Open Source Orchard

Progress report for FNE23-034

Project Type: Farmer
Funds awarded in 2023: $30,000.00
Projected End Date: 09/30/2025
Grant Recipient: KC Bailey Orchards, Inc
Region: Northeast
State: New York
Project Leader:
Josh Bailey
KC Bailey Orchards, Inc
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Project Information

Project Objectives:

This project seeks to address the need for cost-effective digital agriculture solutions that make it easier for farmers to manage their daily operations/inputs efficiently.

1. LoRaWAN Gateway Deployment – assess optimal implementation of an on-farm LoRaWAN network to interface with all sensor nodes in a commercial orchard in the Northeast

2. Irrigation Management – determine optimal way to sense drip irrigation needs/success and deploy LoRaWAN sensors in irrigation zones/orchard blocks based on soil maps, elevation, and apple variety

3. Irrigation Automation – implement LoRaWAN valves for irrigation zones and determine best setup of valve transmitter/cable and irrigation box 

4. Weather Data Collection – establish a LoRaWAN weather station and collaborate with 2-3 other farms in the area with already-established weather stations to compare weather patterns near and away from Lake Ontario 

5. Asset Tracking – assess LoRaWAN asset tracking capabilities and attach nodes to specific pieces of equipment to track live location/historical paths taken

6. Fuel Tank Monitoring – apply LoRaWAN tank monitors to 2 diesel tanks to view levels at any time for refill planning 

7. Dashboard Integration – integrating all data to one open-source dashboard for live andaggregated data visualization, and potentially providing updated imagery with drones

Introduction:

The following are numbered in accordance to the Methods section of this application to explain their importance. 

1. LoRaWAN Gateway Deployment 

The basis for our IoT infrastructure will be a LoRaWAN network (specification: Low Power, Wide Area; LPWA), which overcomes another historical barrier to IoT adoption in commercial agriculture: the difficulty of covering vast amounts of land and connecting the number of devices necessary to acquire big picture data. Early commercial IoT solutions relied on full-farm WiFi, cellular, or Bluetooth coverage, which establishing in and of themselves increases costs. Plus, early devices needed to be constantly maintained since battery life was an issue. LoRaWAN on the other hand offers an extremely affordable option for wide area coverage that allows devices to save battery power (5–10-year battery lives) since they only need to communicate with a gateway every 15 minutes or so (soil moisture data isn’t needed every second for adequate insights). 

2. Irrigation Management 

Since our main farm (where the experiment is) is 100% drip irrigated and relies entirely on municipal water, water as an input cost can be quite high in dry years. Therefore, being able to manage the amount of water applied to each of our 30+ irrigation zones is critical, but is very difficult to do just on qualitative observations of individual rows. Therefore, we plan on deploying multi-depth soil moisture sensor systems to give indications of the level of water trees are exposed to from rain and irrigation and also serve to monitor if the irrigation zones are functioning properly. Additionally, our systems (as discussed more in Methods) will provide an affordable solution that will allow for sensing further into the root zone to take into account the actual water penetrating the soil. We've determined a deployment of 2 sensors per irrigation zone will provide the necessary data at a reasonable cost/sensor.

3. Irrigation Automation 

Our 30+ irrigation zones are set up to have submain control boxes where water valves are turned on/off by hand, which takes a lot of time in going around to each box. Therefore, we plan to automate the on/off process so that it can be done remotely from anywhere, using our soil moisture sensors to aid in making the decision on when to do so.

4. Weather Data Collection 

Our farm extends about 1.5-2 miles right up to Lake Ontario, which provides an overall optimal climate for apple production. However, there are some notable differences in temperature and humidity that would be helpful to quantify in making spray and irrigation decisions for our orchard blocks near the lake vs. further away. Therefore, we plan on working with 2-3 other farms in the area with already established weather stations in the NEWA system to better understand local weather patterns and draw correlations for reference in decision making. 

5. Asset Tracking 

Farms, especially highly managed specialty crop farms, constantly deal with moving equipment and people on a daily basis that can be hard to keep track of and manage. To help with this, we will experiment with LoRaWAN GPS trackers to track equipment live to view progress with various tasks and also over time so that a farmer can see at the end of the day/month/year(s) where each piece of equipment has been. 

