Researchers from Michigan State University created a remote forest fire detection and alarm system that is powered by the movement of trees and wind.
The new device generates electrical power by harvesting energy from the sporadic movement of the tree branches from which it hangs. Source: Michigan State University
The new device is called MC-TENG, a multilayered cylindrical triboelectric nanogenerator that creates electrical power by harvesting energy from sporadic tree branch movement. It continuously monitors forests and environmental conditions without maintenance.
The team believes that early and quick response to forest fires makes it easier to extinguish and reduce damage and loss of life. Traditional forest fire detection includes satellite monitoring, ground patrol and watchtowers. These methods have high labor and financial costs with low efficiency. Remote sensor technology is becoming more common but it isn’t incredibly effective because it relies on batteries for power. Using solar tech for power is a challenge because of forest shading or covering of lush foliage. The new device uses TENG tech to convert external mechanical energy into electricity using the triboelectric effect.
A simple version of the new device is made of two cylindrical sleeves of unique material that fit together. The core sleeve is anchored above and the bottom sleeve is free to slide up and down or side to side. It is constrained by an elastic connective band or sleeve. As the sleeves move out of sync, the intermittent loss of contact generates electricity.
MC-TENG is equipped with several hierarchal triboelectric layers and increase electrical output. It stores sporadically generated electrical currents in a carbon nanotube-based micro supercapacitor. This allows it to have rapid charge and discharge times so the device can charge with short and sustained gusts of wind. The device can generate electricity to charge in less than three minutes.
The initial prototype had carbon monoxide and temperature sensors that were intended to reduce the likelihood of a false positive CO2 reading.
A paper on this technology was published in Advanced Functional Materials.
