The AgriSpectraVision project addresses the pressing challenge of optimizing crop management in modern agriculture
🔗 Contact Information
Department
777 Glades Road
Boca Raton, FL 33431-0991
S.E. Wimberly Library
Sandbox
🔗 Project Leader
- Prajwal Nagaraj
🔗 Supervisor
- William E. Hahn
🔗 Project Description
The AgriSpectraVision project addresses the pressing challenge of optimizing crop management in modern agriculture. The objective of AgriSpectraVision is to harness the power of hyperspectral imaging and computer vision to revolutionize crop monitoring, enabling farmers and researchers to make data-driven decisions for healthier crops, increased yields, and reduced environmental impact by utilizing less fertilizer and optimizing precise use of farming tools. We will employ cutting-edge hyperspectral imaging technology to capture an extensive range of spectral data beyond human vision. This data will be collected by weather forecasting. The tower was repurposed to collect hyperspectral images to analyze crop health. State-of-the-art computer vision algorithms and machine learning models will be applied to process the hyperspectral data. These techniques will identify patterns, anomalies, and spectral signatures related to crop health, stress, nutrient status, diseases, as well as optimal irrigation times and soil fertility. The developed system will enable real-time, non-destructive monitoring of crops in the field. This information will be used to create detailed maps of the entire cultivation area, highlighting areas of concern and providing early warning signs of issues.
AgriSpectraVision will facilitate precision agriculture by guiding farmers in making precise interventions. This includes optimized resource allocation, such as targeted nutrient and fertilizer application, irrigation, and pest control. A user-friendly interface will present the collected data and insights to farmers, agronomists, fertilizer companies, and researchers. It will offer actionable recommendations and visualizations to aid in decision-making. Crop market value analysis compares the number of farmers farming the same crop in a specific area and determines which produce is best for each farmer’s location.
Early detection of stress, diseases, and nutrient deficiencies will lead to timely interventions, resulting in healthier crops. Data-driven decisions will maximize crop yields by optimizing resource usage and minimizing losses due to adverse conditions. Reduced reliance on excessive fertilizers, pesticides, and water will lower production costs and minimize environmental impact. AgriSpectraVision promotes sustainable agriculture by aligning practices with ecological conservation goals. The project will contribute to scientific knowledge by generating valuable data for crop science, agronomy, and environmental studies research.AgriSpectraVision aims to transform agriculture into a more efficient, sustainable, and data-informed industry. Providing precise insights into crop health and cultivation practices empowers farmers to make decisions that benefit both their yields and the environment. Ultimately, this project supports food security, reduces agricultural waste, and promotes sustainable land use.