6. Fuel Tank Monitoring

Our farm has two diesel tanks for our equipment, and knowing when they need to be refilled requires taking the time to manually check gauges at the tank and requesting more. By using LoRaWAN tank monitors, this process will be simplified to be able to monitor levels from anywhere. 

7. Dashboard Integration 

Software development has consistently been a source of high costs for commercial IoT solutions and a major reason for high prices to farmers. By utilizing an open source platform to develop on, we hope to deliver a comprehensive dashboard for farmers to visualize the data they collect in a simplified way anywhere with internet or cellular connection at an affordable cost. Depending on additional resources from this grant, we can also look into the viability of using drone imagery or purchasable satellite imagery to create up-to-date mapping for asset tracking. Free satellite imagery (i.e., Google Earth) is typically out of date, so changes made on the farm aren’t visible and it’s difficult to get an accurate depiction of where everything is if entire planting systems have been altered. 

Cooperators

Click linked name(s) to expand/collapse or show everyone's info
  • Dr. Dennis Buckmaster - Technical Advisor
  • Dr. James Krogmeier - Technical Advisor

Research

Materials and methods:

1. LoRaWAN Gateway Deployment 

To determine the optimal implementation of a LoRaWAN gateway (or multiple) in a commercial orchard setting, our initial assumption was to continue with our approach from the summer of 2022 where we set up a WisGate Edge Pro gateway on a tripod next to our shop, and simply move the entire unit on top of our roof to ensure greater farm-wide coverage. However, we had issues scheduling anyone who would be able to (safely) get on the 30' high roof to fasten the tripod down and we quickly realized if there was ever a need to provide maintenance to the gateway, it would be virtually impossible. We then began to reevaluate the overall agrosecurity of the system, and started by addressing questions such as "If something were to happen to a gateway, how easy would it be to replace that gateway, reconnect sensors, and get everything back up and running?" As our new shop office is now in it's final stages of completion, we plan to attach a WisGate Edge Pro (V2) to the lower part of it's roof which can be easily reached by a ladder and we will begin range testing by moving a couple of sensors further and further away from the gateway, collecting data on the SNR (Signal Noise Ratio), RSSI (Received Signal Strength Indication), and time intervals of sensor communication. This gateway should be able to at least cover the south side of our farm based on our summer 2022 tests as well as beyond that, but we're looking to shift to a cluster deployment strategy where 2-3 gateways are used for a more resilient form of coverage. In the event one gateway is knocked out, sensors can still connect to other gateways within the network, allowing for data collection to continue even in worse-case scenarios. This can also ensure that risks of physical interference are reduced, such as from a locust grove standing between two farm sections, and because a smaller amount of acreage is the focus, tripod-based gateways on the ground level are an option. In addition, this means a cluster gateway deployment can be taken in during winter months when data collection isn't as necessary as during the growing season. We view the initial shop office gateway as a more "permanent"deployment and we still plan to run an Ethernet cable into our shop from the gateway to a PoE injector to mitigate the risk of a lightning strike causing a fire inside the shop if a gateway is hit, and another Ethernet cable will run from the injector to an office space to connect to a WiFi router. For the server however, we're looking to switch from a Raspberry Pi-based physical computer to a cloud-based computer via a managed service provider. This concept came from the question "How could a farm respond to cybersecurity threats and ensure operations can continue to run smoothly especially if automated devices are in use?" Using cloud computing instead of physical computing will mean maintenance of a separate computer is not necessary and farms will not be responsible for establishing intense cybersecurity measures on their own (the Raspberry Pi could be hacked if left unmaintained). If cybersecurity issues do occur, the managed service provider will act as a deterrent and work on the farm's behalf. The full IoT data pipeline, including Chirpstack (the web-interface to manage the gateway and all devices connected to it), will reside on the cloud computer for an affordable cost.

