The use of unmanned aerial vehicles and wireless sensor network in agricultural applications

Costa, Fausto Guzzo da; Ueyama, Jó; Braun, Torsten; Pessin, Gustavo; Osório, Fernando Santos; Vargas, Patrícia A.

doi:10.1109/igarss.2012.6352477

Cited by 138 publications

(82 citation statements)

References 8 publications

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“…Costa et al [101] described an architecture that can be employed to implement a control loop for agricultural applications where UAS are responsible for spraying chemicals on crops. Application of chemicals is controlled by the feedback obtained from a wireless sensor network (WSN) deployed on the crop field.…”

Section: Vegetation Monitoring and Precision Agriculturementioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

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Section: Vegetation Monitoring and Precision Agriculturementioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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“…This method offered a new range of application in many different research areas including forestry and agriculture (e.g., [1,2]), archeology (e.g., [3,4]) biology [5,6] and hydrology (e.g., [7,8]). An increase of studies using UAV photogrammetry is observed in geosciences, as well (e.g., [9,10]), where the DSMs and orthophotos are typically used for mapping and monitoring (e.g., [11,12]), object detection (e.g., [13]) or quantification of topographic changes, for instance (e.g., [14,15]).…”

Section: Introductionmentioning

confidence: 99%

Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers

2017

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Abstract:The use of Unmanned Aerial Vehicles (UAV) for photogrammetric surveying has recently gained enormous popularity. Images taken from UAVs are used for generating Digital Surface Models (DSMs) and orthorectified images. In the glaciological context, these can serve for quantifying ice volume change or glacier motion. This study focuses on the accuracy of UAV-derived DSMs. In particular, we analyze the influence of the number and disposition of Ground Control Points (GCPs) needed for georeferencing the derived products. A total of 1321 different DSMs were generated from eight surveys distributed on three glaciers in the Swiss Alps during winter, summer and autumn. The vertical and horizontal accuracy was assessed by cross-validation with thousands of validation points measured with a Global Positioning System. Our results show that the accuracy increases asymptotically with increasing number of GCPs until a certain density of GCPs is reached. We call this the optimal GCP density. The results indicate that DSMs built with this optimal GCP density have a vertical (horizontal) accuracy ranging between 0.10 and 0.25 m (0.03 and 0.09 m) across all datasets. In addition, the impact of the GCP distribution on the DSM accuracy was investigated. The local accuracy of a DSM decreases when increasing the distance to the closest GCP, typically at a rate of 0.09 m per 100-m distance. The impact of the glacier's surface texture (ice or snow) was also addressed. The results show that besides cases with a surface covered by fresh snow, the surface texture does not significantly influence the DSM accuracy.

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“…In this work nonlinear transformations permit to achieve a total decoupled model [5]. In this system the Process of applying chemicals can be controlled by means of wireless sensor network deployed on the agriculture field [6] …”

Section: Introductionmentioning

confidence: 99%

Remotely Operated Pesticide Sprayer Robot in Agricultural Field

Londhe¹,

Sujata²

2017

IJCA

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Despite the focus on industrialization, agriculture remains a dominant sector of the Indian economy both in terms of contribution to gross domestic product (GDP) as well as a source of employment to millions across the country. Agriculture plays a vital role in the Indian economy. Over 70 per cent of the rural households depend on agriculture as their principal means of livelihood. But an attack of pest in crops is one of the major problems to reduce the production growth in agriculture field. To deal with this kind of problem diagnosis of crop disease is very essential. This paper presents an engineering solution to tackle this kind of problem in which an automatic pesticide sprayer is involved to spray the pesticide to the localized area of the affected crops. This system is based on sprayer filled with pesticides. The Sprayer movement is controlled by DC motor at low velocity, up & down direction according to plant height. The design deals with three modules image capturing, processing and automatic pesticide spraying. The proposed system can remotely operate through any electronic device like mobile, laptop etc.

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The use of unmanned aerial vehicles and wireless sensor network in agricultural applications

Cited by 138 publications

References 8 publications

On the Use of Unmanned Aerial Systems for Environmental Monitoring

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers

Remotely Operated Pesticide Sprayer Robot in Agricultural Field

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