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Barros, M.F
Bishop, T.F
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Authors
Benavente, J.C
Cugnasca, C.E
Barros, M.F
Santos, H.P
http://icons.paqinteractive.com/16x16/ac, G
Barros, M.F
Cugnasca, C.E
Congona Benavente, J
Filippi, P
Jones, E.J
Fajardo, M
Whelan, B.M
Bishop, T.F
Topics
Sensor Application in Managing In-season Crop Variability
Engineering Technologies and Advances
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2010
2018
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1. Changes Of Data Sampling Procedure To Avoid Energy And Data Losses During Microclimates Monitoring With Wireless Sensor Networks

... J.C. Benavente, C.E. Cugnasca, M.F. Barros, H.P. Santos, G. Http://icons.paqinteractive.com/16x16/ac

2. An Inter-connection Model Between Standard Zigbee And Isobus Network (ISO11783)

The typical five-step cyclical process of precision agriculture includes soil and environment data collection, diagnosis, data analysis, precision field correction operation and evaluations. Usually, some steps are executed in field, others in the farm office and others in both. This can result in a complex system and consequently in waste of time and high cost in equipment, tools and workmanship. To simplify this process, the challenge is running... M.F. Barros, C.E. Cugnasca, J. Congona Benavente

3. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine Learning

The ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop