Predictive AI That Acts
Before the Mosquito Does
The first IoT + AI system built by Amazon students to predict dengue larval risk and automatically deploy Bti β a WHO-approved biological larvicide β before mosquitoes emerge.
Real-time readings from the Amazon
Updated every 3 seconds
Temperature & Humidity Trend
Boots-on-the-ground inspection β Satipo
Students physically inspect water containers weekly. AI recommends, humans confirm.
IR% = (containers with larvae / total inspected) Γ 100
| Zone | Container | Larvae | Risk | Bti Deployed |
|---|---|---|---|---|
| Jr. Amazonas | πͺ£ Bucket | 23 | HIGH | Yes β |
| Near central market | π΄ Tire | 11 | HIGH | Yes β |
| School yard | πͺ΄ Flowerpot | 0 | LOW | β |
| Jr. JunΓn | π§ Water tank | 8 | MEDIUM | Yes β |
| Residential block | π§Ί Tray | 0 | LOW | β |
| Jr. PerΓΊ | π’οΈ Barrel | 17 | HIGH | Yes β |
| Church area | πͺ£ Bucket | 3 | MEDIUM | Yes β |
| Plaza central | πͺ΄ Flowerpot | 0 | LOW | β |
| Jr. Ucayali | π’οΈ Barrel | 5 | MEDIUM | Yes β |
From sensor to action in 5 steps
We disclose what our system can β and can't β do
False positives may trigger unnecessary Bti release. False negatives may miss real outbreaks due to limited local training data.
Students physically inspect containers weekly using a standardized field protocol (IR% calculation). AI recommends β humans confirm before any large-scale deployment.
Community health workers review the dashboard weekly. Families decide whether to install the device in their home. The AI never acts alone.