Big brother (or should we say) beacons are watching. And that isn’t necessarily a bad thing. The buzz around beacons started in 2013 when Apple introduced iBeacons the first BLE (bluetooth enabled beacon) at WWDC. iBeacon use cases have increasingly gained momentum and notoriety for the ability to integrate the virtual and physical worlds.
One of the iBeacon use cases: When coupons come to you
By 2018, retailers are predicted to install 3.5 million iBeacons. Even in a year beacon adoption has made huge strides. Forty-six percent of retailers introduced a beacon program in 2015, posting 15% growth since 2014, according to beaconstac.
Their application is all but obvious for iBeacon use cases like retail, from targeting customers in the aisle to keeping them more engaged throughout the store.
Achieving the Triple Aim — another of the iBeacon use cases
But healthcare represents another field, primed for the widespread use of beacons. Providers, are highly attuned to any data that can be collected to help improve the Triple Aim, whether by decreasing wait times for patients or cutting costs.
Take this example: if beacons are placed throughout a clinic, an associated app can be used to collect the data-filled messages sent by beacons to track patient wait times, how long typical interactions with patients last and how to more efficiently schedule. The key signifier? Proximity. That’s what the app tracks.
How does developing for beacons differ?
Developing for beacon technology is markedly different compared to other apps. In building a game, developers know users will be actively interacting with it for a certain amount of time. Then, that interaction will cease.
A mobile app carried by doctors or hospital staff, intended to communicate with the beacons providing data on where the carriers are and for how long — represents a more edge use case. The app communicating with the beacons must run accurately in the background when not being actively used. The screen may lock, the phone may sleep but the app runs on.
In one of these iBeacon use cases, the app is tracking signal strength. When a physician gets closer to a beacon in a hallway or patient room, the signal is stronger. The app then tracks that over time. The problem? Noise. The resulting graph is jittery. So, developers must get creative. One way to fix this (among other techniques) is to graph a moving average. That way, a given data point at a given time is influenced by the previous (say) 10 values creating a much smoother result.
Learn more about iBeacon use cases in this app update video created by MobCon founder MentorMate.