Agriculture
❯
Crop health Analysis
❯Ecosystems management from causal relation inference from observational data
Crop Diagnosis & Product Recommendations Through AI
For:
Farmers, Biochemical companies, Crop disease treatment manufacturers
Goal:
Improved Product Development / R&D, Improve Operation Efficiency
Real-time segmentation and prediction of plant growth dynamics using low- power embedded systems equipped with AI
For:
Agriculture, ecology management, sanitary services
Scope:
The project is devoted to the development of a low-power embedded system and AI algorithm for real-time plant segmentation and prediction of its growth. The proposed distributed system is aimed for use in greenhouses and remote areas, where edge-computing autonomous systems are in demand. A branch of this project also aims to develop the payload for drones for the segmentation of harmful plants in real-time.
Goal:
Improve Operation Efficiency
Ecosystems management from causal relation inference from observational data
For:
Environment, ecosystem
Scope:
Infer important latent variables to control a whole ecosystem using a database including human observation and sensor data.
Goal:
Improved Product Development / R&D, Improve Operation Efficiency
Precision Farming as a Service
For:
Farmers
Scope:
Use visual recognition to identify and help fight parasites attacking organic farms.
Goal:
Anticipate Risks, Improve Operation Efficiency
Ecosystems management from causal relation inference from observational data
For:
Environment, ecosystemGoal:
Improved Product Development / R&D, Improve Operation EfficiencyProblem addressed
To provide some suggestions for managing ecosystems and repeatedly improve
management with the introduction of possibly latent variables and new data.
Scope of use case
Infer important latent variables to control a whole ecosystem using a database including human observation and sensor data.
Sensor Network - IOT
AI: Perceive
Bayesian network
AI: Understand
Determine the best Option
AI: Act