Brian L. Steward

Iowa State University

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Co-Authors

Lie Tang

Iowa State University

Manoj Karkee

Washington State University

Stuart J. Birrell

Iowa State University

Safal Kshetri

Washington State University

H. Mark Hanna

Iowa State University

Samsuzana Abd Aziz

NHS Greater Glasgow and Clyde

Thomas J. Brumm

Iowa State University

Dev Shrestha

University of Idaho

Amy L. Kaleita

Iowa State University

Mehari Z. Tekeste

Iowa State University

Cooperative Institutions

Iowa State University

Universidade Federal de Viçosa

University of Illinois Urbana-Champaign

Agricultural Research Service

Washington State University

United States Department of Agriculture

NP Photonics (United States)

Purdue University West Lafayette

ORCID

Institute of Electrical and Electronics Engineers

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Research Field

Measuring and modeling the movement of spray droplets into off-target areas

2019 Boston, Massachusetts July 7- July 10, 2019 (2019)

Brian L. Steward H. Mark Hanna Philip M. Dixon Rithana K Mompremier

Abstract. Spray drift can cause significant environmental harm and is a problem for the agricultural chemical application industry.Â Models help predict the distance of smaller, drift-prone droplet travel from wind tunnel studies, but field testing is required to validate predicted drift from these models. The purpose of this research was to investigate spray drift from three different spray quality nozzles into an off-target area up to 30 m from the end of the spray boom with varying cross-boom wind velocities. Field tests were carried out using a UTV-mounted boom sprayer driving perpendicular to the wind direction. Using pink spray dye, off-target droplets were collected on white Kromekote droplet collection cards spaced on 2 m intervals to 30 m downwind. Tests were done during four days with differing wind speeds less than 15 mi/h. Three different spray quality nozzles were used: fine, medium and very coarse. Each individual card was scanned with a flatbed scanner. The resulting images were analyzed with DepositScan software which found the number, area and diameter of the droplets on each card. The number of droplets collected on cards, decreased with distance from the boom to a low, but non-zero number of droplets were found on cards out to 30 m. Using a statistical model, there was a clear extension of off-target application rates into the 2 to 10 m distance away from the boom depending on droplet size and a low probability of substantial off-target application rates in the 10 m to 30 m region.

Sprayer

10.13031/aim.201901496

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Citations (1)

Real-time weed detection in outdoor field conditions

Brian L. Steward Lei Tian

Though most herbicide is applied uniformly in agronomic fields, there is strong evidence that weeds are not distributed uniformly within the crop fields. If an effective weed detection system were developed, both economic and environmental benefits would result from its use for site-specific weed management. Past work in this area has focused mainly on either low spatial resolution photo-detectors or off-line machine vision system. This study was undertaken to develop real-time machine vision weed detection for outdoor lighting conditions. The novel environmentally adaptive segmentation algorithm was developed with the objective of real-time operation on an on-board computer-based system. The EASA used cluster analysis to group pixels of homogeneous color regions of the image together which formed the basis for image segmentation. The performance of several variations of this algorithm was measured by comparing segmented field images produced by the EASA, fixed-color HSI region segmentation, and ISODATA clustering with hand-=segmented reference images. The time cost and questionable accuracy of hand- segmented reference images led to exploration of the use of computer-segmented reference images. Sensitivity and background sensitivity were used as performance measured. Significant differences were found between the means of sensitivity, background sensitivity, and overall performance across segmentation schemes. Similar results were obtained with computer-segmented reference images.

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Citations (26)

Virtual Operator Modeling Approach for Construction Machinery

Yu Du Michael C. Dorneich Brian L. Steward E. R. Anderson Lawrence F. Kane

Operator (biology)

Source

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Citations (1)

ML-based Anomaly Detection for CAN Bus Network in Agriculture Machinery

Proceedings of the AAAI Symposium Series (2024)

Souradeep Bhattacharya Ranuka G. Gallolukankanamalage Brian L. Steward Manimaran Govindarasu

The adoption of advanced automation and next-generation technologies like the Internet of Things (IoT) and modern communication networks has revolutionized the food and agriculture sector, boosting the efficiency and precision of farm machinery. However, this increased inter-connectivity has also exposed significant vulnerabilities, particularly in Controller Area Network (CAN) protocols, widely used in advanced agricultural machinery and equipment. Due to its lack of inherent security features, CAN is susceptible to various cyber-attacks, potentially leading to severe consequences if these attacks remain undetected and unmitigated. This paper introduces a supervised machine learning (ML)-based anomaly detection system (CAN-ADS) designed to detect various cyber-attacks on CAN-based agricultural machinery. The system leverages network traffic augmentation and data balancing techniques to train ML algorithms on CAN-specific datasets. Experimental results show that CAN-ADS achieves high accuracy (approx 98%) and true-positive rates with low false-negative rates (approx 1%).

Anomaly (physics)

10.1609/aaaiss.v4i1.31826

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Soil Loading Effects of Planter Depth-Gauge Wheels on Early Corn Growth

Applied Engineering in Agriculture (2010)

H. Mark Hanna Brian L. Steward Landon Aldinger

Final soil manipulation before seed germination occurs during the planting operation. Contact force of depth-gauge wheels adjacent to the seed opener potentially alters the environment for corn seed germination and early plant growth. A field experiment was conducted measuring seed spacing, spacing variability, seed depth, emergence rate, plant dry matter, final stand, crop growth stage, and extended leaf height with different soil contact loads [light, 180 to 490 N (40 to 110 lb); medium, 490 to 890 N (110 to 200 lb); and heavy, over 890 N (200 lb)] and a range of three soil moistures (dry, moist, wet). A treatment with randomly variable contact load similar to that of a conventional planter (control) was also included.

