Return-to-work: Best Practices for Implementing Proximity Tracing to Reduce Workplace Risk

Return-to-work: Best Practices for Implementing Proximity Tracing to Reduce Workplace Risk

Contract tracing is especially top of mind given the global challenges surrounding COVID-19, and, in some cases, it’s a requirement as organizations begin re-opening their doors to employees and customers. Analyzing location-based data from network-connected devices or Bluetooth and mobile application signals can significantly reduce workplace risk and enable a safe return to work.

We recently sat down with Joel Crane, Partner Sales Engineer at Juniper, and Ron Frederick, VP of Solutions Architecture at Kudelski Security, for a webinar covering effective methods for user location data collection and how to apply the analysis of that data to reduce workplace risk through various forms of contact tracing. A recap of that discussion is below.

Three ways network-based location data can be analyzed to reduce workplace risk

Enforce social distancing guidelines with congestion alerting. Congestion alerting is the most straightforward way to use location data. It doesn’t require user-level identification, just signals from Bluetooth, WiFi, or a mobile application. Defining a capacity limit for each area or zone will allow you to identify areas that exceed the allowed number of users, at which point you may choose to alert those nearby users that they are in or entering a congested area.

Identify potential contact events with proximity tracing. Proximity tracing looks at user-level location data to identify possible encounters, e.g. the areas and contacts the user comes in contact with and the time and duration of the encounter. This type of analysis requires the user to be identified by their device via Bluetooth, WiFi, or a mobile application.

Understand the potential spread with user journey mapping. Together with proximity tracing, user journey mapping creates a map that allows you to trace a user’s journey throughout a site, floor or zone as defined by your network access points. User journey mapping also requires user-level identification, which can be provided by a Bluetooth device, WiFi connection or mobile application.

Methods of collecting user location data for analysis

The type of analysis you’re able to perform depends on the accuracy and completeness of the location data you’re able to collect. There are three primary methods of collecting location data—each with its own advantages and disadvantages.

WiFi Networks

WiFi is the best place to start for location data gathering. It’s the easiest method to deploy, only requiring an access point to be installed. In fact Juniper includes this type of tracking with all their Mist deployments. WiFi is always-on, meaning your location data is nearly real-time. It’s one limitation, however, is accuracy. WiFi location data is accurate at about 5-10 minutes, which is okay but not great.

There are two variations of WiFi data collection: connected users and unconnected users Connected users have a phone or device connected to the WiFi network. This allows you to track users at the individual level by hostname or MAC address. Collected data from unconnected users won’t give you the ability to uniquely identify a user, but it will show you how many devices are scanning for WiFi in a certain zone.

Bluetooth Beacons

Bluetooth is a great option for collecting location data because it’s always-on. It’s easy to connect a user to a Bluetooth device, especially if you implement a Bluetooth beacon on employee badges (e.g. kontakt.io). If you’re looking at all Bluetooth devices, however, you will need to account for users having multiple devices on their person—a phone, headphones, badge, etc. Bluetooth location data is moderately accurate at about 3-5 meters.

Bluetooth also provides the most variety in terms of the methods of data collections available. Passive BLE listening, for example, can tell you where Bluetooth devices are, but not who they belong to. BLE tags, like a kontakt.io beacons, are constantly signaling and would be tied to a specific user, giving you more precise, real-time location data. Finally, BLE application-based tracking ties to a user’s device….

Mobile Applications

Using an application installed on a mobile phone is the most accurate way to collect user-level location data at about 1-3 meters accuracy. This makes it very precise, but with a caveat. You are only able to collect data from users who have the app installed on their device. For corporate devices, this won’t be a problem. You can use your mobile device management platform to push the app to all employees. For BYOD or customer devices, however, you may need to offer an incentive to entice users to install the mobile app. Mobile applications also allow for bi-directional communication, which enables push notifications, and blue to navigation if needed.

Juniper’s Mist platform now supports digital contract tracing to enable a safe, secure return-to-work. Mist customers can perform capacity analysis, proximity tracing and user journey mapping with a subscription to Juniper’s Assistant and Premium Analytics services.

For assistance in evaluating a digital proximity tracing solution, request a consultation with Kudelski Security’s Advisory Services here.

Watch the Contact Tracing webinar here.