Professor Dinesh Bharadia of the Jacobs School of Engineering University of California San Diego runs their Wireless Communication Sensing and Networking Group. One major focus of the lab is to investigate harvesting energy to enable sensors to communicate in a battery-free manner. The following is an interview with Professor Bharadia.
Tech Briefs: Can you discuss some of the challenges you are working on.
Dinesh Bharadia: Take for example continuous glucose monitoring (CGM). People who have diabetes use micro-needle based continuous glucose monitoring devices, where you attach a patch to your body. The patches contain battery packs and must be replaced every two weeks. What if instead, these patches can operate without batteries, by harvesting power from their surroundings.
The challenge is that the signals from the sensors are very weak; often they are electrical changes in nanovolts or nanoamperes, sometimes even femtovolts. So, you take this tiny signal, convert it into digital bits, and then modulate these bits into BLE or Wi-Fi transmissions. Transforming the sensor output from very a small electrical signal to a signal with enough power so that it can be transmitted to a receiver is the reason for much of the energy required on these devices.
Our innovation was to design a new type of tag that uses RF backscatter connectivity. We investigated whether we could use a smartphone to power a continuous glucose monitor, or an IoT device, or a custom tag, by using some of the very large signals transmitted by our phones to base station towers. An especially interesting feature of this technology is that in addition to harvesting energy from the ambient signals, it can also use them to communicate a sensor’s output.
Typically, for example, a phone transmits close to one watt when it’s communicating with cellular towers. That’s as much power as an RFID reader typically emits. However, a problem with using those signals is that an RFID reader typically sends a constant tone, while a smartphone sends information-filled cellular signals. In our work, we demonstrated how despite that, the cellular signals could be used to harvest energy.
Once we harvest enough energy to power the tag from the cellular signals, we use Wi-Fi and Bluetooth in an innovative way to connect the tag with the phone. Bluetooth signals have a protocol that typically uses some form of frequency shift communication. One frequency means bit-one and if the signal shifts to another nearby frequency, that means bit-zero. So, we take this Bluetooth Low Energy signal and send bits of only ones, which creates a constant tone, pretty much like an RFID reader.
Now that you have a constant tone from the phone to your continuous glucose monitor sensor, you can take that tone and change it into a Wi-Fi signal, which carries the data from the sensor and is directly readable by your phone.
The tone created by your phone is at a relatively large voltage. You can easily modulate this voltage with your data by using typical Wi-Fi digital circuits, which are extremely low-power and energy-efficient. You can then take this data-modulated large voltage and reflect it back. This solves the challenge of increasing the energy of the sensor signal — increasing the amplitude associated with the digital signal.
In summary, our tag can take that large tone and reflect it back by adding its data onto it so that it looks like a Wi-Fi signal. You don’t have to change any chip on the phone to receive the signal, so any standard Wi-Fi receiver can receive the signal reflected by our tag. That allows us to leverage the large ecosystem of Wi-Fi and Bluetooth devices — our smart watches, our phones, even smart glasses — which all have Wi-Fi and Bluetooth connectivity.
Tech Briefs: You said you digitize the signals; doesn’t that require electronics?
Bharadia: Yes, typically a sensor on the tag produces an electrical change — let’s say an analog signal. We then use a small logic circuit to digitize the analog signal. It’s easy to do if the sensor outputs a reasonable signal. However, once you have digitized the information from the sensor, now comes the hard part, the communication.
First you harvest enough energy to operate the sensor plus the digitizing logic plus the reflecting logic on the tag. You have a module that harvests the energy and accumulates it on a capacitor. Once there is enough energy, it activates the sensing module, and the communication module as needed.
So, the sequence is: We use the Bluetooth to create a single tone; digital logic on the tag takes the digital information from the sensor and shapes it so that it looks like a Wi-Fi signal; we then reflect the incoming Bluetooth signal, which now has been digitized to mimic Wi-Fi, back to the phone, which can decode it like standard Wi-Fi.
Tech Briefs: What does it mean to convert the tone into a Wi-Fi signal?
Bharadia: When you have the Bluetooth tone that comes from your phone to your tag, your tag’s antenna receives it, and you can decide selectively when to reflect and when not to reflect it. That allows you to create a modulated signal — it creates on-off behavior at the phone’s receive side.
But Wi-Fi doesn’t work with just an on-off modulation. It uses complex modulations like BPSK that encode information as plus or minus one instead of ones and zeros. Plus one typically represents a zero-bit and minus one represents a one-bit, for example. So, we designed our tag to reflect the signal by multiplying it either with plus one or minus one. Our tag can also support more complex modulations, such as QPSK, which require multiplying by complex numbers.
Tech Briefs: What are you currently working on?
Bharadia: We realized that lots of sensors create electrical signals that can vary from very weak to reasonable strength. Most sensors rely on changes in the three fundamental passive elements: resistance, capacitance, and inductance, and sometimes direct changes in voltage or current. We then have a reading logic based on those changes.
We asked ourselves whether we even need digitizing logic or whether we could directly communicate the analog signal itself. So, we came up with an innovation where we took the analog sensor output and used it to modulate the channel of the incoming RF signals. We decided to see if this concept could work for RFID, because that would be the simplest way to start.
The RFID reader sends out a signal to the tag’s antenna to interrogate the tag, then the tag’s RFID chip adds its digital identity, the signal gets modified by the sensor’s analog output and is reflected back to the reader’s receiver.
The returning wave at the receiver now has contains two sorts of data: the sensor’s analog information and the RFID’s digital identity. However there have been additional changes in the wave that have nothing to do with either of these two.
The electromagnetic wave transmitted by the RFID reader travels through a specific medium and the reflected wave travels back through that same medium. As it travels, it undergoes transformations that affect both the magnitude and phase components of the wave. The measure of that transformation is called the channel. Since these transformations affect the signal but are independent of it, we had to devise a method to separate the transmission effects from the actual data on the tag.
Our solution was to connect the sensor tag’s antenna to two separate RFID chips. One chip has the sensor in its path and the other does not. Now I can compare the channels for these two RFID chips, because they have different digital identities. When I compare them, I would know exactly what changes were introduced by the sensor. At the RFID reader, we decode the sensor data by measuring the change in the channel, thus requiring no electronics other than the RFID chip.
What’s great about this technology is that the analog output of the sensor, be it large or small, can be applied to the channel. It just changes the channel’s amplitude and phase. The channel is extremely sensitive, the change is at extremely low power, is easily readable, and provides a unified way of reading all sensors.
We applied this technique to a force-sensing “sticker” that is wireless, can run without batteries, and fits in tight spaces, which is a significant application because a force sensor is often very power-hungry.
Future Possibilities
I went on to talk to Dr. Bharadia about his thoughts for future applications. Force sensors, he said, can be useful in a wide variety of applications. For example, to measure the force on a robot’s gripper when it encounters an object; for logistics in tracking objects, people could use a smart phone instead of a bulky RFID reader; or to be placed at the tip of a device a surgeon is inserting into your body to make sure it isn’t causing damage. More generally, enabling highly sensitive, robust sensors with existing popular information-based wireless technology (WiFi/BLE based), while being batteryless and low-cost.
Batteryless sensors based upon this technology produce far less electronic waste because they last indefinitely, and once they are sent to landfills, they have hardly any non-degradable electronics. And they could be produced for a cost of about a dollar apiece.
This article was written by Ed Brown, editor of Sensor Technology. For more information, contact Professor Dinesh Bharadia at
