Vulcan Ceres:

Vulcan Ceres is a suite of artificial intelligence (AI) applications helping farmers translate data into actionable insights, and make better decisions for yield and quality optimisation at a lower cost. Ceres uses a multi-sensory approach to generate intelligence for micro-supervision. A combination of satellite, unmanned aerial vehicle (UAV), internet of things (IoT) data and your enterprise data are put through signal processing and AI pipelines to generate actionable insights.

Our AI applications have the potential to increase yield by 5-15% and optimise business costs such as fertilisers, weedicides and labour by 10-20%.

Vulcan Ceres comes bundled with third party data like satellite images and weather data that can be combined with your own datasets such as operational and geospatial information.

Ceres Hyperdata: Ceres Hyperdata creates an analytical data model which is then consumed by our proprietary applications and/or integrates with your own analytical models or GIS applications. Hyperdata also offers various GIS layers and data that agronomists can use to easily select areas for investigation and/ or research. Data can be exported to integrate into their own research and analysis systems.
Ceres Sense+ and Replant+: The Sense+ module uses advanced AI models and image processing techniques to generate clean, rich images from satellite images and geospatial data for further processing. The processed and cleaned images are then run through proprietary computer vision and deep learning AI pipelines to generate various vegetation indices for assessment of tree health, water stress, and biomass.

Signal Processing:Auto Quality Control (QC) of Satellite & UAV images, Haze Detection & Removal, Cloud Detection & Removal, Shadow Detection & Correction, Crop Specific Vegetative Indices
AI-Generated Layers:Tree Locations, Tree Counts, Planting Lines, Blank Spots, Thinning Alerts, Tree point Density

Ceres Health+ and Nutrients: Ceres Health+ AI pipelines help to detect potential nutrient deficiencies and/or pest and disease incidence. Running satellite and UAV images through Health+ AI pipelines can identify potential areas suffering from nutrient deficiencies. Various inputs including leaf sampling information, ground sensors, historical pest, disease incidence, and weather, are combined with Multi-Spectral and Hyper-Spectral Vegetation Indices to create AI-based pest and disease surveillance models. These models offer early detection of any yield limiters, enabling you to take rapid action to protect your crops.

AI-Generated Layers:Various Vegetation Indices, Pest and Diseases alerts, Nutrient deficiency alerts, Tree Canopy

Ceres SmartGrader: SmartGrader automates the counting & grading of fruits. Ceres SmartGrader module uses standard camera resolution images to count and grade fruits, and can be deployed to mobile devices and used in the field without real-time data connectivity. By analysing the production & quality of harvested fruit, you can get insights into the quality of the harvesting activities. These insights can help you to fine tune the right time for harvesting and also trace underperforming harvesters.

Artificial Intelligence for Remote Sensing

Autor: Vulcan AI Pte. Ltd.