Indoor hydroponic farming has become an industry changing technology that has allowed for crop growth in areas of the world where it would never be expected before. Freight Farms’ Leafy Green Machine allows for farmers to grow crops throughout the year by controlling the climate inside the farm. However, the farm is not able to predict how the climate of the farm will change based on its current sensor readings and equipment states. To allow the farmer to see how the farm will behave in the future, machine learning algorithms can utilize these readings and states to predict the future climate readings, notifying the farmer of any harmful changes. This project seeks to build a predictive machine learning model to add further measures to the Leafy Green Machine’s self-sustaining climate.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Pandey, Shivangi
• Yevchak, Steven C

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-011918-164136

Advisor

• Venkatasubramanian, Krishna Kumar
• Li, Yanhua

Year

• 2018

Sponsor

• Freight Farms

Date created

• 2018-01-19

Location

• Boston

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright