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Menegasso, A.E
Sharma, V
Jha, S
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Authors
Jha, S
Saraswat, D
Ward, M.D
Sobjak, R
Bazzi, C.L
Schenatto, K
Oliveira, W.K
Menegasso, A.E
Dhillon, R
Takoo, G
Sharma, V
Nagle, M
Castiblanco Rubio, F.A
Arun, A
Lee, B
Balmos, A
Jha, S
Krogmeier, J
Love, D.J
Buckmaster, D
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Topics
Big Data, Data Mining and Deep Learning
Artificial Intelligence (AI) in Agriculture
Data Analytics for Production Ag
Wireless Sensor Networks and Farm Connectivity
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2018
2024
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1. Analyzing Trends for Agricultural Decision Support System Using Twitter Data

The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method to... S. Jha, D. Saraswat, M.D. Ward

2. AgDataBox-IA – Web Application with Artificial Intelligence for Agricultural Data Analysis in Precision Agriculture

Agriculture has been continually evolving, incorporating hardware, software, sensors, aerial surveys, soil sampling for chemical, physical, and granulometric analysis (based on sample grids), and microclimatic data, leading to a substantial volume of data. This requires platforms to store, manage, and transform these data into actionable information for decision-making in the field. In this regard, Artificial Intelligence (AI) is the most widely used tool globally to mine and transform vast data... R. Sobjak, C.L. Bazzi, K. Schenatto, W.K. Oliveira, A.E. Menegasso

3. Machine Learning Approach to Study the Effect of Weather and Proposed Climate Change Scenarios on Variability in the Ohio Corn and Soybean Yield

Climate is one of the primary factors that affects agricultural production.  Climate change and extreme weather events have raised concerns about its effect on crop yields. Climate change patterns affect the crop yield in many ways including the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days. It is important to analyze the effect of climate change on yield variability for a better understanding of the effect... R. Dhillon, G. Takoo

4. OATSmobile: a Data Hub for Underground Sensor Communications and Rural IoT

Wireless Underground Sensor Networks (WUSNs) play a crucial role in precision agriculture by providing information about moisture levels, temperature, nutrient availability, and other relevant factors. However, the use of radio-frequency identification (RFID) devices for WUSNs has been relatively unexplored despite their benefits such as low power consumption. In this work, we develop a hardware platform, called OATSMobile, that enables radio-frequency identification (RFID) communications in WUSNs.... F.A. Castiblanco rubio, A. Arun, B. Lee, A. Balmos, S. Jha, J. Krogmeier, D.J. Love, D. Buckmaster

5. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial Intelligence

The Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos