Tailoring Visual Environmental Intelligence

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

The new AquaWatch AI Camera improves water quality monitoring by providing high-quality images and adapting to diverse water conditions.

How the AVEI process works:

1. Define the problem: Identify specific environmental challenges, like Combined Sewer Overflows (CSOs).

2. Data gathering: Collect high-fidelity visual data with the AW-108.

3. Model training: Train machine learning models to detect early signs of environmental issues.

4. Outcome refinement: Refine models to achieve desired outcomes, like reducing pollution.

5. API and insight delivery: Deliver insights via a user-friendly API for informed decision-making.

6. 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.

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