Proceedings :: International Society of Precision Agriculture

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Kempenaar, C

Kaushal, S

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Kempenaar, C

van Evert, F

Been, T

Kocks, C

Westerdijk, K

Nysten, S

Kaushal, S

Sharda, A

Topics

Decision Support Systems in Precision Agriculture

Big Data, Data Mining and Deep Learning

Type

Oral

Year

2016

2024

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Filter results2 paper(s) found.
1. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van Evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten Download paper
2. Enhancing Agricultural Feedback Analysis Through VUI and Deep Learning Integration A substantial amount of information relies on consumers, influencing aspects from product adoption to overall satisfaction. Similarly, the agricultural sector is entirely dependent on farmers, who dictate the success of products and highlight associated challenges. Our study aligns with this perspective, recognizing the significance of understanding farmers' needs to assist tractor manufacturing industries. As these industries aim for widespread adoption of their products among farmers, it... S. Kaushal, A. Sharda

Filter results2 paper(s) found.

1. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van Evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

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2. Enhancing Agricultural Feedback Analysis Through VUI and Deep Learning Integration

A substantial amount of information relies on consumers, influencing aspects from product adoption to overall satisfaction. Similarly, the agricultural sector is entirely dependent on farmers, who dictate the success of products and highlight associated challenges. Our study aligns with this perspective, recognizing the significance of understanding farmers' needs to assist tractor manufacturing industries. As these industries aim for widespread adoption of their products among farmers, it... S. Kaushal, A. Sharda