Collaborative AI for smarter and safer urban services
This video explains how collaborative AI (Artificial Intelligence) enables smarter, safer and more efficient urban services by combining the expertise of product specialists with the power of deep learning. It introduces the Robovision platform and shows how AI models can be created, scaled and deployed across smart city environments without requiring data‑science expertise.
You’ll learn why collaborative intelligence is essential for real‑world AI adoption, how distributed stakeholders work together on one platform, and how AI supports predictive urban services such as traffic analysis, safety monitoring, public hygiene, fall detection and emergency alerts. Through practical examples from manufacturing, healthcare, greenhouse robotics and city infrastructure, the video shows how deep learning can be scaled reliably and responsibly.
Topics covered
- How collaborative intelligence bridges product expertise and AI development
- Key smart city use cases including safety, surveillance and traffic analysis
- How Robovision enables non‑technical users to build and deploy AI models
- Practical examples from healthcare, horticulture, recycling and public hygiene
- Why scalable tooling is essential for reliable deep learning in urban settings
Video timeline
- 00:00 - Introduction to Robovision and core industries
- 00:40 - Introduction of Robovision through Jonathan Berte , Founder & CEO
- 02:30 - Challenges with AI
- 03:40 - Collaborative Intelligence
- 04:57 - Smart city use cases: safety, traffic, security, monitoring
- 07:24 - Solution and tools of Robovision: 2D labeling Tools
- 07:46 - 3D labeling tools
- 08:05 - Further use cases
- 13:52 - Q&A
Who should watch
Ideal for smart‑city planners, AI developers, public‑sector innovators, urban‑infrastructure specialists, system integrators and anyone exploring scalable machine‑vision solutions for city environments.
Watch the full video to discover how collaborative AI is transforming urban services.