Monitoring natural environments with AI is difficult due to variations in lighting, weather, and seasons. Training robust AI models requires extensive datasets, which can be expensive and time-consuming to collect.
To solve this challenge, the AquaWatch Visual Environmental Intelligence (AVEI) uses the AW-108 camera to capture high-resolution images and process them on-device. This reduces data noise and creates targeted datasets for training accurate AI models.
Key features of AW-108:
Captures high-quality images in diverse conditions
Processes data on-device for efficient dataset compilation
Learns and adapts over time, reducing human intervention
How the AVEI process works:
Define the problem: Identify specific environmental challenges, like Combined Sewer Overflows (CSOs).
Data gathering: Collect high-fidelity visual data with the AW-108.
Model training: Train machine learning models to detect early signs of environmental issues.
Outcome refinement: Refine models to achieve desired outcomes, like reducing pollution.
API and insight delivery: Deliver insights via a user-friendly API for informed decision-making.
Ongoing calibration and support: The system continuously improves, reducing the need for human intervention.
This enables more efficient and effective environmental monitoring, real-time data for informed decision-making, reduced pollution and mitigated health risks
Contact us to find out how you can utilise the powerful AVEI tool and harness visual intelligence to solve real-world environmental problems.