EnviroFlame

Arduino ESP with flame, sound, and humidity sensor
The finished prototype with our team name, EVE

Inspiration

Wildfires have devastating effects on both the environment and human populations. They destroy wildlife habitats, contribute to air pollution, accelerate soil erosion, and disrupt climate stability. In addition to wildfires, illegal logging poses a serious threat by degrading forest ecosystems and reducing natural fire barriers. Detecting and preventing these activities at the root is crucial for environmental conservation.

What it does

To address these challenges, we developed EnviroFlame, a smart wildfire and illegal logging detection system designed to monitor environmental conditions in real time. Powered by the ESP32 microcontroller, EnviroFlame is a cost-effective, energy-efficient, and scalable solution that utilizes three key types of sensors:

Heat Sensors: Detect unusually high temperatures, signaling potential fire outbreaks.
Humidity Sensors: Measure moisture levels in the environment, as low humidity increases fire risks.
Sound Sensors: Monitor noise levels to identify illegal logging activities.

By analyzing sensor data, EnviroFlame provides real-time updates of the temperature, humidity and noise level of natural forested areas and sends automatic alerts to authorities when wildfire risks or illegal activities are detected.

Wildfire Detection: When EnviroFlame detects extreme heat levels and low humidity, it sends immediate alerts to authorities, enabling quick intervention to prevent fires from spreading.
Illegal Logging Detection: The system monitors noise levels in forested areas. In undisturbed environments, the noise of nature is typically 30–40 dBA, while logging machinery, such as chainsaws and skidders, can exceed 85–100 dBA. When EnviroFlame detects abnormal noise levels, it notifies authorities of possible illegal logging and ensures quick intervention

How we built it

Our prototype is built using an ESP32 microcontroller, allowing for efficient data collection and transmission. The final design will incorporate fireproof and waterproof materials: fire-rated gypsum board, mineral wool, intumescent coatings, and fire-resistant sealants to ensure durability in forested environments. EnviroFlame devices are intended to be mounted on trees or buried at their roots, strategically distributed across protected forested areas for optimal coverage. They will be camouflaged within nature to prevent disturbances to natural habitats.

Challenges we ran into

None of us had used the Arduino ESP32 board before, so figuring out how to wire sensors to the breadboard was a challenge. The hardest thing was definitely connecting the board to WiFi.

Accomplishments that we're proud of

Figuring out how to connect components on the board together, and process digital and analog sensor inputs. We all had more experience with computer software than hardware, so we're super proud of earning how to use both Arduino Uno and Arduino ESP, and building our first project with one!

What we learned

Lots of new computer engineering skills, and how to not short-circuit an Arduino board. Also navigating the Arduino IDE, which was made easier because of previous Python experience.

What's next for EnviroFlame

To further improve accuracy, we plan to integrate an AI-powered sound recognition system capable of distinguishing between natural forest sounds and human activity (e.g., chainsaws and heavy machinery). This will reduce false alarms and enhance the system’s reliability.