2. Irrigation Management 

Three “Drop Count” sensor systems were constructed during the summer of 2023 and the design involved a Watermark Soil Moisture Sensor (acting as a soil potential sensor) with 15’ cable, Watermark Soil Moisture Sensor Voltage Adapter in a plastic utility box, Vegetronix Soil Moisture Sensor with 2-meter cable, Watermark Soil Temperature Sensor with 15’ cable, Dragino Waterproof Long Range Wireless LoRa Sensor Node, and a wooden stake to prop the system vertically. The systems were successfully assembled but proved to be tedious to assemble and far too bulky, especially since a 2x4 was needed to hold everything upright. Moving forward, we will be using a much leaner design that includes a Tektellic KIWI Agriculture Sensor, 2 Watermark Soil Moisture Sensors, and 2 soil temperature sensors. One pair of soil moisture sensors and soil temperature sensors will be placed about 6" deep and the second pair about 18"-24" deep, the latter of which was suggested by a Cornell Cooperative Extension agent. This will allow us to not only monitor surface level soil moisture, but also soil moisture at the depth of roots as well. One major adjustment to the initial "Drop Count" systems that will carry over to the new, leaner approach was the use of schedule 13.5 PVC pipes to ensure cables aren't exposed and mice can't chew on them. Evaluation is still being done on the implementation of the soil moisture sensor system, such as positioning relative to the apple varieties in irrigation zones, but so far soil and topography maps have been generated using the USDA NRCS Web Soil Survey online tool to analyze consistency. We plan to use 2 sensor systems per zone so that we can deploy 16 on the 8 irrigation zones on the south portion of our farm and use additional sensors to test on zones further away to see how all established devices of varying ranges are able to communicate with our gateway(s) for potential expansion. 

3. Irrigation Automation 

To automate turning irrigation zones on/off, our plan is to install Strega LoRaWAN Smart Valves with 10' cables for each submain to control remotely from anywhere. So far, we've acquired 10 smart valves but faced great difficulty in doing so. Because 10 smart valves was a small order for Strega, they had us order the valves through their Chinese partner and the LoRaWAN transmitters through them. There were no issues when paying the Chinese company for the valves, but currency conversion issues came up when making bank transactions to Strega, a Belgian-based company. Then, the smart valves were packaged and shipped in a single box to us, but got stuck in customs in Memphis and an additional payment was required to finally get the package to us in NY. After receiving the smart valves, we were notified we'd need to make a firmware upgrade, and that's where we've left off so far. Fortunately, this has given us time to think more about the configuration of our submain boxes, which have been wooden to date and are starting to fall apart. As part of an expansion project on another section of our farm, concrete submain boxes are being implemented as a more structurally sound alternative, and now we're planning on replacing our existing submain boxes with the same material. This will also allow for a more stable smart valve deployment and mitigate against flooding and damage concerns. When implementing, the valve portion of the smart valve will replace the current manual valve at a pipe diameter size of DN50 or 2” and is high pressure rated at PN20. The wire to the actuator (the control and transmission portion) will be run in 10’ schedule 40 PVC pipe up the nearest row post and secured with the end of the pipe to the post. This will ensure data transmission/communication between the gateway and smart valve can be kept above ground and interference won’t occur with the zone box lid. Besides being able to use the smart valve to turn on and off water flow to irrigation zones, the valves have a digital input to connect a pulse counter (i.e., a flow meter) to generate pulses based on the amount of water flowing through the system that will indicate real-time and historical water usage, another digital input to connect a wired leak detection sensor to the system that can be used for notifications in case any issues were to occur, and a feature for automatic flushing sequences to prevent clogging. These features were determined after having further discussion with a Strega sales director and options are being evaluated. Similar to the soil moisture sensor systems, we will start by testing 8 zones on the south end of the farm and then build more out based on results. Evaluations will be made during the “irrigation season” (June/July/August when irrigation is needed most) on how well the system works, which will involve the use of the soil moisture sensors to do so. 

4. Weather Data Collection 

To study weather differences near and away from Lake Ontario, we’re planning on doing a weather data study with a Davis Wireless Vantage Pro2 Weather Station mounted on a tripod and working with 2-3 other farms with already-established weather stations in the NEWA system to compare weather patterns over a period of time. Data collected will be used to correlate with the soil moisture sensor systems and make irrigation decisions utilizing the smart valves. Concerns earlier in the summer of 2023 arose when it appeared Davis weather stations didn't have a supportive LoRaWAN integration, and individual components for the only LoRaWAN-specific option we could find were ordered from a company based in China. However, once we acquired everything, we found out that we had to source the tripod mounting brackets ourselves, as the company in China only worked with local distributors for those parts. There weren’t any distributors in the US or anywhere else as far as we could tell, so that left us with the option of modifying scrap metal ourselves or trying to find an alternative. We’re now returning to the Davis Vantage Pro2 Weather Station and are talking with a couple of companies that have created the necessary LoRaWAN integration components.

