Weed Warden Updates
Author: Liam Duncan, Brendan Miller, Colton Shaw, and Alyssa Berquist
Update
The software has been updated to the latest release of Loom. The SD stores data for the current light state, NDVIB, EVI, and PSND values. The current light state allows us to know if the IR light was on or off. The device is being tested on a wagon with a shade cover. We are only using one IR light, but that may change with more testing. Details on the NDVIB, EVI, and PSND can be found here: Possible Indices Used on Weed Warden
We are testing the minimal amount of green that the sensor is able to detect over a dirt landscape. We are also testing if an interchanging an IR light and testing other possible indices for any notable differences.
An image of a recent testing setup can be seen above. We are using a large whiteboard to provide additional shade cover. The sensor is elevated three feet to match the requirements. The IR light is turned on for one data collection cycle then is turned off for a data cycle and repeats. Currently, we are unable to detect plant life a quarter in diameter.
Author: Alyssa Berquist, Brendan Miller, Colton Shaw, and Zachary McLaughlin
Update
Due supply chain issues caused by COVID-19, many of the necessary components needed to upgrade our second Weed Warden unit have been delayed. Until the shipments for these parts come in, this unit will be on standby. Similarly, the PCBs have yet to arrive. Access to the machine shop has been restricted until recently, so adjustments to the enclosure will be made once permission is granted. Without the ability to further prototype our units, our focus shifted towards en masse data collection and testing polarized film in combination with the triad sensor.
In this experiment, we examined the effect of polarized film on the spectral triad sensor. Interest in the use of polarized film for the Weed Warden started due to the use of edgebands in NDVI calculations, with a secondary interest in preventing saturation. Polarized film blocks out certain electromagnetic spectrums (light) by absorbing different wavelengths depending on the angle of the films in relation to each other. The figure above animates this process. Theoretically, by adjusting the angle between two pieces of film, the amount of light blocked can vary.
The most surprising finding was that the edgebands (blue and NIR) spectrums on the 45° film were increased, whereas on the other films they decreased the edgebands but were still the closest values to 0. The rest of the visible color spectrum was substantially blocked from the spectral sensor, with one of the more absorbed wavelengths (730nm) being reduced by ~80%, ~50%, and ~65% in the 0°, 45°, and 90° films, respectively.
These films should be used in conjunction with the spectral sensor when in need of higher weighted spectral value for the green wavelength of 585nm, less weighted spectral value for some red, NIR, and non-585nm green wavelengths, and/or inflating the outermost edgebands: 430nm, 850nm, 900nm, and 940nm. When choosing which of the three films to use, the average absorptions should be considered, with ~20% increments from lowest to highest film absorption: 45°, 90°, 0°.
Author: Brendan Miller, Zachary McLaughlin, Alyssa Berquist, and Colton Shaw
Update
Creating a watertight sensor housing has been the focal point of mechanical development. The 3D model, pictured to the right, is in the process of being manufactured and has had a series of iterations with minor tweaks 3D printed before testing for water tightness.
The current iteration of the case, once assembled, will be tested for water tightness. The lid of the case is to be made out of acrylic, and requires a routed groove to fit an o-ring to prevent water from leaking in through the lid. Routing this groove into the plastic requires a milling machine, which we do not have access to during the current COVID-19 pandemic. Nonetheless, we are still testing the housing with a temporary 3D printed version of the lid, pictured next to the acrylic lid.
Overall, progress on the sensor housing is promising despite some setbacks due to COVID-19. Temporary workarounds are allowing us to move forward on making the best design possible for the Weed Warden project. Pictured to the right is the housing unit assembled without the lid and electronic furnishings.
A custom PCB was designed to be able to house connectors for the Triad sensor and the TTL sensor. This PCB would be attached to an Adafruit Feather M0 board and an in-house PCB called Hypnos for power and data logging functionality. The board is fairly simple, as noted by its simple task, but it provides a substantial benefit in easing the complexity of the system. With this board, the Weed Warden would be simply a plug-and-play system that can easily be disassembled, connected, and handled. Before, the Weed Warden had made use of up to six boards with differing functionality and loose connections purely soldered on. There was no relative ease of plugging in sensors and the system itself provided difficulty in understanding what each board did and how to operate them. The form factor of this previous system was also very cumbersome and occupied a large amount of space within the housing. This new system, with the new PCB and the Hypnos/Feather combination should allow for a smaller form factor, ease in understanding and handling, and a more efficient system.
