College - Author 1

College of Engineering

Department - Author 1

Electrical Engineering Department

Degree Name - Author 1

BS in Electrical Engineering



Primary Advisor

William Ahlgren, College of Engineering, Electrical Engineering Department


Each year wildfires cause significant loss of property, worsen people’s health, and destroy multiple ecosystems. On average, a wildfire season costs anywhere from 7.6-62.8 billion dollars due to fire containment, repair, and restoration [1]. It can take decades to recover from the crippling loss of land and take even longer to fully restore it. However, with the implementation of a robust early detection system, these losses can be significantly reduced. The current process for identifying wildfires involves visual identification, phone call alerts, and media tools primarily driven by park rangers and public reporting. Unfortunately, this system is not preventative and allows fires to grow in scale before adequate resources can be deployed to combat them. This is catastrophic in remote areas and leads to long drawn-out fire seasons that have recently become more destructive.

As climate change continues to accelerate the intensity of these wildfires, a key solution is to utilize advanced technologies to monitor, prevent, detect, and contain fires along with alerting first responders with critical data in a timely manner. The advanced technologies would incorporate a system of integrated communications that are all networked to government agencies and first responders. The new system focusses on early detection in high-risk areas by implementing an infrared sensing system with bandpass filtering that can detect fires and use long range radio/instant messaging to alert first responder agencies. This will allow first responders to be alerted to threats in remote areas and will save countless lives, improve people’s health, lessen impact to climate change, save ecosystems, and reduce economic loss from fire damage.

Senior Project-Integrating Wildfire Responses.pptx (3843 kB)

Fire Response Model (2).html (102 kB)
Fire Response Model