Prediction of Aerial Spray Release from UAVs

Teske, Milton E.; Wachspress, Daniel A.; Thistle, Harold W.

doi:10.13031/trans.12701

Cited by 46 publications

(25 citation statements)

References 25 publications

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“…It is well known that many interacting factors influence the fate of spray material released from helicopters and fixed‐wing aircraft, hence the development of process‐based simulation models to help understand these interactions . It is clear that similar types of user‐accessible models are required for the complex array of multi‐rotor UAVs that are becoming available, each with their own design characteristics that could have a large potential influence on spray performance . Initial modelling research on multi‐rotor UAVs has identified a critical speed above which spray application efficiency from UAVs declines dramatically for at least some multi‐rotor UAV configurations.…”

Section: Resultsmentioning

confidence: 99%

“…It is clear that similar types of user‐accessible models are required for the complex array of multi‐rotor UAVs that are becoming available, each with their own design characteristics that could have a large potential influence on spray performance . Initial modelling research on multi‐rotor UAVs has identified a critical speed above which spray application efficiency from UAVs declines dramatically for at least some multi‐rotor UAV configurations. This critical speed varies with UAV configuration and relates to the stronger downwash at lower speeds enhancing deposition, but above the critical speed, rotor outwash may entrain spray upwards, increasing drift beyond the intended swath.…”

Section: Resultsmentioning

confidence: 99%

“…There is uncertainty over the efficiency of UAV spray applications in terms of the uniformity of spray deposition and the amount of spray drift . A recent modelling exercise demonstrated the sensitivity of four spray application parameters to the complex characteristics of the wake produced by multi‐rotor UAVs. These wake characteristics were strongly influenced by the UAV rotor configuration and operating variables such as forward speed, release height and crosswind speed.…”

Section: Introductionmentioning

confidence: 99%

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Swath pattern analysis from a multi‐rotor unmanned aerial vehicle configured for pesticide application

Richardson

Rolando

Somchit

et al. 2019

Pest Management Science

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BACKGROUND Although unmanned aerial vehicles (UAVs) are increasingly used to deliver small‐scale aerial pesticide applications, there remains uncertainty over their efficiency in terms of uniformity of spray deposition and their application efficiency. Consequently, a field study was designed to quantify factors influencing the uniformity of spray deposition from a multi‐rotor UAV that is operated commercially in New Zealand. Two sampling systems for measuring spray deposition, a continuous horizontal string and steel plates placed on the ground were compared. RESULTS The spray deposit distribution characteristics and calculated lane separation values (distance between flight lines that produces a maximum coefficient of variation of 30% for spray deposits) were strongly influenced by wind speed, nozzle position, release height, ground speed and droplet size. Lane separation values ranged from 1 to > 5 m. Swath distribution parameters (spread and position of peak deposition) derived from plates were not significantly different from those derived from string. However, total deposition on strings relative to plates increased with small droplets. Reducing plate sampling intensity from 0.25 m intervals to 0.5 m and even 1.0 m had only a minor effect on estimates of swath parameter values. CONCLUSIONS The potential for precision spraying from UAV platforms has yet to be achieved with improvements required in hardware and software. Further, mechanistic models are needed to quantify how complex interactions among multiple operating and meteorological variables influence spray deposition. © 2019 Society of Chemical Industry

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Swath pattern analysis from a multi‐rotor unmanned aerial vehicle configured for pesticide application

Richardson

Rolando

Somchit

et al. 2019

Pest Management Science

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“…In reviewing some of the Superior Paper Award winners for 2019 (e.g., Ban et al, 2018;Her and Heatwole, 2018;Jones et al, 2018;Li et al, 2018;Teske et al, 2018;Zhou et al, 2018), it is readily apparent that the quality of the writing and the overall presentation of the research are extremely important. These articles are ideal examples of avoiding the common mistakes listed in table 2; manuscripts that require major revision due to those common mistakes are not likely to be considered for a Superior Paper Award.…”

Section: Professional Recognitionmentioning

confidence: 99%

Navigating the Publication Process: An ASABE Journals’ Perspective

Fox¹,

Douglas-Mankin²,

Muthukumarappan³

et al. 2019

Transactions of the ASABE

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Abstract. HighlightsASABE journals publish impactful research in multiple article types in addition to research articles. Prospective authors should consider a journal’s peer-review quality, readership, metrics, and page charges. An article’s impact should be measured based on citations instead of predicted based on the journal’s impact factor. Always recommend subject matter experts as reviewers so that a manuscript can benefit from their suggestions. Publishing in ASABE journals offers opportunities for contributing to and being recognized by the profession. Keywords: Impact factor, Page charges, Peer-reviewed journals, Review quality, Review time

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“…Deposition and drift models of UAV spraying droplets have been established through wind tunnel experiments and field experiments to predict the drift distance and deposition distribution under various meteorological conditions, as well as to evaluate according to weather station data whether a particular time is suitable for pesticide spraying to help select the appropriate operational parameters for UAV spraying [ 3 , 4 , 5 , 6 ]. However, these models have poor real-time performance.…”

Section: Introductionmentioning

confidence: 99%

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

Tuan

Yang

et al. 2020

Sensors

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Unmanned Aerial Vehicles (UAVs) have been widely applied for pesticide spraying as they have high efficiency and operational flexibility. However, the pesticide droplet drift caused by wind may decrease the pesticide spraying efficiency and pollute the environment. A precision spraying system based on an airborne meteorological monitoring platform on manned agricultural aircrafts is not adaptable for. So far, there is no better solution for controlling droplet drift outside the target area caused by wind, especially by wind gusts. In this regard, a UAV trajectory adjustment system based on Wireless Sensor Network (WSN) for pesticide drift control was proposed in this research. By collecting data from ground WSN, the UAV utilizes the wind speed and wind direction as inputs to autonomously adjust its trajectory for keeping droplet deposition in the target spraying area. Two optimized algorithms, namely deep reinforcement learning and particle swarm optimization, were applied to generate the newly modified flight route. At the same time, a simplified pesticide droplet drift model that includes wind speed and wind direction as parameters was developed and adopted to simulate and compute the drift distance of pesticide droplets. Moreover, an LSTM-based wind speed prediction model and a RNN-based wind direction prediction model were established, so as to address the problem of missing the latest wind data caused by communication latency or a lack of connection with the ground nodes. Finally, experiments were carried out to test the communication latency between UAV and ground WSN, and to evaluate the proposed scheme with embedded Raspberry Pi boards in UAV for feasibility verification. Results show that the WSN-assisted UAV trajectory adjustment system is capable of providing a better performance of on-target droplet deposition for real time pesticide spraying with UAV.

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Prediction of Aerial Spray Release from UAVs

Cited by 46 publications

References 25 publications

Swath pattern analysis from a multi‐rotor unmanned aerial vehicle configured for pesticide application

Swath pattern analysis from a multi‐rotor unmanned aerial vehicle configured for pesticide application

Navigating the Publication Process: An ASABE Journals’ Perspective

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

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