4 ms·

It's interesting to consider that Bluetooth cannot be used to estimate distance between two devices in any meaningful way in real-world environments. A recent

It's interesting to consider that Bluetooth cannot be used to estimate distance between two devices in any meaningful way in real-world environments. A recent article [1] confirmed this in interviewing the inventors of Bluetooth. The environmental factors were explored in a recent conference on contact tracing [2] with leading researchers. So in a UK context, what is the plan in dealing with the huge number of false positives captured by this system, which in reality cannot estimate a 2 metre distance? The Australian COVIDSafe app sends all contacts in Bluetooth distance, which obviously includes people in other rooms, and on entirely different levels of a building - because there's no directional information. Separate to the issue of proximity is the issue that this system cannot really work unless it's mandatory, as others have outlined. Does any purpoted health benefits have to be modelled, proved and measured against the issues of shifting Western society to one which requires mandatory install and carry of a mobile phone which records all nearby devices? It gets us closer to a society where political actors will be tempted to provide a rationale which justifies permanent extreme surveillance of citizens. The limited analysis of the particular client implementations appears to miss this wider geopolitical point, and responsible technologists might want to consider these more carefully. In the Australian situation all we are currently told is that if the app registers you as a close contact then it is used for 'usual contact tracing' and that contact tracing involves determining whether you are a 'close contact' and have to self-isolate for 14 days - a huge cost in a re-opened society if it is an unnecessary false positive. It's been quite strange to see leading technologists such as Mike Cannon Brookes of Atlassian and Troy Hunt of HaveIBeenPwned strongly urge Australians to download it as an 'unequivocally safe app' when the most important part - the server-side algorithm to 'guesstimate' proximity - has not been shared by the Australian Government [3]. How can a technologist give the thumbs up to a proximity app when there is no evidence of it reliably estimating proximity in the real-world scenarios it is meant to operate in? [1] https://theintercept.com/2020/05/05/coronavirus-bluetooth-contact-tracing/ https://theintercept.com/2020/05/05/coronavirus-bluetooth-co... [2] https://www.youtube.com/watch?v=KgKbllhgESc&feature=youtu.be&t=2988 https://www.youtube.com/watch?v=KgKbllhgESc&feature=youtu.be... [3] https://www.abc.net.au/news/science/2020-05-06/coronavirus-contact-tracing-app-covid-safe-lockdown-lift/12217146 https://www.abc.net.au/news/science/2020-05-06/coronavirus-c...

g_p 6y ago
Interestingly, and purely anecdotally (so not designed to replace the study itself), I've been experimenting with the RSSI being reported by the NHSx app through the debug menu. At least based on what I've seen so far on my devices (and noting the NHSx model considers device model ID to allow for antenna variations going forwards), there was a ~25 dBm change in signal strength (from -32 to around -57) between phones being sat together, and through a wall yet still close. Clearly this is going to vary depending on building construction, but I suspect the most relevant factor will be determining whether a contact event takes place through a wall or not. The real question is whether or not this can be modelled into the app and it proves reproducible. My understanding is there's no claimed intention to measure the 2m distance, and this is accepted as a known factor, at least for now. I suspect in an indoor setting the initial challenge will be preventing spurious triggers from indoor use (although arguably if people are that close they might live in an apartment block, and they could have been exposed through contact with door handles or lift buttons etc). But once people are outside more and returning to normality, all bets seem to be off - I imagine a lot of false positives. My instinct would be that contact exposure duration will become more of a factor than the RSSI, or that a min/max/median/standard deviation might be captured in addition to a "raw" RSSI, to perhaps get a better idea. If the RSSI never goes "above" -60 (noting it's a negative number) then that's not likely to be a hugely close contact event.
- 7952 6y ago
  I wonder if WiFi connection information could help. Being on different networks would suggest greater social distance.
  - g_p 6y ago
    During current "distance under all circumstances, stay at home", that is likely going to be true (modulo people using multi-AP setups that aren't meshed under one SSID, assuming you use SSID, or who use 2.4 and 5 GHz SSIDs). Going forward though, I imagine that as restrictions loosen, the usefulness of WiFI connections would drop significantly, as people aren't always at home. It would also not really help in the workplace, assuming a large campus WiFi setup, since everyone would probably be joined to the same network anyway. The challenge would be privacy - you'd have to send some kind of information (or unique derivative) of the BSSID/SSID, which would introduce some privacy impact too. At that point, assuming you got access to the hashed SSID/BSSIDs, someone like Google with a street view dataset of AP MAC addresses could "enrich" the anonymised dataset with "ordinary location".

g_p 6y ago

Interestingly, and purely anecdotally (so not designed to replace the study itself), I've been experimenting with the RSSI being reported by the NHSx app through the debug menu. At least based on what I've seen so far on my devices (and noting the NHSx model considers device model ID to allow for antenna variations going forwards), there was a ~25 dBm change in signal strength (from -32 to around -57) between phones being sat together, and through a wall yet still close. Clearly this is going to vary depending on building construction, but I suspect the most relevant factor will be determining whether a contact event takes place through a wall or not. The real question is whether or not this can be modelled into the app and it proves reproducible. My understanding is there's no claimed intention to measure the 2m distance, and this is accepted as a known factor, at least for now. I suspect in an indoor setting the initial challenge will be preventing spurious triggers from indoor use (although arguably if people are that close they might live in an apartment block, and they could have been exposed through contact with door handles or lift buttons etc). But once people are outside more and returning to normality, all bets seem to be off - I imagine a lot of false positives. My instinct would be that contact exposure duration will become more of a factor than the RSSI, or that a min/max/median/standard deviation might be captured in addition to a "raw" RSSI, to perhaps get a better idea. If the RSSI never goes "above" -60 (noting it's a negative number) then that's not likely to be a hugely close contact event.

7952 6y ago
I wonder if WiFi connection information could help. Being on different networks would suggest greater social distance.
- g_p 6y ago
  During current "distance under all circumstances, stay at home", that is likely going to be true (modulo people using multi-AP setups that aren't meshed under one SSID, assuming you use SSID, or who use 2.4 and 5 GHz SSIDs). Going forward though, I imagine that as restrictions loosen, the usefulness of WiFI connections would drop significantly, as people aren't always at home. It would also not really help in the workplace, assuming a large campus WiFi setup, since everyone would probably be joined to the same network anyway. The challenge would be privacy - you'd have to send some kind of information (or unique derivative) of the BSSID/SSID, which would introduce some privacy impact too. At that point, assuming you got access to the hashed SSID/BSSIDs, someone like Google with a street view dataset of AP MAC addresses could "enrich" the anonymised dataset with "ordinary location".