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California teenager invents AI-powered tool for early wildfire detection

The world is indeed lucky when our most brilliant minds choose to work for the common good, rather than chasing money or becoming master criminals. So Inhabitat wants to thank young Ryan Honary for his work on an early detection system for wildfires.

Sickened by the losses people sustained in the 2018 Camp Fire, California’s deadliest wildfire, Honary turned his attention to how to mitigate future disasters. In 2019, Honary won the $10,000 grand prize in the Ignite Innovation Student Challenge for his Early Wildfire Detection Network submission, which provides app technology to firefighters. He was only in fifth grade at the time.

Related: Rocky Mountains experience more severe and frequent wildfires

Turning 14 years old this summer and going into the eighth grade in the fall, Honary is busy working on SensoRy AI, the company he founded. With the help of his father, Hooman Honary, and a team of experts, the startup has already received a lot of attention. The Office of Naval Research awarded SensoRy AI a grant of nearly $1.6 million earlier this year.

Honary talked to Inhabitat about how he managed to achieve more than most people do in their lives before even getting to middle school as well as his vision for using AI and other technology for helping people in the future.

Ryan Honary with prototype of wildfire detection tool

Inhabitat: Tell us a bit about your early interest and training in science and artificial intelligence.

Honary: I was always interested in the applications of technology. Because of my dad’s background, I was exposed early on to programming, and I started creating my websites when I was in third grade. I learned Python and Javascript in a local after-school program called Ardent Academy.

In parallel, I became very passionate about animals and the environment. I also became concerned as I saw how much the environment is under pressure because of a variety of issues. My science teachers at school encouraged me and provided many resources for me to study environmental issues.

These issues became very personal when massive wildfires started hitting California on a pretty regular basis, ruining the air quality, destroying homes and unfortunately killing some people. I started thinking about how the power of technology can be used to solve many environmental problems such as wildfires. I had been reading about the predictive powers of AI. I reached out to and started learning about artificial intelligence from a family friend who was a PhD student at UCLA working on Machine Learning.

Inhabitat: How did you research wildfires?

Honary: I was shocked when I first heard about the Camp Fire of 2018 on the TV. From then, I started reading about wildfires all over the internet. Both from places such as National Geographic as well as CAL FIRE. I started researching why it is so hard to manage and extinguish these massive wildfires.

More specifically, in order to capture data to train the Machine Learning models on my fire detectors, I captured real-world data from Google Earth about the Camp Fire of 2018 in Northern California. There is a tremendous amount of useful data available for free on Google Earth. It’s an awesome resource.

Phone screen with information on temperature, humidity, and smoke detection

Inhabitat: Could you give a basic explanation of how your system works?

Honary: My system consists of a network of detectors: mini meteorological stations and fire detectors. My network consists of mesh networking, which means that all the nodes can communicate with each other. As a result, once a fire is detected by a fire detector, the information can be communicated from node-to-node until it reaches a mini meteorological station where it will then be sent to the app I created using Javascript.

In order for the system to operate, the detectors must be 100-150 feet apart, so it would depend on the size of the area being monitored to know how many sensors would be needed. The sensors would be placed in rugged and fragile places. The sensors on the detector can track the fires and communicate that information in real-time to the mini meteorological station and then to the app. Also, machine learning can be used to predict where the fires are going to go.

Inhabitat: What was it like to win the Ignite Innovation Student Challenge?

Honary: When I first found out I won, I was shocked! I never thought that I could’ve won a national-level science competition, especially since I was a fifth-grader and it was a middle school competition! That win inspired me to continue working on my project and helped bring me where I am today.

Ryan Honary sitting behind a desk

Inhabitat: What is your role in SensoRy AI now?

Honary: I am leading the environmental part of my company. I am hoping to turn our platform into a real working product solving real-world environmental problems. As part of that, I have contacts with scientists from Forest Service and the EPA which provide me data and guidance, enabling me to conduct research.

Inhabitat: What’s it like to be a kid working closely with the Office of Naval Research and other much older colleagues?

Honary: I feel honored that a distinguished research group, such as the Office of Naval Research, has decided to offer our project a research grant. It is sometimes a little scary to work with older people, but I enjoy learning from their experience. I am hoping to attract more people from my generation to join our company. At the end of the day, the environment is going to be a big responsibility for my generation.

On the left, Ryan Honary with award from Red Cross. On the right, Honary testing early wildfire detection tool on a fire pit.

Inhabitat: Tell us a little bit about your hope for future applications of the early detection technology.

Honary: The early detection technology can be used in future applications such as methane gas leaks in refineries and oil plants and water contamination caused by mining or other human-based activities. In any scenario where an environmental disaster can start from a high-risk location, our early detection and growth prediction platform can be utilized to help preserve the environment.

Inhabitat: What else should readers know about you and SensoRy AI?

Honary: We are a group of technologists who are very passionate about leveraging technology and AI to solve environmental problems. We have access to sophisticated AI experts as well as research funding. We would love to help anyone who has an environmental problem and is looking for technology-based solutions.

+ SensoRy AI

Images via SensoRy AI and NASA

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