Proceedings
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| Filter results8 paper(s) found. |
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1. 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 |
2. 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 |
3. AI-based Pollinator Using CoreXY RobotThe declining populations of natural pollinators pose a significant ecological challenge, often attributed to the adverse effects of pesticides and intensive farming practices. To address the critical issue of pollination in the face of diminishing natural pollinators, we are pioneering an AI-based pollinator that utilizes a CoreXY pollination system. This solution aims to augment pollination efforts in agriculture, increasing yields and crop quality while mitigating the adverse impacts of pesticide... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett |
4. AI-based Precision Weed Detection and EliminationWeeds are a significant challenge in agriculture, competing with crops for resources and reducing yields. Addressing this issue requires efficient and sustainable weed elimination systems. This paper presents a comprehensive overview of recent advancements in weed elimination system development, focusing on innovative technologies and methodologies. Specifically, it details the development and integration of a weed detection and elimination system based on the CoreXY architecture, implemented... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett |
5. AI-based Fruit Harvesting Using a Robotic ArmFruit harvesting stands as a pivotal and delicate process within the agricultural industry, demanding precision and efficiency to ensure both crop quality and overall productivity. Historically reliant on manual labor, this labor-intensive endeavor has taken a significant leap forward with the advent of autonomous jointed robots and Artificial Intelligence (AI). Our project aims to usher in a new era in fruit harvesting, leveraging advanced technology to perform this essential task autonomously... H. Kulhandjian, N. Amely, M. Kulhandjian |
6. 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 |
7. 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 |
8. 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 |