We are currently determining whether a normalized difference vegetation index (NDVI) would help detect live green vegetation. To test this theory, the Weed Warden will be held over areas of grass about three feet off of the ground. The device will be sensing during a long interval, and it will collect data on 30-minute intervals.
The individual wavelengths measured by the triad sensor will be summed up, then each wavelength will be divided by the total wavelength. The NDVI is calculated by summing the infrared bands (730nm and 760 nm) and the blue bands (435nm and 460nm), then subtracting the red bands (645nm and 680nm). This value is then divided by the sum of the infrared, blue, and red bands. The acceptable NDVI range will vary depending on the total amount of light received by the sensor.
Author: Brendan Miller, Colton Shaw, and Alyssa Berquist
Update
An initial design for the case has been printed. We are now adding the TSL 2591 light sensor to measure the amount of sunlight while the spectroscopy sensor continues to read the light reflected from the ground. The data from the TSL will help us calibrate Weed Warden to work under any light conditions.We are also calculating the normalized difference vegetation index (NDVI) and the NDVI with the blue wavelengths. Testing will be done to see if the NVDI will help Weed Warden differentiate between what is a live plant and what is not.
A new member has joined our team! Zachery McLaughlin is an Electrical Engineering student here at Oregon State University, and he will be assisting the electrical tasks of this project.
Author: Brendan Miller, Colton Shaw, and Alyssa Berquist
Update
A string of in-lab testings have been conducted in order to have lighting as a control. The tests concluded in erroneous data collected by the triad. We honed in on the problem which was insufficient lighting. Most tests will be conducted outside.We have created an algorithm that can now distinguish artificial green from plant green!
The weed warden enclosure has been drawn up and is ready for printing. Thanks Alyssa!
Author: Brendan Miller, Colton Shaw, and Alyssa Berquist
Update
Back from the holiday, our team is back in full throttle.In the coming weeks, a new enclosure will be designed and printed using a 3D printer.
Future development of Weed Warden is dependent on the shipment of the UV lights that will be mounted onto the Weed Warden. An unexpected issue arose with the last shipment of UV lights, delaying our testing of our near-IR detection algorithm.
Pseudocode has been developed for the Weed Warden, as shown below.
Author: Brendan Miller and Colton Shaw
Update
This week we have added Alissa Bergquist onto our WeedWarden Project. She will be working on the mechanical aspects of the project. Welcome to the team Alissa!Gathering as much data with the triad and TTL have been the main task this week. At the start of next year we will have another member join us who will be involved in creating an algorithm to enhance our weed detecting ability. In order for this to happen, massive amount of data must be collected.
Author: Brendan Miller and Colton Shaw
Update
* New software and hardware components are being implemented and await testingA set of LEDs will be mounted onto the outside of the enclosure in order to increase the detection of vegetation. With data collected from testing with these new lights, we will be able to calibrate our software.
The aforementioned PCB design has been completed. The near-infrared sensor is still in development.
Author: Brendan Miller and Colton Shaw
Update
A schematic for the WeedWarden is being developed in order to produce a PCB to consolidate wiring for our sensors.Field tests have been conducted successfully and the data collected has been added to our database which will be used for further tailoring of sensing.
The near-infrared sensor is still in development.
Author: Brendan Miller and Colton Shaw
Update
Plants reflect green and near-infrared light, both of which our Weed Seeker has the ability to sense. Instead of using only UV light to sense weeds, we will be collecting data to incorporate the visible and IR spectrum.WeedWarden is now using Loom 2, and after every ten seconds a picture is taken and data is stored. Both the data and pictures are clearly labeled to distinguish them from the data taken every two seconds.
A wagon mount was built to easily use the two sensors side by side and remain at a constant height. The sensors are spread three feet apart and are two feet off the ground.
Author: Brendan Miller and Colton Shaw
Update
We are currently in transition from Loom to Loom 2.The second prototype of the WeedWarden is complete. This second WeedWarden will allow us to field tests more effectively by doubling our ability to gathering data.
Author: Brendan Miller and Colton Shaw
To resolve this issue, I looked at how I split the camera setup and the snapshot function. The issue was that no new pictures were actually being taken, and the pictures would either be repetitive or would not save properly. By splitting up the functions the camera would not reset after each picture and would send the same or corrupted image to be saved. Instead of keeping these split, combining the functions allowed the camera to reset properly in order to take a new picture.
Author: Brendan Miller and Colton Shaw