Reduce resource wastage, manage risk and boost production yields
with our precision agriculture and smart forestry solution
Intelligent AI-based data analytics at scale
Commercial plantations and forestry projects face a number of common challenges. They can be costly to monitor manually due to their sheer size and need huge amounts of real-time data to run efficiently and profitably.
Using geospatial and algorithmic models deployed over cloud, Aya empowers organisations to automate traditionally manual operations at scale.
Tree counting:
count and geolocate trees and other landed assets
Yield prediction:
predict future yields before harvest
Nutrient deficiency detection:
visualise plant health through vegetation indexes
Pest and disease detection:
identify at risk crops early for timely interventions
Blank spot analysis:
identify sites that can be replated for land optimization
Aya Smart Palm Management Solution
Cloud-based geospatial AI solution for palm plantations:
Tree counting: model built with data from Africa and Malaysia; with 20,000 instances of palm trees; crown size, height, geolocation, Precision rate: 98%
Bunch counting and grading: count palm bunches and assess the evel of ripeness to an accuracy of 96% using RGB drone imagery
Yield prediction: methodology leverages aerial data, GIS and field data to accurately forecast palm yield before harvest
Nutrient Detection: visualize plant health status through vegetation indexes such as NDVI
Pest and disease: identify areas affected by leaf spots, blight spots, red palm weevil and others with 95% accuracy.
How does our solution work
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CASE STUDIES
Combining Soil Acidity Data with Product Sales to Create Unique Business Intelligence
Demeter, an agricultural inputs supplier that operates in West Africa, specializes in working with smallholder farmers to enhance crop yields using primarily organic fertilizers. In order to optimize their product offers and serve the needs of their customers, Demeter sought to utilize open-source data on soil acidity. This information would be used to gain insights into their target markets and customize product recommendations.
Leveraging Drones and AI to Increase the Efficiency and Decrease Risk in Reforestation Projects
Oko Environmental, a reforestation company dedicated to combating climate change by establishing indigenous forests in West Africa, intended to utilize drones and machine learning solutions to gather valuable data and insights regarding their reforestation projects.
Using AI and Drones to Create Precision Agricultural Systems for Commercial Farming
Managing large-scale commercial farms necessitates a lot of progress tracking and repetitive tasks, in addition to being manually overwhelming. However, crop management systems powered by drone-fed computer vision models are a solution to the traditional system of manual data collection, while improving data accuracy and providing valuable insights into farming operations.
Building a Model to Rapidly Identify Disease in Ghana’s Maize Plants
Maize is one of the most important crops for Ghana’s agricultural industry; there have been significant, largely successful, investments into finding solutions to increase yields over the years. However, maize diseases still pose a significant challenge for maize farmers and communities.
Sourcing and Annotating Large Volumes of Agricultural Imagery for Precision Spraying
Client X is a leading AgTech company focused on improving agricultural productivity and sustainability through cutting-edge technology solutions. Their aim was to have their in-house data science team develop a computer vision model that would detect and identify weeds.
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Feel free to contact us and schedule a free consultation if you wish
to discuss how we can add value to your project.