Harvesting solutions: tackling agricultural challenges with advanced technologies.
Rapid population growth strains food production, exacerbating the need for sustainable practices. Climate variability introduces unpredictability, affecting crop yields and requiring adaptive strategies. Resource constraints, including water scarcity and arable land availability, compound the complexity. These problems all have to be solved without destroying the environment.
Theta Vision wants to help address these complexities with a holistic and technologically advanced approach to propel agriculture into a resilient and sustainable future.
Domain knowledge
Collaboratively, we are at the forefront of agricultural innovation, driving groundbreaking work on mathematical models that transcend boundaries across various crops. These models, the result of collaboration with experienced growers and researchers, embody decades of industry knowledge. Rooted in data-driven insights, our project revolutionizes indoor farming by providing adaptable solutions for a multitude of crops.
To make the mathematical model insightful to all, we are also developing a custom user interface that requires minimal training. This interface seamlessly integrates with our mathematical models, empowering users to leverage the full potential of the models.
Precision seeding
In the realm of precision agriculture, Theta Vision leverages the capabilities of computer vision to redefine the seeding process. Through the strategic use of synthetic data augmentation, we address a common challenge where up to 10% of seedling cups from automated seeding machines remain empty, we developed a solution that employs computer vision algorithms. Taking innovation further, our solution is implemented on an edge device, ensuring real-time analysis directly at the source.
This dual approach not only eliminates missed yield and resource wastage but also exemplifies our commitment to pushing the boundaries of agricultural technology. Theta Vision envisions a future where missed yield and resource wastage are eliminated. Our seamless integration of synthetic data and edge computing maximizes efficiency, marking strides in the evolution of precision seeding.
