Trust Range Method of Improving Location Accuracy

A mentioned in our post on location accuracy, two methods of improving accuracy are calibration and trilateration. There’s a recent research paper on iBeacon indoor localization using trusted-ranges model, that explores an alternative ‘trusted-ranges’ method. The method is still based on the RSSI measurements between the beacon and detector. It builds up a trusted-range model to describe how the RSSI varies over time and distance.

The model supplies reliable ranges of received signal strength values from nearest neighbours classifying received signal strength values into various levels of range. It performs better than calibration, especially at shorter ranges, while having a low complexity and hence computationally fast speed.

Enhanced Vehicle GPS Using Beacons

A problem with navigation in vehicles is that location can be lost in radio-shadows such as in tunnels and in tree covered areas. ChoonSung Nam and Dong-Ryeol Shin of Sungkyunkwan University, Suwon, Korea have a new paper on Vehicle location measurement method for radio-shadow area through iBeacon.

Beacons are placed at the side of the road and instead of advertising unique ids in the form of iBeacon or Eddystone, they advertise absolute Global Positioning System location data. Together with the received signal strength (RSSI) this allows the vehicle to better determine the location.

Hybrid Localisation Method

In our previous article iBeacon Microlocation Accuracy, we wrote about ways of using beacon RSSI to determine location. However, what if you were to use and combine beacon RSSI with other ways of locating to create a hybrid method? This is the topic of a new research Unsupervised Indoor Localization Based on Smartphone Sensors, iBeacon and Wi-Fi by Jing Chen Yi Zhang and Wei Xue of Jiangnan University, School of Internet of Thing Engineering, China.

The paper describes UILoc a system combining dead reckoning, iBeacons and Wi-Fi to achieve an average localisation error is about 1.1 m.

The paper also compares the trajectories obtained using different localisation schemes:

Using iBeacons for Motorola TRBONet

Motorola MOTOTRBO range two-way Radios can be used with the Motorola-supplied TRBOnet PLUS (pdf) control room software to show the location of workers with digital radios on maps and plans. The radios contain both GPS and iBeacon detection to allow locating indoors.

There are three places where iBeacons need to be set up in TRBOnet:

In the GPS profile:

Placing beacon on the map:

Are you an established 2-way radio company?
Contact us for advice on which beacons we have supplied for use with TRBONet.

Read the full User Guide
View compatible beacons

iBeacon Microlocation Accuracy

Customers often ask us the accuracy when locating beacons. In order to get the answer, its necessary to understand different ways of locating and the tradeoffs that are needed to get the different levels of accuracy.

There are two types of locating, received signal strength (RSSI) based and angle of arrival direction finding (AoA).

Locating using RSSI

There are two main scenarios. The first is a where the detector, usually a phone or gateway, is at a known location and the beacon moves. The second is where the beacons are fixed and the detector moves. Either way, the detector receives a unique beacon id and the receiving electronic circuitry provides the strength of the received signal.

The value of the RSSI can be used to infer the distance from the detector to the beacon. The main problem with RSSI is that it varies too much, over time, to be used to accurately calculate distance. The direction also isn’t known when there’s only one beacon and one detector. The varying RSSI, even when nothing is moving, is caused by the Bluetooth radio signals that are reflected, deflected by physical obstacles and interfered with by other devices using similar radio frequencies. Physical factors such as the room, the beacon not uniformly emitting across a range of 360 degrees, walls, other items or even people can affect the received signal strength. How the user holds a detecting phone can affect the effectiveness of the antenna which in turn affects the signal strength.

The varying RSSI can be smoothed by averaging or signal processing, such as Kalman filtering, to process multiple RSSI values over time. The direction not being known can be solved by using trilateration where three gateways (or beacons depending on the above mentioned scenario) are used to determine the distance from three directions and hence determine the 2D location.

Trilateration

The aforementioned physical factors that affect RSSI can be reduced by measuring the actual RSSI at specific locations and hence calibrating the system.

The change of RSSI with distance is greater when the beacon is near the detector. At the outer reaches of the beacon signal, the RSSI varies very little with distance and it’s difficult to know whether the variance is due to a change of distance or radio noise. Hence for systems that use signal processing, trilateration and calibration tend to achieve accuracies of about 1.5m within a shorter range confined space and 5m at the longer distances.

However, such systems have problems. The multiple RSSI values needed for averaging or signal processing mean that you either have to wait a while to get a location fix or have the beacons transmit more often (with a shorter period) that flattens their batteries much sooner. Trilateration requires at least three devices per zone so can be costly and require significant time to setup and maintain. Using calibration is like tuning a performance car. It works well until something small changes and it needs re-tuning. If someone adds a room partition, desk or even something as simple as lots of people in the room, the calibration values become invaid. Re-calibration takes human effort and, pertinently, it’s not always easy to know when it needs re-tuning.

