Narrator: Imagine a world where our wildlife is at risk, and conservation efforts are hindered by challenges like limited internet access in remote areas and the complexities of identifying animal species,
[Scene Transition to Wildlife.ai Website]
Narrator: Welcome to Wildlife.ai, a charitable trust using artificial intelligence to accelerate wildlife conservation. Our current project involves open-source wildlife cameras capturing and identifying species, a critical initiative for global conservation efforts.
[Problem Statement]
Narrator: In the vast landscapes where these cameras operate, internet access is uncertain. Notification alerts are unreliable, and financial constraints make hosting solutions impractical. How do we ensure real-time communication and data processing in these challenging conditions?
[User Perspective]
[Scene Transition to Enthusiast Using Mobile App]
Narrator: Enter our solution—an intuitive mobile application designed for users like you, the biologist out in the field, the nature enthusiast eager to contribute. With just a few taps on your mobile device, you can control the wildlife camera—turn it on or off, adjust settings, and upload models.
[Scene Transition to App Receiving Wildlife Alerts]
Narrator: Receive instant alerts directly to your mobile app when the camera captures a moment. No need for emails or central websites. It's all about simplicity and direct communication.
[Scene Transition to Analyzing Videos on App]
Narrator: Analyze captured videos using third-party platforms seamlessly integrated into the app. Label videos for training edge models and contribute to the broader conservation community.
[Scene Transition to Publishing Frames on iNaturalist]
Narrator: Publish frames to iNaturalist for experts to assist with species identification. Your contribution becomes part of a global network working together to protect biodiversity.
[Scene Transition to Long-term Vision]
Narrator: Our phased approach ensures a sustainable, user-friendly solution. We start with the essential features, gradually expanding to more integrations, making Wildlife.ai a leader in AI-driven wildlife conservation.
[Transition to Architecture Overview]
Narrator: Now, let's delve into the architecture that powers this solution.
HERE we can do the boring part of walking people over our repo to explain the solution.
[Closing Scene]
Narrator: This proposed solution for Wildlife.ai, is not just addressing the challenges of today; it is shaping the future of wildlife conservation. Join us in this journey towards a world where AI empowers us to protect and preserve the incredible biodiversity that surrounds us.
Video Script: Wildlife Conservation Solution
[Opening Scene]
Narrator: Imagine a world where our wildlife is at risk, and conservation efforts are hindered by challenges like limited internet access in remote areas and the complexities of identifying animal species,
[Scene Transition to Wildlife.ai Website]
Narrator: Welcome to Wildlife.ai, a charitable trust using artificial intelligence to accelerate wildlife conservation. Our current project involves open-source wildlife cameras capturing and identifying species, a critical initiative for global conservation efforts.
[Problem Statement]
Narrator: In the vast landscapes where these cameras operate, internet access is uncertain. Notification alerts are unreliable, and financial constraints make hosting solutions impractical. How do we ensure real-time communication and data processing in these challenging conditions?
[User Perspective]
[Scene Transition to Enthusiast Using Mobile App]
Narrator: Enter our solution—an intuitive mobile application designed for users like you, the biologist out in the field, the nature enthusiast eager to contribute. With just a few taps on your mobile device, you can control the wildlife camera—turn it on or off, adjust settings, and upload models.
[Scene Transition to App Receiving Wildlife Alerts]
Narrator: Receive instant alerts directly to your mobile app when the camera captures a moment. No need for emails or central websites. It's all about simplicity and direct communication.
[Scene Transition to Analyzing Videos on App]
Narrator: Analyze captured videos using third-party platforms seamlessly integrated into the app. Label videos for training edge models and contribute to the broader conservation community.
[Scene Transition to Publishing Frames on iNaturalist]
Narrator: Publish frames to iNaturalist for experts to assist with species identification. Your contribution becomes part of a global network working together to protect biodiversity.
[Scene Transition to Long-term Vision]
Narrator: Our phased approach ensures a sustainable, user-friendly solution. We start with the essential features, gradually expanding to more integrations, making Wildlife.ai a leader in AI-driven wildlife conservation.
[Transition to Architecture Overview]
Narrator: Now, let's delve into the architecture that powers this solution.
HERE we can do the boring part of walking people over our repo to explain the solution.
[Closing Scene]
Narrator: This proposed solution for Wildlife.ai, is not just addressing the challenges of today; it is shaping the future of wildlife conservation. Join us in this journey towards a world where AI empowers us to protect and preserve the incredible biodiversity that surrounds us.
[End Scene]