From a hardware perspective it covers, RFID, UWB, Bluetooth, ZigBee, IR, WiFi, ultrasonic and hybrid systems. There’s a useful comparison table of the various technologies:
The paper describes methods of using radio signals to determine position such as RSSI ranging, trilateration, angle of arrival (AOA), round trip time of flight (RTOF), phase of arrival (POA) and time of arrival (TOA).
It also describes methods such as fingerprint localization.
The paper starts with an overview of indoor positioning techniques including trilateration, fingerprinting, dead reckoning and AI machine learning. It also provides a synposis of different technologies such as RFID, WiFi and Bluetooth.
The paper explains that while fingerprinting is widely used, it faces limitations when used in dynamically changing environments. Fingerprinting requires ongoing maintenance and updating of the reference fingerprinting map that’s manually intensive and time-consuming. Fingerprinting also requires a large number of beacon reference points to perform accurate locating.
The researchers looked into positioning within a two floor (grocery) retail store. Retail stores are of of the more challenging environments as there are shoppers moving about that can affect indoor localisation
Several indoor positioning techniques were considered including fingerprinting and trilateration. The researchers implemented fingerprinting and compared it to seven established classifiers. The random forest algorithm worked the best and inspired the authors to build an ensemble classification filter with lower absolute mean and root mean squared errors.
The paper provides a great introduction to positioning using beacon received signal strength (RSSI). It describes trilateration and fingerprinting methods for determining location.
Key insights are:
High temperature, strong wind and blocking by pedestrians degraded the signal strength.
Pedestrians traffic blocking the line of sight caused the most signal attenuation and variation.
High air temperature caused significant increase of packet loss that affected the RSSI.
Strong wind reduced the signal strength but didn’t affect the stability of signals.
Trees and nearby vehicle traffic didn’t have any negative effects on signals.
Lower error rates were observed when beacons were deployed on the ceiling as opposed to on the wall.
Positioning accuracy improved with ceiling placement due to the reduction of obstructions.
If ceilings are too high or ceiling deployment is impracticable wall mounted iBeacons should be placed as high as possible.
For fingerprinting, sample at 2m grid intervals for 6s to 10s at each point. Avoid having too many beacons as this won’t improve the positioning accuracy. A transmission interval of 100ms is detrimental to the positioning accuracy. 417ms is better.
For fingerprinting, positioning accuracy varies greatly according to the what is in the room.
The paper mentions that beacon UUID, major and minor are used to uniquely identify beacons. While this is true in the context of detecting using apps, most locating systems use gateways. Gateways use the Bluetooth MAC address to uniquely identify beacons and the advertising type, iBeacon, Eddystone or other, is irrelevant. Using gateways as receivers is also a solution to the problem of variability in receiving capability across smartphones.
The study only considered one beacon type and two receiving smartphones. At Beaconzone, we recommend experimenting with the actual hardware in the actual environment as, being wireless radio, optimum settings and can vary considerably.
A common problem in factories is manual searching for stock for input to manufacturing. Stock is usually stored in boxes or pallets and can be in one of many rooms, warehouses or might already be somewhere on the factory floor. A large amount of stock arrives and leaves every day leading to logistical challenges keeping up with the whereabouts of goods. Timely delivery of components or sub-assemblies is critical to ensure smooth flowing of production and making best use of factory resources.
Manual paper-based processes are extremely inefficient and prone to human error. Old fashioned RFID or barcodes are also susceptible to error because data is only as up to date as the last scan and a recent scan might not have occurred.
We offer multiple solutions for tracking stock and can adapt them to your exact needs, for example integrating with your existing systems. Once you have a tracking system in place you can use it for extra purposes such as locating jobs/work orders, monitoring machine/people capacity and providing for location based instruction/tasks. Sensing open/closed, on/off and quantities such as temperature and vibration enables diagnostics, monitoring and prognostics.
FIND is an open source indoor locating system for home automation, indoor local positioning and passive tracking. It uses your smartphone or laptop to pinpoint your position in your home or office with a location precision of below 10 sq ft.
FIND uses scanning of WiFi and Bluetooth:
FIND compiles these different signals can be compiled into a fingerprint which can be used to uniquely classify the current location of that device
The main insight is that along with the expected difference in the RSSI attenuation there is a considerable difference in the BLE signal variation at all transmission power levels with respect to distance. The variation increases and the localisation accuracy decreases from high to low transmission power levels:
Another observation is that outliers in the data tend to affect the localisation accuracy. Applying filters to the data, they achieved a location accuracy of 2.2 meters with a precision of 95%.
One comment we have is that the researchers didn’t try different beacons. As we mentioned in 2016, the RSSI stability also varies across different beacon models.
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.
There’s a video at YouTube on the installation of Raspberry Pi based beacon detectors in a cow shed to detect the position of cows.
Beacon on a cow
Beacons can, in fact, do a lot more than just determine location. For example, it’s possible to track extra things such as temperature, humidity and unexpected movement. In the cow shed case, hall effect beacon sensors can be put on gates to alert when gates are open/closed when they shouldn’t be. The location data can be used to provide geofencing to alert when things, people or animals enter or leave specific areas.
They evaluated RSSI and indoor positioning trilateration algorithms in order to determine location accuracy. After lots of experimentation and mathematics, they calculated the average error to be 1.09m for 1–9m and 1.75m for 1-20m and after trilateration an average error 2.45m was achieved.
The conclusions give some hints how better results might be achieved. For example, correlating the RSSI with accelerometer, gyroscope and other sensors. Other strategies might be to excluding areas where an object
cannot move, or filtering out situations where objects move but accelerometer measurements don’t match.
IndoorAtlas has a new free, openly accessible 2016 Indoor Positioning Research Report that has some insights regarding indoor positioning and beacons. However, while reading the report you should know IndoorAtlas is trying to position their geomagnetic indoor positioning solution.
The report says the main concerns for implementing beacon indoor positioning systems are scalability (40%) and expense (38%).