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Using AI to manage IoT sensor power

Sensor power loss is the scourge of IoT.

Deploying millions of sensors is pretty much a useless endeavor if the devices continually run out of power. IoT sensors can’t collect or transmit data without power.

That’s one reason researchers are exploring ambient energy harvesting. Numerous projects have shown that small amounts of power can be generated by converting ambient energy in the environment – from stray magnetic fields, humidity, waste heat, and even unwanted wireless radio noise, for example – into usable electrical energy to power the IoT.

But while ambient energy can be harvested, it’s not a reliable replacement for battery power.

Scientists from University of Pittsburgh are proposing a system that applies artificial intelligence to cut back on IoT sensors’ energy consumption and mitigate battery longevity issues. The project uses piggyback sensors, which are powered by energy harvested from the environment, to trigger the main sensors. The piggyback sensors will run unattended and are trained, using AI algorithms, to signal the main devices to turn on only when specific event conditions are met.

“One of the main challenges of running AI algorithms with energy harvested from the environment is that the energy from the environment is intermittent,” said Jingtong Hu, lead researcher on the study and associate professor of electrical and computer engineering at the university’s Swanson School of Engineering, in an article on the university’s website. “… if the sensor loses power, you lose the data, so we want to help AI algorithms reach an accurate decision, even with intermittent power.”

Copyright © 2020 IDG Communications, Inc.

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