I. What is your solution? What is the goal of the project?The goal of this project is to implement machine learning into agriculture to make growing food more efficient and easier to do. By implementing A.I. into agriculture, farmers won't have to work as much, their jobs will be easier, planting processes will be faster, and more people that need food can get it because the efficiency of growing food is increased; this will reduce the price of food to increase efficiency.
0 Comments
II. Where in Hawaii would this be located?This solution will be implemented on the fields owned by Mahi Pono. Their farms would require less maintenance and overall increase the speed at which the work is being done because of the implementation of artificial intelligence. Increased work speed means more fruits and vegetables to sell and less people being hungry.
III. Show a timeline of your project.Artificial intelligence for agriculture is currently in a development and training stage. Around the 2030s we will likely see machine learning on farms be used widely. It is possible after a while that the computers will take over farming from the humans, but this is likely to be far in the future.
IV. Who do you need for this project?We would probably try to target small poorer farms. Big industrial farmers use machinery with working widths of 30 meters or more. The higher the working widths the higher chances of over fertilizing fields. Smaller farms are usually more local than larger farms. If we give these smaller farmers Artificial Intelligence, they could produce more foods for their local community and reduce the transportation needs.
V. What is your plan to implement your solution?Our plan is to get farmers to use machine learning in their agriculture. Small steps like downloading an app to detect disease your plant can have will start the switch to A.I. Having machine learning in a farmer's fields would be like having an anonymous tractor driving on your field doing the tasks you would normally be doing to make profit from your business/selling fruits, vegetables, and starches. We would try to get lots of farmers to switch to machine learning in agriculture to better monitor their farms, make the best decisions to keep their land healthy, and to increase the rate of plant growth.
VI. What is the cost to build and implement this project and where are you going to get the funds from?It will be pretty costly to implement machine learning into not industrialized farms. By the year 2025, over $15 billion will be spent on technologies that use artificial intelligence in agriculture. Funding for these projects would come from farmers, big tech companies, and the government. The cost of creating a farm that runs on artificial intelligence is unknown because these farms do not currently exist.
VII. How much Co2 will be sequestered or prevented?Using machine learning in agriculture can prevent lots of Co2 from going into the atmosphere. Using machine learning will make farming much more efficient, but the amount of Co2 prevented from being in the atmosphere is unknown. The Co2 would be prevented from going into the atmosphere by reduced transportation needs and by not need as many nutrients to be created.
VIII. Analysis of carbon and climate change data.Lots of carbon emission come from the agriculture industry. Currently, around 10-11% of Co2 emission in the United States are from agriculture. This contributed around 669 million tons of Co2 to the atmosphere in 2019; as demand for food grows, the greenhouse gases emitted by agriculture will only increase.
IX. Potential benefits and drawbacks of your solution?Drawbacks and benefits of artificial intelligence/machine learning do exist. Benefits of machine learning/artificial intelligence are increased efficiency and avoids waste, Artificial intelligence can monitor the environment to find weather patterns ahead of time, currently we can find the wind patterns up to 36 hours before they appear. Learning these patterns gives us time to respond to these events. In order to develop, machine learning needs to establish a curve, this curve usually takes several years to develop a model for the A.I. Using computers for several years requires lots of energy, but powering the computers will not have a carbon-footprint if using inexhaustible energy resources.
|