Drone networks detect wildfires quickly with low budget
Rapid drone-based wildfire detection at a fraction of current prevention spending
Computers and Society
Summary
Wildfires can get very big if not spotted early. This paper shows how drones can be placed and routed to detect fires fast while costing much less than current methods. The authors tested their approach on thousands of real California fires, finding that drones could spot most fires quickly within a budget that's a small fraction of current spending. The key to success is covering wide areas with drones and planning their paths well.
What this means in practice
- •For wildfire prevention agencies: Plan and deploy drone-based wildfire monitoring networks that detect fires quickly at a fraction of current prevention budgets.
- •For environmental monitoring teams: Integrate optimized drone routing strategies into existing fire detection systems to improve early response times.
Authors
Romain Puech, Danique de Moor, Ana Trišović, Dimitris Bertsimas
Abstract
Early wildfire detection is critical to prevent small ignitions from escalating into large-scale disasters, yet current monitoring systems lack a quantitative framework for allocating detection infrastructure at scale. We jointly optimize the placement of monitoring infrastructure and the routing of autonomous drones under realistic operational constraints to quantify the investment required for rapid, large-scale wildfire detection. Evaluated out-of-sample on 3,693 California ignitions from 2021-2024, an optimized drone network operating at a $100 million five-year budget detects 97.3% of fires, including 74% within the first hour. Amortized over five years, that budget is about $20 million per year, roughly 5% of California's annual wildfire-prevention expenditure. Under current technology costs, drone-based monitoring is substantially more cost-effective than static ground sensors. Detection is governed primarily by spatial coverage, while routing strategy mainly determines detection speed.