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Berretta, B.G
Brokesh, E
Botsali, F.M
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Authors
Pecker, K
Botsali, F.M
Topal, A
Zengin, M
JANBAZIALAMDARI, S
Brokesh, E
Rai, S
Sharda, A
Berretta, B.G
Topics
Adoption of Precision Agriculture
Digital Agriculture Solutions for Soil Health and Water Quality
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2008
2024
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1. The Review of Studying and Using Advanced Technologies for Site Specific Management in Konya, Turkey

Using advanced (information) technologies in agriculture is increasing rapidly especially in the developed countries such as USA, Japan, and some members of EU. Advanced technologies in agriculture are mostly based on sensors. Site specific management is a form of agricultural management, which is governed by optimum use of variables. Input such as chemical, water, and seed in agricultural production can be managed by using the technologies. Geographic information systems (GIS), Global Position... K. Pecker, F.M. Botsali, A. Topal, M. Zengin

2. Integrating Collected Field Machine Vibration Data with Machine Learning for Enhanced Precision in Agricultural Operations

In this research, we provide an innovative combination of the Agricultural Vibration Data Acquisition Platform (avDAQ) with cutting-edge machine learning methods for data collecting from agricultural machinery. The avDAQ system, which has a strong connection to a GPS sensor, provides precise spatial information to the vibration data that has been collected, providing an in-depth explanation of the locations of the vibrations. The objective is to fully utilize avDAQ's potential to extract detailed... S. Janbazialamdari, E. Brokesh

3. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision Agriculture

In precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision technology.  We... F. Sidharth, A. Sharda, B.G. Berretta