10.13031/2013.32058

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Citations (30)

Soybean Moisture Content Measurement Based on Impact Force Parameters

ASSA, CSSA and SSSA (2013)

Brian L. Steward John W. Hummel

Previous work has shown that force-time curves for impacting soybeans vary with soybean moisture content. This paper documents an effort to characterize the nature of the relationship between a parameter developed from the force-time curve and soybean moisture content. The underlying objective was to determine if impact force sensing could be used to reliably make real-time moisture content measurements for yield monitoring applications. A parameter, C, based on the peak force and duration of the force-time curve was calculated. C was regressed onto moisture content using a polynomial model. The model fit the data with R 2 = 0.84 and 0.76 for the Conrad and Jack cultivars, respectively. The variability in C increased as moisture content decreased, and the strength of the relationship between C and moisture content decreased with increasing moisture content.

Content (measure theory)

10.2134/1999.precisionagproc4.c27b

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Dielectric Spectroscopic Sensor for Particle Contaminant Detection in Hydraulic Fluids

2016 ASABE Annual International Meeting (2014)

Safal Kshetri Brian L. Steward Stuart J. Birrell

Abstract. Particulate contamination of hydraulic fluids is one of the major causes of mechanical wear of hydraulic components resulting in system inefficiency and failure. Potential failures of hydraulic systems could be avoided through continuously monitoring the condition of the fluid. A practical contaminant sensor was developed to estimate the level of particulate contamination in hydraulic fluids. The sensor was designed to be installed on vehicle and provide in-line measurements of contaminated hydraulic fluid. The sensor used dielectric spectroscopy for measuring contaminants. To investigate the performance of the dielectric sensor two tests were performed with different diameter central rods using iron particles as hydraulic contaminants. A hydraulic test circuit was built and a methodology was developed for the tests. An eight-channel particle counter was used for calibration of the dielectric sensor. PLS models were developed to investigate the relationship between dielectric spectra and iron particle counts. The RMSEC and RMSECV for the sensor with a central rod diameter of 6.35 mm were 1.1ISO 4406 scale numbers and 1.39 scale numbers respectively. For a 17.7 mm diameter rod, the respective values were 0.62 and 0.77. The sensor shows good potential estimate of the cleanliness level of hydraulic fluid mixed with iron contaminants.

Particle (ecology)

Hydraulic fluid

Rod

Hydraulic circuit

10.13031/aim.20141914249

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An Object-Oriented Architecture for Field Data Acquisition, Processing and Information Extraction

2003, Las Vegas, NV July 27-30, 2003 (2003)

Dev Shrestha Brian L. Steward Cory Van Wyngarden

Software architecture was developed to automate site specific field data acquisition,processing, and geo-referenced crop plant parameters extraction. The architecture supportedacquisition and processing of different data streams such as digital video for machine vision anddigital serial communications of NMEA strings. The number of channels for data import could beeasily expanded for multiple video, GPS, and other signal sources. The architecture was objectorientedand each component in the architecture was developed as a separate class. A keycomponent of this architecture was a supervisor class, which communicated and coordinated theoperations on all other classes. Based on this framework, early stage corn population estimation(ESCOPE) software was developed which grabs pre-recorded digital video from a vehicle-mountedcamera, that was passed over corn rows, and acquires GPS strings which were modulated andrecorded on the audio channel. A digital video (DV) capture class was written to acquire video usingMicrosofts DirectShow technology which enables camera control and video acquisition using higherlevel hardware functions. After completion of software development, reusability and extensibilitycharacteristics were demonstrated by adding a class to acquire images from the hard drive and alsoby deriving a new image analyzer class to extract an additional feature. The architecture forms ageneral framework for developing reusable and extensible software for field data sensing systems.

10.13031/2013.13855

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Citations (1)

Bioethanol production potential from Brazilian biodiesel co-products

Biomass and Bioenergy (2010)

Evan Michael Visser Delly Oliveira Filho Márcio Arêdes Martins Brian L. Steward

Cellulosic ethanol

Jatropha curcas

Jatropha

10.1016/j.biombioe.2010.09.009

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Citations (59)

<title>Smart sprayer project: sensor-based selective herbicide application system</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2000)

Lei Tian Brian L. Steward Lie Tang

The smart sprayer, a local-vision-sensor-based precision chemical application system, was developed and tested. The long-term objectives of this project were to develop new technologies to estimate weed density and size in real-time, to realize site-specific weed control, and to effectively reduce the amount of herbicide applied to major crop fields. This research integrated a real-time machine vision sensing system and individual nozzle controlling device with a commercial map-driven-ready herbicide sprayer to create an intelligent sensing and spraying system. The machine vision system was specially designed to work under outdoor variable lighting conditions. Multiple vision sensors were used to cover the target area. Instead of trying to identify each individual plant in the field, weed infestation conditions in each control zone (management zone) were detected. To increase the delivery accuracy, each individual spray nozzle was controlled separately. The integrated system was tested to evaluate the effectiveness and performance under varying commercial field conditions. Using the on-board differential GPS, geo-referenced chemical input maps (equivalent to weed maps) were also recorded in real-time. The maps generated with this system have been compared with other sensing and referencing systems.

Sprayer

Precision Agriculture

Differential GPS

10.1117/12.411741

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Citations (6)