iBeacon, Eddystone, Bluetooth, IoT sensor beacons, apps, platforms
We have a new case study on our consultancy for Royal Museums Greenwich on the Cutty Sark.
Royal Museums Greenwich wanted to locate visitors as part of their forthcoming Cutty Sark Alive Augmented Reality (AR) experience.
Use our consultancy to help prevent problems that should have been known prior to commencement. Otherwise, ‘unknown unknowns’ can lead to project failure or force pivoting in less desirable directions. A small initial study prevents expensive and embarrassing mistakes.
As previously mentioned, we perform signal strength and stability tests across beacons. The data feeds into our consultancy work. Here are some high level observations.
The following graph shows the standard deviation of the RSSI @ 1m, for some of our beacons, measured over a 60 second time period:
Smaller bars are better and represent beacons
whose RSSI varied the least over time.
We found that beacons belonged to one or two groups. Firstly those with very stable RSSI and secondly those with an RSSI that had a standard deviation between about 4 and 6 dBm.
Signal stability is more important when you are using the RSSI to infer distance, either directly from the RSSI itself or indirectly via, for example, the iOS immediate, near and far indicators. RSSI varying without a change of distance might cause more spurious triggering. However, you should keep in mind that environmental factors can often cause variation much larger than the 4 to 6 dBm found in this test. Moving obstacles, for example people, will cause significant variation in RSSI.
Bluetooth LE advertising moves pseudo-randomly between radio channels. The channels use different radio frequencies that, in turn, results in fading of the signal at different distances. We experienced and mitigated similar behaviour in our LocationEngine™. Different radio frequencies experience different constructive and destructive interference at different physical locations. Beacons that move more between channels can cause more rapidly varying received signal strength (RSSI).
There’s new research from Universities in Piraeus, Greece and Berlin, Germany, together with U-Blox AG in Switzerland who create Bluetooth Angle of Arrival prototyping boards on Deep Learning-Based Indoor Localization Using Multi-View BLE Signal.
Processing of Bluetooth Angle of Arrival usually requires radiogoniometry spectral analysis of radio in-phase and quadrature-phase (IQ) signals in order to then determine location by triangulation. Instead, this paper proposes machine learning of IQ and signal strength (RSSI) data from multiple anchor points to determine location. AoA processing also uses distributed processing across the anchors to improve performance.
The developed machine learning models were found to be robust against modifications of room furniture configurations and materials and it’s therefore expected that they have high re-usability (machine learning generalisation) potential. The system achieved a localization accuracy of 70cm.
The Future of Personal Health has an article on Innovate Oncology Operations With RTLS Patient Flow Technology.
The article explains how 75% of cancer program management cited workflow inefficiencies as the most concerning bottleneck to patient care delivery. There are problems with patient flow that stresses care teams and ultimately jeopardises the safety of patients.
RTLS can be used to know and optimise how long patients have been waiting, their stage of care, who has seen them and who they need to see next. This reduces both patient and staff frustration. The article claims it is possible to increase increase capacity by 10% without adding physical space.
While mentioned in an oncology setting, this is just as applicable to other health settings where patients are waiting.
It’s easy to buy into an idea and commit significant resources only to find very late on that a project is overly difficult or impossible to implement. We see too many companies only come to us after they have gone a long way down a particular road only to discover they made a big mistake early on. It might be, for example, they have heavily committed to the wrong beacon, wrong platform or have assumed something on one of the mobile platforms. They didn’t do their research. Often we can help them get on the right track but sometimes not.
We always recommend organisations research upfront. Test risky areas. Create a low cost proof of concept exercising risky areas. A proof of concept is the implementation of a small subset of the whole system to prove implementing the whole thing is possible. Good candidates for functionality for proof of concepts are specific usecases, scenarios or user stories. Choose specific usecases to exercise what you think might be the most difficult or unknown parts of the system.
Proof of concepts provide a feel for the development effort that will be required to develop the complete system thus giving an indication of the project’s cost and the financial viability of the project.
It’s also possible to create proof of concepts that include business goals. Think ‘proof of value’ rather than ‘proof of concept’. Proving a project has value to stakeholders can help unlock realistic funding for development of the complete project.
There’s new research from College of Information Engineering, Shanghai Maritime University, China on BSSH: Bluetooth Indoor Positioning Strategy for Ship Cabin Based on Hierarchical Area.
The locating and monitoring of ship crew is an important part of ship safety when it comes to adherence to duty regulations. The paper shows how Bluetooth works within the complex electromagnetic and spatial structure of a ship.
The research proposes a BSSH positioning system using fingerprinting that divides the ship up into hierarchical areas.
The BSSH system eliminates the affect of distant beacons on the location results thus reducing the computational effort and improving accuracy.
The system demonstrated better results than a traditional KNN positioning algorithm. It had higher positioning accuracy, better stability and an accuracy rate of more than 80%.
The Bluetooth SIG, who manage the Bluetooth specifications, have a new market update that provides information on the Bluetooth ecosystem. The most interesting and pertinent segment for our customers is location services:
Location service device shipments are expected to have 25% compound annual growth over the next five years according to ABI Research:
Commercial RTLS are being driven by recent inventory and logistic challenges:
‘Retail and Services’ at 62% is surprising as we would have expected ‘Warehouse and Logistics’ to be the larger segment.
Marwell Zoo has a new app, with support for beacons, that allows visitors to plan their day, locate animals and stay informed about the zoo’s latest news.
The app provides an interactive map and contextual messages to the 140-acre park’s 500,000 visitors a year. The app uses the attractions.io platform who have an article on how to add value to a visitors’ experiences through the use of contextual messages and having a better understanding of guests.
There’s new research from China on Regional Double-Layer, High-Precision Indoor Positioning System Based on iBeacon Network.
The project used extended Gaussian filtering to delete and filter significant abnormal data values caused by multipath radio noise indoors. A deep neural network was also used to fingerprint data.
The system resulted in a maximum error positional error of only 1.02m.
The Bluetooth SIG, the organisation that produces Bluetooth standards, has a recent post The Myths & Facts About Bluetooth Technology as a Positioning Radio. It talks about the location services in general and how they have evolved over time. It explains how Bluetooth helps solve key enterprise pain points to save tens to hundreds of billions of dollars globally through enhanced operational efficiencies, increased worker safety, and loss prevention.
In manufacturing facilities, billions of dollars are lost through unplanned downtime thanks to being unable to locate assets, tools, and equipment. In warehouses, RTLS can help automate the tracking of assets, such as pallets, which is becoming more essential with the ever-increasing size, complexity, and amount of assets stored
Despite the gains thus far, this only represents as small proportion of the opportunity because only a very small percentage of the potential addressable market in the enterprise is using RTLS.
The article continues with a summary of the myths we covered in a previous post.
ABI Research expects that will be a 2.5x increase in total Bluetooth RTLS deployments over the next five years, with the fastest growing segments being healthcare, warehouse and logistics, manufacturing and smart building.