5. Asset Tracking 

With our LoRaWAN infrastructure, we plan on testing multiple Digital Matter Oyster LoRaWAN GPS Trackers on select pieces of equipment and observing how well multiple oysters maintain connection with our gateway while moving around high-density orchard trees, and if one drives out of range of the gateway, how well it can resume connection. Case studies will be built out especially during equipment-heavy seasons, such as spray season and harvest, where we’ll apply oysters onto tractors and harvest platforms to show the advantages of seeing progress from anywhere. Additionally, we’ll have the ability to view paths taken by equipment historically, so we can refer back to progress made before on specific days. We are currently in talks with a US supplier for Oyster3 trackers to ensure proper configuration before testing.

6. Fuel Tank Monitoring 

The specific fuel tank level sensors to be used are still being determined, but two options that have been evaluated are Dragino’s LDDS20 LoRaWAN Liquid Level Sensor and IOT Factory’s Fuel-Water LoRaWAN Sensor (Ultrasonic). The issue we faced with the Dragino sensor was it requires a slightly flat surface at the bottom of a fuel tank, and in our case our tanks are perfect cylinders. For the IOT Factory sensor (and in general), we require LoRa products that can operate at the US frequency level (US915), but unfortunately IOT Factory doesn’t offer the US frequency for this specific product. Once we source a sufficient fuel tank sensor, we will likely insert it from one of the screwable top pieces and from there it will be able to record data on the amount of fuel in the tank. We are currently discussing options with a former extension agent from North Dakota State University who has published extension reports on LoRaWAN implementation on farms. Fuel tank monitoring can help with refill scheduling which can be especially important during busy seasons.

7. Dashboard Integration 

By utilizing the open source dashboard Grafana, we will synthesize all data points collected to one location for ease of use for farmers, meaning all soil moisture sensor systems will be displayable as graphs live and over time, fuel tanks will show their levels, and the locations of vehicles will be shown on a map, for example, all in the same place. Development work will be done to make the dashboard as efficient as possible, and we will receive input directly from the managers of KC Bailey Orchards, Inc. on improvements to consider.

Because of the nature of our project, experimentation and testing of each objective will be frequent and throughout the development process, reflective of a true R&D phase. Adjusting slightly, but in order to make the system more resilient, we will focus on the closest block of orchard to our shop to start with before expanding and testing the system over longer periods to observe data collection and infrastructural stability, while learning how to adapt our systems to the weather and environment of the Northeast. Economic impact analyses will also be conducted to show benefits of each technology to farmers throughout (see Other Relevant Research Information).

Research results and discussion:

So far, some main takeaways have been the importance of shoring up supply chain issues, thinking through agrosecurity concerns to improve resiliency, and especially collaborating with local resources and support ecosystems. When trying to figure out details for smart valve implementation, we were able to receive great support from our local irrigation supplier and they even talked with Strega on our behalf to explore middleman vending options for us. We've also started working more closely with Cornell Cooperative Extension, especially the Lake Ontario Fruit Program team, and extension resources/agents in general as well that have done work with IoT. A major reason for our shift from the "Drop Count" system to the leaner soil moisture sensing system focused around the the Watermark 200SS sensor was because it's been widely used and documented for extension purposes by the Universities of Arkansas, Nebraska, and Minnesota (plus more), which will help ensure reliability of the data collected for this category and provide assurance that there are resources and people available to consult with if necessary. Lastly, an important point I'd like to note is that as I've been more involved and integrated with The OATS Center this academic year, I've been able to work on elements of this project at Purdue as part of my graduate program. A lot of the agrosecurity and cloud-based data pipeline components were developed last semester for an agricultural informatics class I was in, and this semester another OATS member and I are experimenting with the LoRaWAN gateway cluster deployment and cloud-based data pipeline at the Purdue Agronomy Center for Research and Education (ACRE) and the results and experience will be directly applied back on our farm.

Participation Summary
Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.