Solutions usually detect and store contact events between Bluetooth devices that has poor interoperability when applied to smartphones. Adoption rates are also low due to privacy concerns and resultant systems depend on subsequent manual contact tracing.
Instead, a new architecture is used that comprises standard beacons carried by users and detectors placed in strategic locations where infection clusters are most likely to originate. [This is similar to the architecture used for IoT sensing using gateways.]
The system helps control disease spread at lower adoption rates. It also provides significantly higher sensitivity and specificity than existing app-based systems.
The Bluetooth SIG also has a new draft standard for exposure notification that can be used to allow wearables to participate in exposure notification systems such that provided by Apple and Google. The idea is that not everyone has a ENS capable smartphone and extension to wearables provides a more complete system.
Herald can’t be used for contact tracing unless you are a government agency because 3rd parties can’t publish such apps on the Apple app store. However, Pivotal Lab’s deep work in this area provides many insights into the use of Bluetooth on smartphones. The library itself also has other uses other than contact tracing:
File sharing between Android and iOS devices, reliably
Local ‘same location’ peer to peer applications, such as instant messaging or gaming apps
Using beacons in high-risk areas, an employee exposure app could accurate record exact exposure to hazardous environments
Also using beacons, know where to deep clean if an employee does fall ill at your large campus
Check in app – Walk around and be let in to secure areas automatically
Rescue app – e.g. for skiing/snowboarding avalanche rescue – find the hidden/non visible person. Could be fire in a large building, or rescue on a tube train
Using scanning for 1-3 seconds with a gap of a few seconds between scanning uses 6-11% battery over 8 hours
Android phones’ speed when reading characteristics is significantly slower than write and acknowledge. Using write instead of read reduces the mean window times from above 8 seconds (minutes for some phones) to 0.5 – 4 seconds, depending on the handset. Use write characteristics wherever possible, and cache data to remove any redundant reads.
Apple iOS has a bug with background Bluetooth advertising where applications on two backgrounded iOS devices are not notified about each other. Two backgrounded iPhones cannot detect one other.
The background timer on Android sometimes gets stuck and might not wake for many minutes.
The way smartphones interpret Bluetooth signals to determine RSSI varies across Bluetooth chipsets. Some such as the iPhone 7 use a log approach while others use an inverse distance-squared scale. This affects accuracy if you subsequently use a common formula to derive distance from RSSI.
The problem with smartphones is that their transmit and receive capabilities vary widely. The received signal strength (RSSI) is inconsistent across types of smartphone and you can’t determine distance reliably. Apple and Google have mitigated this problem by attempting to create a database of calibration values (csv).
The calibration data is useful for Bluetooth developers creating solutions across devices. However, it’s of no use for 3rd party contact tracing as only Government agencies can use the Exposure Notification API and Apple is banning Covid related apps.
Gartner has a recent update to their research of hype cycles that takes into account disruption caused by the Covid pandemic.
Five emerging trends have been identified:
Social Distancing Technologies
Social distancing technologies, related to the COVID-19 pandemic, are taking the fast track through the Hype Cycle and have high impact. Technologies rarely enter the Hype Cycle at the point where social distancing technologies has entered it
Wearable devices provide more reliable performance than smartphone apps because smartphones’ transmit and receive capabilities vary considerably across types of device. Using defined, known wristbands or lanyard devices eliminate the variances.
We have a new beacon, the 1810G in stock that monitors both heart rate and body temperature.
This fitness band can provide real time steps, heart rate or temperature. It also stores the historical data. Data is obtained by connecting programmatically to the device, via Bluetooth GATT, from Android, iOS or other Bluetooth LE device.
Can be set up to provide for social distancing reminders, tested every minute, when two bands of this type come close together (2m).
Being programmable it allows for new usecases such as monitoring groups of people. This might be used, for example, to identify those with an elevated body temperature.
There’s also an iOS and Android app for normal consumer use.
