's Grow the Growers Program Trains next Generation of Farmers.” Albuquerque Journal, 2018.
“Carbon Footprinting Guide.” Carbon Trust, Jan. 2018, www.carbontrust.com/resources/guides/carbon­footprinting­and­reporting/carbon­footprinting/
Jordan, Amanda Ruggeri from. “Future ­ How to Use Seawater to Grow Food – in the Desert.” BBC News, BBC, 24 Sept. 2018, www.bbc.com/future/story/20180822­ this­jordan ­greenhouse­uses­solar­power­to­grow­crops
Liedtke, Michael. “Down on the Farm, Robot­Style.” Albuquerque Journal, 4 Oct. 2018, p. A12.
“Minormorgan@Northvalleyorganics.com.” Received by Minor Morgan,
Minormorgan@Northvalleyorganics.com

Team Members:

  Naomi Ramos
  Jerrel White
  Alex Phommachack
  Nigone Phommachack
  Manoj Subedi

Sponsoring Teacher: Kurtis Griess

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