A Small Versatile Electrical Robot for Autonomous Spraying in Agriculture

Cantelli, Luciano; Bonaccorso, Filippo; Longo, Domenico; Melita, Carmelo Donato; Schillaci, Giampaolo; Muscato, Giovanni

doi:10.3390/agriengineering1030029

Cited by 74 publications

(39 citation statements)

References 18 publications

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“…For this purpose, the introduction of low-cost, time-saving, and easy-to-operate tools will play a key role in the acceptance and application of IPM in practice. Such techniques can also contribute to a broader market share of precision spraying machinery for horticultural production 3 . Most automated monitoring tools could provide maps of pest distributions, especially in phytosanitary sensitive environments such as greenhouses.…”

Section: Introductionmentioning

confidence: 99%

Rapid and low-cost insect detection for analysing species trapped on yellow sticky traps

Böckmann

Pfaff

Schirrmann

et al. 2021

Sci Rep

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While insect monitoring is a prerequisite for precise decision-making regarding integrated pest management (IPM), it is time- and cost-intensive. Low-cost, time-saving and easy-to-operate tools for automated monitoring will therefore play a key role in increased acceptance and application of IPM in practice. In this study, we tested the differentiation of two whitefly species and their natural enemies trapped on yellow sticky traps (YSTs) via image processing approaches under practical conditions. Using the bag of visual words (BoVW) algorithm, accurate differentiation between both natural enemies and the Trialeurodes vaporariorum and Bemisia tabaci species was possible, whereas the procedure for B. tabaci could not be used to differentiate this species from T. vaporariorum. The decay of species was considered using fresh and aged catches of all the species on the YSTs, and different pooling scenarios were applied to enhance model performance. The best performance was reached when fresh and aged individuals were used together and the whitefly species were pooled into one category for model training. With an independent dataset consisting of photos from the YSTs that were placed in greenhouses and consequently with a naturally occurring species mixture as the background, a differentiation rate of more than 85% was reached for natural enemies and whiteflies.

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Section: Introductionmentioning

confidence: 99%

Rapid and low-cost insect detection for analysing species trapped on yellow sticky traps

Böckmann

Pfaff

Schirrmann

et al. 2021

Sci Rep

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“…To reduce the physical presence of workers in areas to be sprayed with pesticides, the performance of the robots and ML algorithms needs to be accurate. The following reports have proposed the use of semi-autonomous operation of a teleoperated pesticide-spraying robot [ 86 , 87 , 88 , 89 ]. The operator would be able to remotely control the robots using a mouse, a remote, and digital, thus reducing the risk of exposure to hazardous pesticide exposure.…”

Section: Resultsmentioning

confidence: 99%

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Pishgar

Issa

Sietsema

et al. 2021

IJERPH

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Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker’s immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being.

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“…The authors introduced an autonomous Agricultural Robot (AgBot) System [106] that can detect weeds using Haar feature-based cascade classification and spray a controlled amount of herbicide or fertilizers while navigating using GPS. In [107], the authors proposed a solution for the connection between the autonomous vehicle and spray management system to perform spraying operations autonomously in the field. The architecture comprised of four subsystems, namely, mobile tracking robot, localization and navigation system, smart spraying system, and human-machine interface (HMI) system.…”

Section: E Autonomous Technologiesmentioning

confidence: 99%

IIoT Based Multimodal Communication Model for Agriculture and Agro-Industries

Almadani

Mostafa

2021

IEEE Access

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The population would reach ten billion by 2050, and experts believe that the agricultural sector needs to boost production by 70% to satisfy the demand. Traditional farming practices rely on primitive technology that creates a yield gap with low productivity. A paradigm shift towards merging new technologies in the agriculture sector would enhance productivity, optimize cost, and encourage sustainable development. In this paper, we review the necessity for the fusion of the Fourth Industrial Revolution technological approach in the agricultural domain. We discuss the gap in supply chain management for the Industrial sector and Agricultural sector and identify the issues of vendor-specific production systems. We propose a multimodal communication model for the systematic integration of multi-vendor agricultural production systems. Our model utilizes the Data Distribution Service (DDS) middleware to enable communication between heterogeneous production systems to perform farming operations in a coordinated manner. Experimental work is conducted on a small-scale hydroponic farm to evaluate the system performance in terms of throughput, latency, and packet delivery ratio (PDR). The throughput for our proposed DDS system has significantly improved with the use of the BATCH QoS policy for payload size less than 1024 bytes. However, we incur an average latency of approximately 235 microseconds for any payload size. The value of PDR is 1 for any payload size ensuring our system to be reliable. The results suggest that our model can enable interoperability between multi-vendor production systems in real-time while incurring minimum latency.

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A Small Versatile Electrical Robot for Autonomous Spraying in Agriculture

Cited by 74 publications

References 18 publications

Rapid and low-cost insect detection for analysing species trapped on yellow sticky traps

Rapid and low-cost insect detection for analysing species trapped on yellow sticky traps

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

IIoT Based Multimodal Communication Model for Agriculture and Agro-Industries

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