Locasur

Locasur Logo

Inspiration

Public health teams have limited time, staff, and money to inspect mosquito breeding risks. We created Locasur to help them decide where to go and what to do after each visit.

What it does

Locasur turns area priority scores into inspection routes that fit staffing, working hours, and transport budgets. Teams can update access times, record findings, and track follow-up tasks.

How we built it

We used real satellite measurements from Tallo, Makassar, Indonesia, and simulated larvae labels to build an AI prioritization model. We connected it to a route planner and an offline-capable web app built with Python, JavaScript, HTML, and CSS.

Challenges we ran into

We worked to balance area priorities with travel time, inspection duration, resident availability, and budget limits. We also made replanning preserve completed visits and clearly labeled our simulation assumptions.

Accomplishments that we're proud of

We built a working planning and reporting workflow. In our demonstration, Locasur covered 68.7% of candidate priority compared with 56.4% for visiting the closest areas first under the same resource limits.

What we learned

A useful prediction needs a practical path to action. Local knowledge, clear comparisons, and inspection feedback help make a plan useful for field teams.

What's next for Locasur

We plan to co-design a pilot with local health teams and community mosquito monitors. We will evaluate actual travel times, inspection findings, costs, usability, and follow-up completion.