An alternative to trilateration is zoning. This involves putting a detector (or beacon depending on the above mentioned scenario) in each room or zone. The system works out the nearest detector or beacon and can work on just one RSSI value to get a fix quickly. The nearest zone is often all that’s required of most implementations. With zoning, if you need more accuracy in a particular zone you add more detectors in the area to get up to the 1.5m accuracy of other methods. This will obviously be impractical if you need 1.5m accuracy everywhere over a large area.

BeaconRTLS™ area zones

Angle of Arrival Locating

An alternative to trilateration and zoning is more expensive Bluetooth hardware and more complex software that makes use of Angle of Arrival (AoA). Locator hardware with multiple antennas uses Bluetooth Direction Finding to find assets to better than 1m accuracy. Location engine software uses the difference in the time of receiving the signals at multiple antennas to calculate the position. Multiple locators can also be used to cover larger areas and/or improve the accuracy using triangulation.

Unlike RSSI systems where any beacons can be used, locators tend to be tied to using the same manufacturers’ beacons. The complex hardware and software has less throughput and supports fewer beacons. The computing hardware needs to be more powerful. Systems need careful, accurate site measurements to achieve good accuracy.

Summary

Choosing a solution just because it is more accurate, rather than needed, will cost significantly more not just in hardware but in software cost, setup effort and maintenance. Work out what accuracy you need and then seek out an appropriate solution.

BeaconRTLS™ v2

A new v2 version of our BeaconRTLS™ has become available. The previous version of our RTLS works great but it needs relatively powerful hardware and was complex to install such that only we could install. While the older version will still be used for our clients that need extremely large throughput, most new customers will now use v2 that works on a greater range of hardware and has a simple setup allowing us to offer it to qualified resellers.

Projects are supplied as a self-install for dedicated, VPS or cloud servers.

More information is available at beaconrtls.net.

New BeaconServer™ Software

For a while now, we have had enquiries from companies interested in our BeaconRTLS but not wanting the whole thing. In some scenarios such as IoT, machine learning and even locating you just want to collect data and not visualise it on maps/plans. Also, our BeaconRTLS™ was found to be overkill for small scale projects that don’t need the extremely high throughput.

Today, we have released BeaconServer™. It’s a ready-made system to collect multi-location beacon advertising data and make it available to other people, systems and apps. It allows you to collect, save and query beacon data without any coding.

BeaconServer™ comes in the form of a self install. Please see the BeaconServer web site  for more information.

Obtaining Distance from RSSI

RSSI is the signal strength at the Bluetooth receiver. The signal type, for example, iBeacon, Eddystone or sensor beacon is irrelevant. The value of the RSSI can be used to infer distance.

The accuracy of the distance measurement depends on many factors such as the type of sending device used, the output power, the capability of the receiving device, obstacles and importantly the distance of the beacon from the receiving device.

The output power isn’t known to the receiver so it’s sometimes added to the advertising data in the form of the ‘measured power’ which is the power at 1m from the sender.

The closer the beacon is to the receiver, the more accurate the derived distance. As our article mentions, projects that get more detailed location derived from RSSI, usually via trilateration and weighted averages, usually achieve accuracies of about 5m within the full range of the beacon or 1.5m within a shorter range confined space.

There’s some Android Java code on GitHub if you want to experiment with extracting distance from RSSI. There’s an equation for iOS on GitHub.

Need more help? Consider a Feasibility Study.

Beacons that flash/vibrate at a given distance.

Beacons to Detect Proximity

Beacons can be used to detect if things or people are in a zone by either putting beacons on the moving things or having the beacons static in a zone.

For the beacons on things/people approach, a gateway or other scanning device looks for beacons in the vicinity and triggers actions. For the static beacons case, an app on peoples’ phone can detect beacon(s) in a zone and trigger actions.

We have some new beacons in stock that now provide a third way of detecting proximity. They use IR and PIR to detect the proximity of any item coming within range. For IR that’s <50cm and for PIR < 5m. These beacons transmit the current state via Bluetooth that can be picked up by an app or gateway.

iBS02IR

iBS02PIR

It’s expected these beacons will be more suitable for IoT and Industrial scenarios.

How Does Using Beacons for Tracking Compare with the Use of RFID?

The main difference between beacons and RFID is the range. RFID only works up to 1m while beacons typically reach 50m to 100m, even more for specialist beacons. It’s also possible to get an indication of distance to the beacon whereas with RFID it’s just ‘seen’ or ‘not seen’.

RFID tags are less expensive than beacons. However, as the range of beacons is much larger, fewer readers are required thus compensating for the extra cost. It’s also possible to totally cover a much larger area.