The Digital Edge

Enabling an infrastructure with serious location capabilities isn't cheap at roughly $1000 per access point (MSRP), so the use cases need to be substantial. HALO is a premium engagement and location offering that will not be adopted by the masses, however those who can leverage it effectively stand to offer tremendous value to their customers, patients, stakeholders, etc. Hospital environments to be the single most valuable environment for HALO, especially after RTLS tags are added to the mix. This environment is highly mobile and ripe for disruptive location technologies that can automate work flow and enable meaningful interactions and engagement. Hospitals today leverage multiple location systems that facilitate portions of work flow, however very infrequently are they integrated together well enough to gain additional actionable insights. There are a number of point products addressing nurse rounding, locating wheelchairs and beds, theft prevention (babies and assets), etc. Some of the "bleeding edge" use cases include playing a loved one's voice over IP speakers to coax an elderly patient back into bed or having a display cheer up a child who is battling cancer when they near the screen. In theory, this HALO module is enabling a world in which we know where every associated wireless device is down to a matter of feet, without necessitating RTLS tags. This opens the data floodgates for actionable intelligence at unprecedented levels.

One of the major limitations to the Low-Energy Bluetooth solutions is that they are almost exactly backwards from RTLS solutions in that mobile assets are required to interact with fixed (usually) assets. This typically means an app on a Smartphone (carried by a mobile user) is the typical mode of engagement and this is an active process. A few use cases of cropped up recently in which a BLE-beacon is strapped to a patient to monitor them as they move through an environment. To accomplish this the interaction points along the way require a tablet mounted to the wall to pick up on the patient's tag and initiate the engagement work flow. This reverse BLE-solution is somewhat innovative and solves a specific problem, however we need a world in which mobile assets are interacting with other assets on demand and relative proximity to each other should be irrelevant as long as I have access to the back end data. I believe that HALO is positioned to do exactly this as it evolves and in doing so will allow the use of Wi-Fi based geofencing capabilities indoor, reducing or possibly even eliminating the need for traditional fixed beacons. At the very least this will provide us new deployment options and can be combined with a BLE infrastructure to offer infinite interaction capabilities.

The items above all point towards enabling the Internet of Things (IoT) and allowing real time interactions between devices to the betterment of the healthcare environment. An example of this could be the lifecycle of an infusion pump. These devices follow a predictable cycle in which they move from being clean through being attached to a patient and ultimately wind up having to be cleaned again before being released back to the care areas. In this scenario, alarms could be triggered by a device that has not been put in a maintenance mode and is following an unexpected path, possibly avoiding a dirty pump being brought to a patient, etc.

Designed to be cross-platform, Google's Eddystone supports the Nearby API and is available on GitHub under Apache 2.0 license.

Anyone interested in creating awareness of who they are, what they are doing, or empowering a device to do the same in a given location now has the ability to advertise to passersby. This has many implications from brand awareness to interacting with a specific device. Most importantly this can happen on the smallest of scales, increasing the chance for adoption and interaction since there is no dependency on a mobile app. Check out the Physical Web Cookbook for many newer ideas.

Google Eddystone supports multiple frame types enabling users to interact in a variety of ways. These frames are designated in the Service Data field associated with the Service UUID by using the high order four bits of the first octet. Github provides all this information in much more depth.

The Proximity Beacon API is a new interface enabling users to manage their beacons via the cloud and use a REST interface. This enables monitoring of the telemetry data previously mentioned as well as reconfiguration of the beacons.

Geolocation is defined as the process of physically locating or the actual location of an object on Earth. In defining contextually aware networks, it is no longer enough to know whether someone is on-net or off-net. Where they are "off network" is important as well and can offer additional insights and opportunities for engagement.

Geolocation primarily leverages a Smartphone's built in Global Positioning System (GPS) and uses the installed application and either Wi-Fi or cellular backhaul to report current location for users that have opted in to this offering. This enables the operator of a contextually aware application to engage with the customer outside the "four walls" of the organization. At this macro scale, location is typically measured in meters however results vary wildly depending on the type of location being deployed.

Assisted GPS uses a secondary system to increase the accuracy of the GPS satellite reporting. In the case of Smartphones the cellular network is responsible for assisting. This enables the phone to download information about the GPS satellites in order to quickly determine its position and provide updates at an interval frequent enough to be useful for engagement purposes. The newest smartphones are able to use both the US Department of Defense GPS system and the Russian GLONASS system to further increase accuracy. These solutions are limited in scope from an engagement perspective as they require clear visibility to the sky, so they tend to not function in large downtown areas. Recent testing has shown that A-GPS offers approximately an 8 meter accuracy range, which is typically accurate enough for any of the geolocation use cases. IT is important to note that accuracy in dense urban centers may still be challenged at times.

One of the most important aspects of constructing a contextually aware network is the concept of geofencing. A geofence is a virtual construct that overlays a logical "fence" on the world map and allows decisions to be made as a device crosses the geofence or is inside or outside that geofence. A virtually unlimited number of geofences can be constructed, but it is important to know when engaging with the customer is meaningful and wanted. Since the geofence is virtual, no equipment is required at any location defined by a geofence.

Let's assume for a moment that you are headed out on a gambling vacation to "The Vegas Hotel" on the south end of the Las Vegas strip and have installed their mobile concierge app. Upon landing at McCarran airport and taking your phone out of airplane mode, it is able to recognize its GPS coordinates via A-GPS and the concierge app wakes up. Once awake, the app prompts you to meet your hotel shuttle outside baggage claim #2. Once you meet your shuttle and arrive at the hotel, you could also cross a geofence. This hotel side geofence lets the hotel know that you have arrived on their property. A property geofence allows for analytics around when customers are on or off property, insights into the shuttle service travel times, etc.

Geoconquesting is the ability to leverage geolocation and fencing to pursue those who are patronizing a competitor's location. This information may be used for direct customer engagement via their installed application or indirectly by providing information that can tailor how future marketing is done to sway the customer's future decisions as to where they spend their money and/or time. Let's assume that the "Vegas Hotel" highlighted above is running a strategic marketing campaign to capture more business on the south end of the strip. Geofences could be established around competitors properties for analytics purposes to help an organization better understand how much time their customers are spending on property versus at a competing site. Typically this can then be used to entice users to come back to their establishment.

Geofencing is a very powerful component of context aware networking, however the engagements need to be used sparingly as there are many users who feel this type of engagement could be an invasion of privacy if they weren't expecting to receive messages. There are many use cases for the back end analytics enabled by geofencing from location enabled work flow automation for a mobile fleet to targeted interactions with customers to predicting whether or a patient might arrive for a doctors appointment or not and early adopters of this technology have a distinct competitive advantage versus those who do not have the same capabilities.

An Intro to the Contextually Aware Networking Blog Series (Published 12/28/2014)

Part I: Building a Contextually Aware Network: Beacons (Published 12/28/2014)

Part II: Building a Contextually Aware Network: Geolocation (Published 1/2/2015)