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Smart agriculture
Plant imagery, vision models, and field context form an analysis flow for appearance candidates and condition records.
Products used: Plant Doctor · Edge Vision · Asterism
Plant inspection needs consistent image capture and records to compare appearance changes across time and growing areas.
Lighting, angle, occlusion, and crop differences affect model review, while a single inference cannot replace professional confirmation.
Image-quality checks, vision inference, candidate classification, and human review are composed with an interface for future environmental-data comparison.
Receive still, video, or confirmed live sources.
Review lighting, angle, clarity, and completeness.
Analyze plant appearance within a validated scope.
Organize candidate states and retain human confirmation.
Store time, area, and result context.
Confirm plants, appearance states, and the public scope.
Establish capture, quality, and annotation rules.
Check outputs, constraints, and the human-review method.
Place candidate results in the existing inspection record.
The workflow defines image and annotation rules, validates model output formats, then adds results to inspection and review records.
Image input, model analysis, structured output, and human review have been validated; recognition scope remains dependent on crop and data conditions.
No quantitative indicators are currently approved for public release.
Turn plant imagery and field context into traceable review support
Image models and field data support plant-condition review, creating a consistent information entry point for inspection and management decisions.
View productRun image analysis and event integration close to the data source
Image input, model inference, event decisions, and system outputs run in an edge environment, shortening the path from data to application.
View productCompose sensing, models, decisions, and device control into an adaptable flow
Asterism is Constellation’s core platform direction, connecting data inputs, edge analytics, decisions, safety conditions, and device outputs through explicit modules.
View productCombine environmental sensing, plant imagery, Edge AI, decisions, schedules, and device control around crop and field requirements.
View solutionDeploy image models to Edge devices and connect cameras, video, RTSP, events, and structured output.
View solutionSensor data, environmental analysis, schedules, and device control form a greenhouse flow that retains human intervention and safety conditions.
Products used: Asterism · Environment Control
View case detailsVision models run on edge devices to validate camera input, inference, structured results, and event integration.
Products used: Edge Vision · Custom Edge AI · Asterism
View case detailsMultiple sensor inputs, schedules, decisions, safeguards, and control outputs form a traceable field workflow.
Products used: Asterism · Environment Control · Custom Edge AI
View case detailsShare the field context, available data, equipment interfaces, and validation question. We can clarify a bounded next step without assuming a finished deployment.
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