As the need for companies to understand the location of a person or thing grows, a conversation about potential indoor solutions inevitably starts with Bluetooth beacons. A well-known and simple system for indoor applications such as retail customer engagement or general warehouse localization, Bluetooth beacons are based on a network of Bluetooth Low Energy (BLE) chips set in specific locations that transmit a unique signal. Smartphones in the area can receive these signals, determine the beacon’s location based on signal strength, and use the information from several beacons to estimate the location of the smartphone.

Barriers for Bluetooth beacons

While the simplicity of Bluetooth beacons is appealing for certain applications, in many cases they’re too simplistic. First off, Bluetooth beacons can only be used with smartphones, not tags, and as such are not applicable in applications such as asset or people tracking based on ID badges. Furthermore, while beacons generally provide accuracy within 3-4 meters, they simply aren't precise enough for applications where more than proximity is required. For example, beacons might be able to determine the location of a smartphone in a mall, but not whether a user is in front of the coffee shop or the shoe store. As such, even a basic welcome messages or advertising specials can be delivered incorrectly.

Bluetooth beacons can also be challenging from an operational perspective. Beacons are, of course, mainly battery-operated devices, and one of their key selling points is their untethered nature. They’re easy and relatively cheap to install. However, this requires constant maintenance, making beacons less cost-effective over time. In large deployments such as an airport, shopping mall, or even large retail store, a large number of beacons will be required for reasonable location accuracy, highlighting the complexity of this challenge. Battery performance depends on a number of factors, including settings, environment, power modes, and rules that establish how often beacons transmit a signal. These variables could result in beacons having a battery life of only a few months, resulting in operational expenses that frequently ruin the business case.

Batteries can also impact the real-time nature of location services required by many devices. Bluetooth beacons only transmit periodically because real-time location drains battery life. For example, navigation applications cannot function with more than a 1 to 2 second delay in location updates. Otherwise the app will say “you should have turned right” instead of “turn right.”

Beyond Bluetooth beacons

So, if Bluetooth beacons aren’t enough for emerging applications, what can provide higher, more reliable, real-time accuracy?

The world of IoT is very much about tracking mobile assets. Smartphone-centric beacons are therefore giving way to network-centric systems built from "smart" receiver antennas. In configurations such as these, intelligence is located in the receiver antenna and a centralized software application rather than a smartphone app, allowing the devices being tracked (or located) to be much simpler. This opens up the possibility of using a wide range of low-cost tags with extremely long battery life. For systems that involve tracking hundreds, thousands, or hundreds of thousands of assets, the cost and life expectancy of such tags is crucial.

New approaches to angle estimation

A network-centric solution enables the launch of active, low-cost BLE tags with extremely long battery-life, but also alters the way signals are measured to determine location.

As mentioned, signal strength has been used as the primary mechanism for estimating a device's location in traditional Bluetooth beacon deployments, which fails to consider the impact of the physical environment such as a building’s layout or concrete walls. Therefore, if distance is derived from signal power and the power is affected by fading, the signal strength cannot be an accurate representation of physical distance.

This has resulted in new ways of thinking about how location is calculated within the Bluetooth Special Interest Group (BT SIG), and the organization has begun work on a new standard for BLE angle estimation based on two new approaches:

1. The first uses the signal’s angle of arrival (AoA), which is the exact direction the device is from the receiver antenna arrays. AoA receivers utilize multiple antennas within the same device to better measure the signal, allowing antennas to locate a smartphone or tag to within 10-20 cm. This is about 20 times more accurate than most Bluetooth beacon systems. Location is also calculated much more quickly using AoA than beacons, because variations in signal strength require beacon-based systems to average readings over several seconds to achieve good results. Suddenly, applications that demand accurate real-time location capabilities — such as user navigation and collision avoidance services between machinery and people in a warehouse setting — are possible.
2. The second approach moves location intelligence back to smartphones and mobile devices when it makes sense for the application. These smart devices measure the “direction of departure,” or DoD. This works much like the AoA network-centric approach, and can measure locations of many more devices since the work is done on the device itself.

Next-generation precision location

These innovative new approaches deliver a real-time, accurate location methodology that moves well beyond Bluetooth beacons and into the next generation of indoor location technology. This, in turn, will spawn even more industries that benefit from the ability for precision location.

Fabio Belloni is general manager and co-founder of Quuppa LLC. Belloni has worked for the Nokia Research Center as senior researcher and principal researcher focusing on advanced algorithm development and antenna modeling, positioning technologies, hybrid systems architectures, indoor mapping, and navigation. He received a MS in Telecommunications Engineering from Politecnico di Milano, and a PhD from the Helsinki University of Technology (now part of Aalto University) Department of Electrical and Communications Engineering. Fabio is author and co-author of numerous academic papers, and has several granted patents and pending patent applications.

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