The problem now is that the Google/Apple solution doesn’t provide access to RSSI and instead makes its own determination of close contact. Developers are forced down the path of a closed solution that can’t be improved upon. The new app is worse at determining distance than the original NHS Covid-19 app:
Engineers are still trying to reduce how often the Bluetooth-based tech wrongly flags people as being within 2m (6.6ft) of each other
RSSI is very noisy due to radio multi-path distortion, reflection, shadowing and fading. It also varies due to differences across devices in transmit and receive capabilities.
The paper shows show how good prediction of proximity and risk can be obtained by using RSSI sequences rather than applying thresholds to single values. This correlates with our findings in that our Bluetooth contact tracing solution uses sequences rather than value thresholds. The paper also mentions that the duration of the risk also makes some close contacts more important to classify correctly. Again, we concur in that our solution has the ability to contact trace based on contact duration.
England’s contact tracing is now heading in a better direction and in the direction we previously advocated. They now need to persuade Apple and Google to improve their solution.
The BBC had a piece last night on the use of social distancing beacons at Florence Cathedral in Italy.
The beacons are worn by visitors and vibrate and flash when people get too close to one another. The reporter, Mark Lowen, said that it was the first use of the devices which might be true of that device model but not of social distancing devices in general.
He looks into the variation of Bluetooth received signal strength (RSSI) due to different types of obstruction such as walls and the human body. He explains how RSSI is being used in contact tracing apps and asks whether it’s possible to have false positives when there’s wall between smartphones or false negatives when people are close together but blocked by their bodies.
David used a Raspberry Pi as a Bluetooth emitter and a smartphone as a receiver, situated 1 metre apart and placed various obstacles between them. He found that drywall and stud walls were ineffective at reducing Bluetooth signal strength. Conversely, human bodies drastically reduce Bluetooth signals.
Smart watches might be possible candidates for more accurate contact tracing as they are less obstructed by the body when worn on the wrist
It’s well known that human bodies block Bluetooth. We have an article that explains how this phenomenon can even be used to infer direction.
What David didn’t do was test at different levels of power output. We assume he just used full power which will go through walls. Solutions such as our CATT use lower power predominantly to save battery life but also because there’s no need to transmit further. There’s are also factors at play in a smartphone app such as the variance of signal power across transmitting smartphone, the variance in the ability of different smartphones to receive the signal and the ability (or not) of smartphones to be able to transmit and receive in background when the app isn’t showing/running. These factors make app based contact tracing even more unreliable. Stand alone devices, such as smart watches mentioned by David, work better.
Theatre and performing arts are currently going through a crisis as theatres remain closed but are still experiencing ongoing costs with no income. Performers are juggling new jobs to make ends meet. In the UK alone there’s a projected £74bn drop in revenue for the creative industries and the loss of 400,000 jobs. There’s a growing realisation that the Covid pandemic is going to be with us for a long time. Even when there’s a vaccine, it will take a long time to manufacture, only provide for gradual vaccination and probably require seasonal re-vaccination much like flu.
With this in mind, once theatres are allowed to re-open, they will have to adapt to the new normal. Andrew Lloyd Webber’s pilot performances are leading the way with improvements in hygiene, social distancing, temperature testing, mandatory face masks and special anti-viral sprays.
The Grand Theatre in Blackpool has a new article on the Future of Theatre In A Digital World. It describes new innovations that will improve the customer journey as well as provide for more automated contact-less engagement required for coping with the Covid crisis.
The aim is to integrate all systems to improve the customer experience, raise more online reviews and gain customer feedback. This starts with smart booking of theatre tickets through smartphones, watches and home speakers. Tickets reside on your smartphone with associated useful information such as casting biographies, announcements, behind the scenes photos/videos, reviews, cast introductions, offers and vouchers. This will allow for faster returns and seating updates. eVouchers allow contactless use of entry gates, concession areas, car parking passes, public transport tickets and pre-paid taxis.