A technology developed by the University of Washington, US, promises to reduce the energy costs of connected devices via Wi-Fi networks by eliminating the analog transmitter. The technique was named “passive Wi-Fi” and promises a consumption 10,000 times smaller than the traditional and a thousand times less than other low-energy methods, such as Bluetooth Low Energy.
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The project is still in the testing phase and there is no forecast of when will hit the market. The measure is ideal for the Internet of Things, because it makes users spend less electricity to keep your smart houses in operation.
The Wi-Fi signal transmission is made up of two components, one digital and one analog. The first consistently evolved over time, becoming more efficient. The second is still consuming a lot of energy, which ends up draining the battery of devices faster.
The solution found by the University of Washington was to separate the two sides. In this way, devices that use passive Wi-Fi only have digital connection, which makes them more economical. Because the connection is dependent on the analog component output was to create a second device with the complete transmitter.
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The device acts as an intermediary, communicating with others devices connected to the network and also to those with Wi-Fi liabilities. The arrangement allows the transmission of packets consume little, which is done through reflection and absorption signal by using a digital switch.
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“All the heavy activity and consuming energy is made by this device. The passive devices only reflect the package, which is an efficient way to communicate, “explains electrical engineer Vamsi Talla, co-author of the project.
The average range achieved by the survey was about 30 meters away. The downside of the technology is that it achieves lower speeds to traditional Wi-Fi, with a maximum of 11 mbps, but still, the rate is eleven times higher than Bluetooth.
project is compatible with all Wi-Fi standards currently accepted. Since it is still in the experimental stage, there is no predicting when it will be implemented in other products and get to market.
Via Washington University and The Next Web
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