Open Data Model for (Precision) Agriculture Applications and Agricultural Pollution Monitoring

Řezník, Tomáš; Charvát, Karel; Vojtěch, Lukáš; Horáková, Šárka; Kepka, Michal

doi:10.2991/ict4s-env-15.2015.12

Cited by 25 publications

(11 citation statements)

References 14 publications

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“…Given the technologies assessed above, other researchers have described how IoT systems have the potential to collect field sensor data in real time and feed the data to integrated modeling tools for producing decision outputs for irrigation and other farming activities [21]. According to [22], an information system for precision agriculture will depend on how data are stored, managed, accessed, and ultimately combined in order to make sound decisions. With knowledge based on these prior explorations of typical components of IoT for agricultural systems, this work focuses on an IoT system that first includes not only sensor data, but also Web-based weather services, and second, modeling of the irrigation requirements for decision making in the context of rice farming in Rwanda.…”

Section: Decision Modelingmentioning

confidence: 99%

Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda

Bamurigire

Vodacek

Valko³

et al. 2020

Agriculture

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The central role of water access for agriculture is a clear challenge anywhere in the world and particularly in areas with significant seasonal variation in rainfall such as in Eastern and Central Africa. The combination of modern sensor technologies, the Internet, and advanced irrigation equipment combined in an Internet of Things (IoT) approach allow a relatively precise control of agricultural irrigation and creating the opportunity for high efficiency of water use for agricultural demands. This IoT approach can thereby increase the resilience of agricultural systems in the face of complex demands for water use. Most previous works on agricultural IoT systems are in the context of countries with higher levels of economic development. However, in Rwanda, with a low level of economic development, the advantages of efficient water use from the application of IoT technology requires overcoming constraints such as lack of irrigation control for individual farmers, lack of access to equipment, and low reliability of power and Internet access. In this work, we describe an approach for adapting previous studies to the Rwandan context for rice (Oryza sativa) farming with irrigation. The proposed low cost system would automatically provide irrigation control according to seasonal and daily irrigational needs when the system sensors and communications are operating correctly. In cases of system component failure, the system switches to an alternative prediction mode and messages farmers with information about the faults and realistic irrigation options until the failure is corrected. We use simulations to demonstrate, for the Muvumba Rice Irrigation Project in Northeast Rwanda, how the system would respond to growth stage, effective rainfall, and evapotranspiration for both correct operation and failure scenarios.

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Section: Decision Modelingmentioning

confidence: 99%

Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda

Bamurigire

Vodacek

Valko³

et al. 2020

Agriculture

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“…The results of measurements comprise the locations and attributes described in the UML (Unified Modelling Language) class diagram in Figure 2. The used data model represents a specialization of the Open data model for precision agriculture, as defined by Řezník et al [23]. Figure 2 depicts the ISO 19156 schema only partially; the class “TrackingResult” demonstrates the specialization of the ISO 19156 generic abstract class “Result”.…”

Section: Methodsmentioning

confidence: 99%

Deployment and Verifications of the Spatial Filtering of Data Measured by Field Harvesters and Methods of Their Interpolation: Czech Cereal Fields between 2014 and 2018

Řezník

Pavelka

Heřman

et al. 2019

Sensors

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Yield mapping is a subject of research in (precision) agriculture and one of the primary concerns for farmers as it forms the basis of their income and has implications for subsidies and taxes. The presented approach involves deployment of field harvesters equipped with sensors that provide more detailed and spatially localized values than merely a sum of yields for the whole plot. The measurements from such sensors need to be filtered and subject to further processing, including interpolation, to facilitate follow-up interpretation. This paper aims to identify the relative differences between interpolations from (1) (field) measured data, (2) measured data that were globally filtered, and (3) measured data that were globally and locally filtered. All the measured data were obtained at a fully operational farm and are considered to represent a natural experiment. The revealed spatial patterns and recommendations regarding global and local filtering methods are presented at the end of the paper. Time investments into filtering techniques are also taken into account.

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“…In developing and modernization of the harvesting using modern IT-based tools and systems; Agricultural Informatics is applicable [6], [11], [29].…”

Section: Agricultural Informatics: the Root And Functions With The Acmentioning

confidence: 99%

Agricultural Informatics: The emerging field with references to potentiality as Post Doctoral Certificate Programs

Paul¹

2020

IJIC

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Agricultural Informatics is an applied science dedicated in the advancement of the agricultural and allied areas with the help of Information Technology and Computing. The field is interdisciplinary in nature and helps in various pre-production and post-production activities. Agricultural Informatics has gradually become a field of study, and many countries have started offering various degrees on Agricultural Informatics and allied areas. Technologies viz. Database, Web Technologies, Networking, Multimedia, and Software, are widely used in Agricultural Informatics practice. Most of the programs of Agricultural Informatics are at Bachelors, Masters and Doctoral level only, only a few are offered as post-doctoral research opportunity as Post Doctoral Fellow. However, there is a potentiality in offering another emerging, higher qualification program known as Post Doctoral Certificate Program. The Post Doctoral Certificate Program is academic in nature. Few universities of the United States and the United Kingdom offering this degree, hence there is a potentiality to offer Post Doctoral Certificate in Agricultural Informatics. This paper discusses the various aspects of Agricultural Informatics, including its uses, features, functions etc. regarding prospects of Post Doctoral Certificate Program Agricultural Informatics.

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Open Data Model for (Precision) Agriculture Applications and Agricultural Pollution Monitoring

Cited by 25 publications

References 14 publications

Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda

Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda

Deployment and Verifications of the Spatial Filtering of Data Measured by Field Harvesters and Methods of Their Interpolation: Czech Cereal Fields between 2014 and 2018

Agricultural Informatics: The emerging field with references to potentiality as Post Doctoral Certificate Programs

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