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1. Instrumented Blades With Automated Control Used In Chisel Plough Acting In Variable DepthsSoil compaction is a problem that affects most of the tilled areas of Brazil, being caused by several factors, such as overloading and intense machine traffic, use of unsuitable tires for applied load and inflation pressures outside the recommendation, machines in the field with the water content of the soil not recommended and several other problems. There are available several models and systems of measuring soil compaction in Brazil; however, the sensors of the... K.P. Lanças, J. Testa, B.B. Fernandes, T.M. Machado |
2. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement. However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT)... D. Whattoff, D. Mouazen, D. Waine |
3. FOODIE Data Model for Precision AgricultureThe agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and temporal... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka |
4. Quo Vadis Precision FarmingThe agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka |
5. Closing Yield Gaps with GxExM and Precision AgricultureThere are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate. A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges. The yield gap –defined as the difference between current farmer yields and potential... C. Walthall, J. Hatfield, S. Schneider, M. Vigil |
6. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the TreeImage/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli |
7. Data-Driven Agricultural Machinery Activity Anomaly Detection and ClassificationIn modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular paths... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster |
8. Use Cases for Real Time Data in AgricultureAgricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can be... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos |
9. SmartAgriHubs FIE20 - Groundwater and Meteo Sensors and Earth Observation for Precision AgricultureThe solution developed under the SmartAgriHubs project in the scope of the Flagship Innovation Experiment FIE20 Groundwater and meteo sensors is an expert system to support farmers in decision-making process and planning process of field interventions. This FIE20 solution integrates various data sources and different analytical processes in a complete system and provides users an easy-to-use web map application as a common user interface. The FIE20 system integrates components developed during... K. Charvat, M. Kepka, R. Berzins, F. Zadrazil, D. Langovskis, M. Musil |
10. Private Simple Databases for Digital Records of Contextual Events and ActivitiesFarmers’ commitment and ability to keep good records varies tremendously. Records and notes are often cryptic, misplaced, or damaged and for many, remain unused. If such information were recorded digitally and stored in the cloud, we immediately solve some access and consistency issues and make this data FAIR (findable, accessible, interoperable, reusable). More importantly, interoperable digital formats can also enable mining for insights and analysis... M.S. Basir, J. Krogmeier, Y. Zhang, D. Buckmaster |
11. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial IntelligenceThe 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 |
12. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWANThe widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenting... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen |