The Internet of Growing Things
Hungry to get the most productivity out of their operations, farmers large and small are turning to Smart Agriculture solutions. The technologies critical to such systems turn out to intersect sharply with those developed for the Internet-of-Things.
If you look at today’s Smart Agriculture landscape, many of the challenges in that space beg for Internet-of-Thing (IoT) solutions. Advanced communication and sensing technologies are being married to advanced, cloud-based data analytics in order to ensure agricultural production that is both sustainable and resource-efficient.
Like most segments of today’s embedded market, Smart Agriculture system developers are leveraging technologies like IoT-centric wireless comms, artificial intelligence (AI), machine learning and computer vision. While some of these solutions are coming from specialist agriculture technology companies, included in the mix are vendors of microcontrollers (MCUs), sensors and wireless interfaces that are feeding the needs of the Smart Agriculture market. Over the past 12 months, a diverse array of products have been rolled out, including solutions at the system, board and chip level.
MCU + IoT SOLUTIONS
Several MCU vendors are seeing their products and technologies meet the needs of Smart Agriculture applications. Not surprisingly, many of those MCU-based solutions are IoT focused. An example is Microchip Technologies’ PIC-IoT WG development board (Figure 1). It combines PIC24FJ128GA705 MCU, an ATECC608A CryptoAuthentication secure element IC and the fully-certified ATWINC1510 Wi-Fi network controller. The controller provides a simple and effective way to connect an embedded application to the Google Cloud IoT Core, says Microchip. The board also includes an on-board debugger, and requires no external hardware to program and debug the MCU.
Microchip recently produced a video discussing how IoT technologies are transforming agriculture and vertical farming . The video also includes a discussion of tools—like the PIC-IoT WG—and techniques for successfully implementing a cloud-connected sensor network in your own designs. The video is available on Circuit Cellar’s article materials webpage. Microchip also penned an article for AgriTech Tomorrow about using the PIC-IoT WG boards for Smart Agriculture .
On the low power side, Microchip says its SAM IoT board, based on its low power SAM MCUs, is suited for applications like farm sprinkler systems. Microchip’s new SAM-IoT WG board connects the Google Cloud IoT Core with Microchip’s 32-bit SAM-D21 Arm Cortex M0+ range of MCUs. A requirement in sprinkler systems is to have a low power MCU that can be used to control water flow, manage timings, direction of water flow and so forth. Such systems not only need an MCU to manage the system, but also components like analog sensors and power regulators. And the data from these sprinklers can then be collated and transferred to the cloud using Wi-Fi to provide the required information to manage water efficiently for a given area or farm land.
SMART FLOOD IRRIGATION
In another example of combining the connectivity and sensor input themes of IoT, Prescott Farm Innovations makes a product called WET Stake. WET Stake is a device that notifies flood irrigation farmers when the water reaches the end of the section that they’re watering (Figure 2). As one of oldest methods of crop irrigation, flood irrigation is on the low end of the irrigation technology spectrum. Among the issues with flood irrigation is the man-hours needed. The farmer typically sends water to a main ditch at the top of the field, he opens gates or starts siphon tubes in one section of the field. He then waits for the water to get down to the bottom of the field and then stops that section and starts the next one.
Most of the man-hours wasted is because of the need to keep checking to see if the watering is done in each section—times can vary from between 20 minutes to up to 5 hours. Addressing this problem, a farmer can simply place WET Stake at the end of the section he is watering and when the water reaches the right level, WET Stake notifies the farmer by phone call or text. Over watering can reduce the efficiency of fertilizer. WET Stake saves water, prevents over watering crop damage and saves the farmer’s time.
According to the company, the IoT technology revolution was perfectly suited to facilitate the development of WET Stake. The design combines an IoT chip along with GPS, and simple sensors inside a custom-built housing. The mechanical design is a simple, durable and familiar shape for farmers—almost like a shovel. It is also solar powered to eliminate any charging downtime.
The WET Stake interface is also very simple, and requires no extra “Smart” technology overhead or processing. The user simply texts the device code to a phone number which gets paired their WET Stake device. All settings can be changed through texting as well. When the WET Stake detects water, the user is notified via call or text and a map link is sent if they want to see the location on a smart device map. Other features include a supervisor option for larger operations. This lets one person monitor the watering progress of fields by their hired hands.
At several conferences over the past 12 months, Renesas Electronics has demonstrated its Silicon-on-Thin-Buried-Oxide (SOTB) technology using a Smart Agriculture example. The demo showed a SOTB agriculture soil monitoring proof of concept that showcases Renesas’ SOTB technology at the MCU level by leveraging ambient energy sources such as wind, light, thermal, vibration and flow. Featuring the ultra-low power SOTB R7F0E embedded controller product, the solution allows energy-harvesting technologies to drive sensor networks in environments that require battery-free sensors or sensors that function for long periods without battery replacements.
Last November, Renesas introduced its RE Family that encompassed the company’s current and future lineup of energy harvesting embedded controllers. Following the mass production of the RE01 Group (formerly known as the R7F0E embedded controllers), the first of the RE Family, the new RE01 Group Evaluation Kit was launched. The kit enables users working with the RE01 Group of devices to jump start system evaluations for energy harvesting applications (Figure 3).
The RE01 Evaluation Kit includes an evaluation board that features an RE01 embedded controller, an interface for the energy-harvesting device and a rechargeable battery interface. The kit also includes an Arduino-compatible interface for easy expansion and evaluation of sensor boards and a Pmod connector to expand and evaluate wireless functionality. In addition, there is an ultra-low power MIP LCD expansion board so that users can evaluate display functions faster.
The kit also contains sample code and application notes that serve as references for power management designs which eliminate the need for battery maintenance, and driver software that supports CMSIS, Arm’s Cortex Microcontroller Software Interface Standard. Sample code for ultra-low power A/D converters, digital filter and FFT (fast Fourier transform) routines, 2D graphics MIP LCD displays, and secure boot and secure firmware update functions for improved security are all available.
The SOTB process technology allows users to simultaneously achieve low active current, low standby current and high-speed operation at low voltage. The RE01’s 32-bit CPU core enables users to implement intelligent functions in equipment powered by low levels of harvested energy through ambient energy such as light, vibration or fluid flow.
AI IN SMART AGRICULTURE
Just as they are in most all embedded applications these days, AI and machine learning are having an impact in Smart Agriculture. An example is IntelinAir, an analytics company that provides crop intelligence to farmers through aerial imagery, computer vision, machine learning, agronomic science and intelligent user interfaces. In 2020, IntelinAir plans to document images from close to 5 million acres of farmland across nearly 50,000 fields, collecting over 1 petabyte of raw data. Using computer vision and deep learning approaches, IntelinAir analyzes data to deliver near real-time Smart Alerts to farmers through its flagship product AGMRI.
AGMRI is a field health monitoring and early-warning system that enables farmers to proactively manage their operations (Figure 4). AGMRI uses proprietary, patented technology to collect and analyze data from numerous sources. IntelinAir uses AGMRI to gather high-resolution aerial images, temperature readings, humidity measurements, rainfall, soil samples, terrain type, equipment utilized, planting rates, applications and more. They then harness the power of hyperspectral analysis, computer vision and deep learning in order to identify patterns and build a complete and precise situational representation of every monitored field for the entire growing season.
Information is continuously aggregated, correlated and strengthened by remembering, relating and connecting past and present situations. As the system trains on new data, it becomes stronger, smarter and more effective every day. AGMRI identifies abnormal crop conditions long before the human eye can detect them and tracks their progress from week to week.
The system’s AI cognitive decision-making engine has already processed hundreds of terabytes of crop images across multiple seasons. The company uses Big Data and AI to enable what it is says is a previously unattainable class of computation for agriculture. AGMRI uses self-learning algorithms to perform precise predictive analytics, which remove the sampling errors typically associated with relying on scouting efforts alone. Computer vision processes the imagery captured via the aerial sensors to extract meaningful environmental features such as bare ground, biomass, reflection, chlorophyll content and plant heights while removing the noise and clutter.
System level solutions for Smart Agriculture are rapidly evolving and, like component solutions, are leveraging the latest communications technology. Exemplifying these trends, in November, Trible Agriculture introduced its GFX-350 display and NAV-500 guidance controller (Figure 5). The solutions were designed to provide a cost-effective option for farmers seeking to adopt the latest precision agriculture technology for their daily operations.
Continuing a tradition of Android-based high-definition touchscreen displays, the GFX-350 display is a cost-effective way to introduce auto-steering and application control to the farm. The 7″ (18cm) screen is easy to read and can be used to control most field operations with just a few taps. The display is compatible with both the new NAV-500 and the NAV-900 guidance controllers, satisfying different user accuracy needs. The simple and intuitive Precision-IQ operating system speeds up field work and makes equipment configuration easy, says Trimble. Once vehicles, fields, implements and materials are set up during the first use, they are saved and can be re-used with a couple of clicks.
In addition, the GFX-350 display is fully ISOBUS compatible, offering plug-and-play capability for ISO-enabled implements with native task controller and universal terminal functionality. The display also features onboard Wi-Fi and Bluetooth connectivity, allowing seamless sharing of data between the office and the field via optional Trimble Connected Farm solutions.
The NAV-500 guidance controller features a low-profile rugged housing capable of receiving signals from five different GNSS satellite constellations—GPS, Galileo, GLONASS, BeiDou and QZSS. This precision solution offers sub-meter repeatable accuracy and full-farm coverage ideal for tillage, broad-acre seeding, spraying and harvest operations. By using Trimble’s ViewPoint RTX satellite-delivered correction service with the NAV-500, operators can consistently achieve 15cm pass-to-pass accuracy. Paired with either the new GFX-350 display or larger 10″ (25.4cm) GFX-750 display, the NAV-500 can provide roll-corrected manual guidance or can automatically control steering with the EZ Steer assisted steering system and EZ Pilot Pro steering system.
SMART EAR TAG EXAMPLE
In another example of IoT technology being used for Smart Agriculture, Nordic Semiconductor says its nRF9160 System-in-Package (SiP) LTE-M/NB-IoT cellular IoT module is being employed in an IoT-enabled herding livestock management solution developed by Finnish startup, Anicare, called the Anicare Healtag. The Healtag became commercially available in September last year. Healtag is designed to ensure farmers of commercially bred reindeer and other herding animals against the financial loss and livestock welfare issues associated with undetected illness or injury of herding animals that spend most of the year roaming in the wild.
Anicare says Healtag is a significant improvement over existing herding animal trackers that are so large they have to be hung from the animal’s neck, and consume so much power that their batteries have to be replaced every year, which is not only expensive and time consuming for the farmer, but also highly stressful for the animal.
In contrast, by employing a highly miniaturized, low-power Nordic nRF9160 SiP, the 25g, 35mm x 22mm x 23-mm Anicare Healtag is small and light enough to be attached to an animal’s earflap like a traditional livestock ear tag (Figure 6). It offers a maintenance-free battery lifetime of up to five years, which means the tag only needs to be attached once to the animal during its lifetime. The all-in-one module integration of the nRF9160 SiP means they don’t have to worry about having separate application processor, antenna, GPS and NB-IoT circuits that would require a lot of supporting components and thus more PCB space.
In operation, the Anicare Healtag autonomously measures a herding animal’s activity (using an accelerometer) and heat (using a thermal sensor) once every hour, and uses the latest NB-IoT cellular wireless technology to report of any significant changes that would tend to indicate either illness, injury or predator attack. This includes using the Nordic nRF9160 SiP’s built-in GPS functionality to immediately send the exact location of a distressed animal to its owner, enabling rapid rescue and treatment. And Anicare says that in terms of coverage, the latest NB-IoT cellular wireless technology deployed throughout Northern Europe ensures cellular data communication remains possible even in areas with no 2G cellphone coverage.
GNSS AND RF FOR TRACKING
An important component of Smart Agriculture includes the ability to precisely track the position of crops and livestock. Here, access to the GNSS (Global Navigation Satellite System) provides a powerful solution to meet such needs. Along those lines, in December U-blox announced that Taoglas developed a centimeter-level GNSS positioning solution. The system comprises a high-precision L1/L2/E5 GNSS receiver, the U-blox ZED-F9P, all the required RF electronics and antennas in a single package (Figure 7). Called Taoglas Edge Locate, this positioning module simplifies the development and deployments of IoT solutions that depend on high-precision positioning information.
Taoglas Edge Locate addresses the growing demand for highly accurate centimeter-level positioning performance, which, until recently, was reserved for high-value use cases such as guidance systems for precision agriculture and heavy machinery, says U-blox. This changed with the release of additional satellite signals and the announcement of U-blox F9 high-precision positioning platform, which lowered the cost of ownership of the technology, extending its benefits to mass market applications for the first time, according to U-blox.
Featuring the U-blox ZED-F9P high-precision GNSS module with concurrent reception of GPS, GLONASS, Galileo and BeiDou on multiple frequency bands, the Taoglas Edge Locate module can also use real-time kinematic (RTK) algorithms to help achieve even faster convergence times and reliable performance, even in highly dynamic applications. The integrated smart antenna is specifically designed and optimized for multi-band GNSS applications.
High-precision positioning enables a range of use cases like precision agriculture, but also emergency response, smart infrastructure, drone delivery and micro-mobility. Edge Locate’s RTK positioning capabilities let end users benefit from centimeter-level positioning without subscribing to GNSS correction services, relying instead on a local RTK network that Taoglas can also help customers design and set up.
3X REDUNDANT SENSORS
In another example of a GNSS solution suited to precision agriculture, ACEINNA in January announced the availability of its OpenRTK330L device, a triple-band RTK/GNSS receiver with built-in triple redundant inertial sensors (Figure 8). Designed to replace the expensive and bulky precision RTK/INS systems used in today’s autonomous systems, this compact navigation solution meets the performance, reliability and cost requirements of Smart Agriculture systems, as well automotive, robot, drone and construction systems.
ACEINNA’s OpenRTK330L includes a triple-band RTK/GNSS receiver coupled with redundant inertial sensor arrays to provide centimeter-level accuracy, enhanced reliability and superior performance during GNSS outages. The OpenRTK330L integrates a very precise 2 degree/hour inertial measurement unit (IMU) to offer 10 to 30 seconds of high-accuracy localization during full GNSS denial. This enables autonomous system developers to safely deliver highly accurate localization and position capabilities in their vehicles at prices that meet their budgets. OpenRTK330L’s embedded Ethernet interface allows easy and direct connection to GNSS correction networks around the world. OpenRTK330L’s CAN bus interface allows simple integration into existing vehicle architectures.
The multi-band GNSS receiver can monitor all global constellations (GPS, GLONASS, BeiDou, Galileo, QZSS, NAVIC, SBAS) and simultaneously track up to 80 channels. The module has RF and baseband support for the L1, L2 and L5 GPS bands and their international constellation signal equivalents.
The IMU and dead reckoning function contains a total of 9 accelerometer and 9 rate gyro channels based on ACEINNA’s unique triple redundant 6-Axis IMU array. By integrating a triple-redundant IMU array, the OpenRTK330L is able to recognize and utilize only valid sensor data, ensuring high-accuracy protection limits and certifiability under ISO26262 standards. The OpenRTK330L is supported by ACEINNA’s Open Navigation Platform allowing
CATTLE HEALTH MONITORING
Beyond just position tracking of livestock, IoT technologies are also being used to monitor the health of animals. In an example along those lines, last Fall Semtech announced that ITK, a French supplier of IoT-based Smart Agriculture applications, developed a new cattle health-monitoring solution based on Semtech’s LoRa devices. The FarmLife Smart Agriculture service and its LoRa-enabled sensors detect cattle estrus, drive improved nutrition and predict the onset of disease to help ranchers better monitor their herds (Figure 9).
According to ITK, LoRa devices’ flexibility in deployment makes a key difference for connecting animals and offers the potential for a significant return on investment (ROI). ITK’s solution provides ranchers with tangible, actionable data on the health of their herds to remove variables from ranching and create productive, efficient and profitable ranches.
Offering a flexible solution for the Smart Agriculture vertical, Semtech’s LoRa devices create applications that help minimize waste, maximize yield, reduce expenses and offer farms and ranches an opportunity to operate as efficiently as possible. ITK’s LoRa-based sensors deploy simply through a collar equipped to each animal. The collar is non-invasive and immediately begins reporting data on the cow’s health upon deployment
Ranchers monitor their herds from this LoRa-based device, which provides the benefits of four value-added services: Heat’Live for heat detection, Feed’Live for nutrition optimization, Time’Live for animal welfare and Vel’Live for calving detection. These services are available through ITK’s FarmLife Cloud platform. In total, deploying ITK’s solution costs less than 30 Euros per animal annually.
In addition to the 300,000 cows already monitored in Europe, approximately 20 ranches have deployed ITK’s FarmLife platform in North America, connecting cows to the cloud through network connectivity from X-TELIA, a leading Canadian network provider. Following this initial deployment, farmers claimed they received an ROI in less than a year through an increase in ranch productivity and efficiency. X-TELIA and ITK plan to continue the rollout of this Smart Agriculture solution in the Canadian market, adding ITK’s San’Phone cattle health monitoring service and its Thermo-bolus sensor to connect up to 2.4 million cows in the future.
Clearly there’s a lot of interesting activity happening in the Smart Agriculture space. And its overlap with IoT will only grow as system developers seek out highly integrated, wirelessly connected solutions linked together with sophisticated cloud-based oversight and monitoring.
References: Video:  Microchip Technology contributed article in AgriTech Tomorrow
ACEINNA | www.aceinna.com
IntelinAir | www.intelinair.com
Microchip Technology | www.microchip.com
Nordic Semiconductor | www.nordicsemi.com
Prescott Farm Innovations | www.wetstake.com
Renesas Electronics | www.renesas.com
Semtech | www.semtech.com
STMicroelectronics | www.st.com
Trimble Agriculture | https://agriculture.trimble.com
U-blox | www.u-blox.com
PUBLISHED IN CIRCUIT CELLAR MAGAZINE • MAY 2020 #358 – Get a PDF of the issueSponsor this Article
Jeff served as Editor-in-Chief for both LinuxGizmos.com and its sister publication, Circuit Cellar magazine 6/2017—3/2022. In nearly three decades of covering the embedded electronics and computing industry, Jeff has also held senior editorial positions at EE Times, Computer Design, Electronic Design, Embedded Systems Development, and COTS Journal. His knowledge spans a broad range of electronics and computing topics, including CPUs, MCUs, memory, storage, graphics, power supplies, software development, and real-time OSes.