Development of a flexible electronic control unit for seamless integration of machine vision to CAN-enabled boom sprayers for spot application technology

This research work aimed to develop an Electronic Control Unit (ECU) to establish a flexible bridge between machine vision and boom sprayer to control nozzles individually for pesticide spot application based on the Controller Area Network (CAN). The ECU consisted of two electronic entities. The first used UART protocol to parse machine vision messages, detect pest areas, and convert them into binary arrays for nozzle activation. The second received these arrays and generated nozzle controller CAN frames which were broadcast to control the sprayer nozzles on the implement bus. The ECU was tested in four scenarios involving combinations of three machine vision systems and two nozzle systems. The lab tests confirmed, assuming accurate detections, the ECU successfully sent spray commands to all targets across various camera-nozzle ratios. However, at specific ratios (1:3 and 1:6), some nozzles opened in unintended patterns. In the fourth scenario conducted in the field at a 1:2 ratio, all targets were sprayed regardless of their dimensions and distribution in the field. In this scenario, the sprayer operated at speeds of 3.22 km/h, 6.44 km/h, and 9.66 km/h, demonstrating real-time spraying with 55° angled nozzles, where the ECU sent CAN messages every 10ms and issued 400 ms spray commands upon detection, achieving a minimum spray length of 345 mm per detection.

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Institutions

Publication Details

Journal
Smart Agricultural Technology
Published
2024-10-28
DOI
https://doi.org/10.1016/j.atech.2024.100618
Citations
2
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.20

Funders

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article

Development of a flexible electronic control unit for seamless integration of machine vision to CAN-enabled boom sprayers for spot application technology

Ahmad Al-Mallahi, Mozammel Bin Motalab
2 citations
Smart Agricultural Technology
Smart Agriculture and AI
1.20
article

Development of a flexible electronic control unit for seamless integration of machine vision to CAN-enabled boom sprayers for spot application technology

Ahmad Al-Mallahi, Mozammel Bin Motalab
article en
2 citations

Abstract

This research work aimed to develop an Electronic Control Unit (ECU) to establish a flexible bridge between machine vision and boom sprayer to control nozzles individually for pesticide spot application based on the Controller Area Network (CAN). The ECU consisted of two electronic entities. The first used UART protocol to parse machine vision messages, detect pest areas, and convert them into binary arrays for nozzle activation. The second received these arrays and generated nozzle controller CAN frames which were broadcast to control the sprayer nozzles on the implement bus. The ECU was tested in four scenarios involving combinations of three machine vision systems and two nozzle systems. The lab tests confirmed, assuming accurate detections, the ECU successfully sent spray commands to all targets across various camera-nozzle ratios. However, at specific ratios (1:3 and 1:6), some nozzles opened in unintended patterns. In the fourth scenario conducted in the field at a 1:2 ratio, all targets were sprayed regardless of their dimensions and distribution in the field. In this scenario, the sprayer operated at speeds of 3.22 km/h, 6.44 km/h, and 9.66 km/h, demonstrating real-time spraying with 55° angled nozzles, where the ECU sent CAN messages every 10ms and issued 400 ms spray commands upon detection, achieving a minimum spray length of 345 mm per detection.

Smart Agricultural TechnologyVol. 9
Dalhousie University (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 16%
Smart Agriculture and AI
1.20
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Development of a flexible electronic control unit for seamless integration of machine vision to CAN-enabled boom sprayers for spot application technology — Ahmad Al-Mallahi, Mozammel Bin Motalab · Smart Agricultural Technology (2024) | TGRS Research Map | TGRS