Setting the Internet of Things Free -- of Batteries

Yes, please.

Setting the Internet of Things Free -- of Batteries

By R. Colin Johnson, Commissioned by CACM Staff, November 8, 2022

EnOcean’s wall-mounted pushbuttons harvest the energy from the finger pushing them to generate an RF signal that turns on lights, overhead fans, or any other device that would ordinarily require connection to electrical wiring.

Energy harvesting reaps energy that would otherwise go to waste—from sources ranging from solar rays to vibrations to ambient gradations in heat, ocean waves/tides, wind, and even the metabolisms of living organisms. These sources can be tuned to produce electricity that is safe, sustainable, and deployable in conditions not suited to the use of batteries.

Incorporating such energy harvesting into the Internet of Things (IoT) extends its reach to nearly any place on the globe—not just those that can access power lines or rechargeable batteries.

"Energy harvesting has the potential to expand the capabilities of the Internet of Things to heights previously unattainable without the technology," said ABI Research analyst Taylor Jensen, who is just putting the finishing touches on a study on energy harvesting for IoT applications.

Applications for IoT devices are expanding dramatically, targeting industries including automotive, aerospace, military, transportation, consumer electronics, industrial, buildings, home appliances, environmental monitoring, home automation, healthcare, and other increasingly "green" sectors. Ubiquitous communication standards such as Bluetooth, Wi-Fi, and cellular technologies have opened the door to IoT devices that monitor and manage widespread networks of sensors and actuators. With the addition of energy harvesting to power off-grid IoT devices, there are few corners of the Earth left that are out of reach.

Energy harvesting has matured through the use of a variety of environmental sources, including:

• Light (via photovoltaic cells).

• Wind (which drives turbines that generate electricity).

• Vibration (resonators drive transducers to generate electricity).

• Thermal (temperature differences converted to electrical energy by dipole oscillators)

• Radio Waves (electricity harvested from oscillating electromagnetic fields with antennas and diodes).

Today, IoT devices often depend on just one of the energy harvesting methods above; for example, solar cells work fine on sunny days, but not so well on cloudy days or at night. To compensate, the solar cells charge a battery during the day, then switch to battery back-up systems to provide power at night.

Yet batteries are not the long-term power solution for the IoT, according to Pat Pannuto, an assistant professor in the Department of Computer Science and Engineering at the University of California, San Diego.

"Every device with a battery is a device with a lifetime, and a short one at that," said Pannuto. "Today, we already average 10 or more connected devices per person in many parts of the world. Now imagine the transition from today's Internet of Things to tomorrow's Internet of Everything, a future with as many as a trillion connected devices; that is, hundreds of devices per person on the planet. We cannot become a world of battery-tenders; self-sufficient devices are fundamental to scale."

One answer available today has been demonstrated by Ji Li, a senior data and applied science manager at Microsoft. Li says 24/7/365 battery-free always-on IoT devices merely need to include multiple energy harvesters. Rather than using a single-source harvester that stores energy in a battery for times of darkness, no wind, etc., Li has demonstrated a method that combines several energy sources that together can provide the power requirements of an IoT device all day, every day, without the need for batteries.

According to Li, battery-free IoT devices require the use of machine learning (ML) to intelligently switch between multiple energy sources customized to provide the most efficient and most stable power supply for a particular application. For instance, managing the switch among thermal, kinetic, and photovoltaic energy sources with algorithms that compensate for the intermittent nature of each individual energy source allows ML to inform task-scheduler software that automatically switches among power sources.

"Batteries are the limiting factor in the lifetime of today's electronic devices. To extend service lifetime, devices must be able to obtain energy from their deployment context," said Pannuto. "That means scavenging energy from the nearby environment. As we push into more diverse environments, this also means scavenging from new and novel sources. In the future, intelligent instrumented systems will run on energy found wherever they are deployed. For instance, sensors embedded in concrete can harvest from the corrosion of the rebar. Sensors buried underground can harvest from electrogenic bacteria in the soil."  ... '