Barn Owl

Grayson Honan posted an update — Dec 20, 2016 05:18 PM EST

Update #7 Final Update

Here are our video links:

• Barn Owl - Sensor Demo
• Barn Owl - Camera Slider Demo
• Barn Owl - App Demo

And here is the link to our GitHub repo:

https://github.com/grahonan/Barn-Owl

Grayson Honan posted an update — Nov 22, 2016 01:57 AM EST

Update #6 Pre-Demo Day

Here's a quick video showing our working greenhouse for Demo Day 1:

After spending several hours in windy 40ºF weather, it was a big relief to see our system working as intended. We'll let the video speak for itself!

Although not shown in the video, you can rest assured our graphs now have titles and axis labels :)

This GUI will continue to evolve as we add features for Demo Day 2.

Grayson Honan posted an update — Nov 21, 2016 08:58 AM EST

Update #4 Our Front End

Using Python, we've created a front end for controlling and monitoring our greenhouse.

Two Python scripts power the "brains" of our greenhouse -- one script acts as a server passing information to and from the greenhouse, and the other script generates the GUI you see above. The GUI script allows users to control the greenhouse directly (putting the greenhouse into manual mode for various inputs to our system), but it also drives the automation of the greenhouse. Input data from the greenhouse are regularly checked and the system sends the correct state back.

Above is a quick demonstration of our server receiving real temperature data and our GUI graphing it in real-time.

Grayson Honan posted an update — Nov 17, 2016 12:25 AM EST

Update #4 Purchases: Seeds, Soil, and Heating

One of our goals with this project was to create a greenhouse that would allow plants to grow regardless of the weather outside. Freshly planted seeds are especially sensitive to their environment.

Here you see the seeds we selected for growing: broccoli, Bibb lettuce, and kale. In addition to the seeds, we purchased a 70 pound bag of Miracle Grow soil to refresh the current soil in the greenhouse and a small outdoor forced-air heater. The heating will automatically turn on and off with our automated gardener program.

Grayson Honan posted an update — Nov 17, 2016 12:15 AM EST

Update #3 Front End Options

We've gone through several revisions of our front end system, and along the way we've learned a lot about what works and what doesn't!

We've set up EC2 instances on Amazon and torn them down, we've implemented tests in Node.js, Matlab, and most recently, Python -- at one point we even thought we'd use a PostgreSQL database, so we went and learned about databases. In short, we've touched on quite a few possible implementations in a short period of time.

This was one of our first attempts at graphing live data from a Photon. We liked Node.js, but we're unsure how well it would handle some of the image processing we'll need to do for NDVI.

We will have a more thorough post about our final front end in the future.

Grayson Honan posted an update — Nov 16, 2016 11:48 PM EST

Update #2 Sensor Boards

Here's quick peek at our soldered sensor boards. These were created by cutting a larger protoboard into 4 pieces and soldering all the sensors and components on.

Our system will handle four plants simultaneously, so we'll have four of these boards in the greenhouse. Each board has temperature, light, and humidity sensing capabilities.

Grayson Honan posted an update — Oct 23, 2016 09:35 PM EDT

Update #1 NDVI Data Collection

We met with Jnaneshwar Das (JD), our customer for Barn Owl, to discuss the state of the greenhouse and previous progress. JD suggested we use NDVI (https://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index) to measure whether our plants were stressed or healthy, and so we’ve spent some time collecting data on healthy and unhealthy leaves to determine if NDVI will work for our project. Below you’ll see the leaves we used for our data collection:

From left to right, the samples are two leaves from a citrus tree with fruit, two leaves from a citrus tree without fruit, and two leaves that had fallen off the plant (assumed to be a good analog for “unhealthy”). Below is a sample of the spectrometer data we collected:

The spectrum shown is for healthy leaf from a tree with fruit. We are in the process of purchasing camera filters and doing an NDVI calculation using cameras as well. We plan to use a two camera setup for our final implementation, but this initial data collection will serve as a proof of concept.

Grayson Honan posted an update — Oct 23, 2016 09:27 PM EDT

Update #1 NDVI Data Collection

We met with Jnaneshwar Das (JD), our customer for Barn Owl, to discuss the state of the greenhouse and previous progress. JD suggested we use NDVI (https://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index) to measure whether our plants were stressed or healthy, and so we’ve spent some time collecting data on healthy and unhealthy leaves to determine if NDVI will work for our project. Below you’ll see the leaves we used for our data collection:

From left to right, the samples are two leaves from a citrus tree with fruit, two leaves from a citrus tree without fruit, and two leaves that had fallen off the plant (assumed to be a good analog for “unhealthy”). Below is a sample of the spectrometer data we collected:

The spectrum shown is for healthy leaf from a tree with fruit. We are in the process of purchasing camera filters and doing an NDVI calculation using cameras as well. We plan to use a two camera setup for our final implementation, but this initial data collection will serve as a proof of concept.

Nikheel V Savant started this project — Oct 23, 2016 06:49 PM EDT

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