Inspiration
Maintaining cleanliness in public communities such as schools, conference rooms and centers can often be resource-intensive. Traditional cleaning services rely on fixed schedules and manual inspections but can often inefficient, leading to wasted effort, energy and time. We have identified the need to optimize our robot cleaning operations using agentic AI to reduce environmental impact while ensuring cleaner, healthier public spaces. By leveraging Databricks' powerful data processing and AI capabilities, we built Jyson Darvis AI Cleaning Bot - an intelligent cleaning robot management system that dynamically calculates cleaning routes based on locational data.
What it does
These robots are designed to take instructions from a set of AI agents we have running within Databricks to calculate the shortest distance to traverse through conference rooms at DAIS 2025.
How we built it
Using standard Single Shot Databricks Agent approach
Challenges we ran into
How to chain tools together
Accomplishments that we're proud of
Our distance mapping between real building rooms
What we learned
How to use tools in Databricks Agents How to use agent tools on databricks
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