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Scene Two: Guardian Angels



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Scene Two: Guardian Angels





11:46am, 6 July 2020 – It’s a slow day for Johannes. His patients are not doing much, and the data from their activity trackers confirms this. He walks out of his office and into the kitchen to make his second double-espresso for the day. His smartwatch vibrates – his diet app is being worrisome again. The Babel kitchen sensed his arrival and his medical monitoring program is now displayed on the smart fridge’s screen. He finishes his espresso and walks into the lounge room. Again, his work program follows him to the screen of the main TV set. He sits on the couch. “ME-ternity, listen!” he exclaims. The Babel home’s ME-ternity home hub springs to life – within half a second, it captures the sound bite, sends it to the ME-ternity server in Estonia, authenticates his voice, and confirms the command. “TV, split screen, channels one and six”, he commands. ME-ternity splits the TV screen between his work program and a shopping channel. He sees George Clooney holding up a cup of his favourite brand of espresso. This is followed by an advertisement for longer lasting sex. “ME-ternity - TV, mute!” He turns his attention to his tablet.
The ‘Me-Money; Me-Problems’ personal finance app displays the Babel expenses summary. The power usage is unusually high – probably the solar panels on Evey’s window shades playing up. Something catches his eye – his insurance premiums seem to fluctuate monthly, although still payable annually. He zooms into the bar graph and notices that each hour showed a different rate, and seems to change frequently. His health insurance has gone up, but Olivia’s has gone down. Home insurance dropped by 10% last month and has stayed down. These fluctuations seem to begin around Christmas (when the family received activity tracking smartwatches) and when Johannes installed the ‘Safe-me First’ home security system.
“ME-ternity, Jon to RisQi Insurance, teleph-” – he is cut off by another notification, this time via his medical monitoring program on the TV screen. One of his patients has triggered the distress button on his wearable device. He rushes back to his desk. His program follows him onto his laptop screen. He accesses the patient’s health records via the NSW Health E-Health database – Wayne NACCA, 80% vision impairment... Assistance ‘Field Medic’ GPS bracelet, guide-dog (“Harrison”).
Johannes tracks Wayne’s heart rate in real-time – it is high, but not indicative of a disorder. No other biometric signs of emergency. The ‘Field Medic’ GPS shows that Harrison’s GPS dog collar is around the corner. Harrison must have run off. “ME-ternity, Jon to Sutherland Shire Council, Medical Assistance, Non-Emergency, telephone…”, he yells, eyes glued to the screen. ME-ternity connects him to an operator. Johannes briefs the operator, who dispatches a mobile medical unit to Wayne’s location. He is reunited with Harrison. Heart rate stabilises. Johannes makes a note on Wayne’s E-Health record. He steps away from his office. Another espresso. Another vibration. Another health insurance fluctuation.



The Connected Human: Healthcare and Wearables


In the above scenario, we see a few different sides to IoT, healthcare and wearables. Wearables in the medical industry allowed Johannes to monitor his patient remotely, in real-time and with very accurate physiological data. He was able to remedy Wayne’s (non) emergency remotely. On the flip side, Wayne was tracked, raising privacy and consent issues. Astute readers will also recall Johannes’ caffeine consumption and Olivia’s recent health kick – are their wearables sharing this information with their health insurance provider?

Figure 17 – Wearables in healthcare.
Source: Boston Technology
As part of this ‘healthcare revolution’, users may be required to share some of their most intimate personal information with strangers. This sharing is dictated by the privacy policy of the IoT service provider, which users need to click ‘agree’ to. This can include data that devices collect, as well as any inferences that can be drawn from that data. Some of these inferences are very personal (and the quality of inference highly variable), including drug consumption, whereabouts in real-time, biological disorders, stress levels, fitness levels and even sexual performance. This section touches on all of these implications. Types of Wearbles in Healthcare

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