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Hey! Welcome to our latest WiFi Ninjas Blog 🙂 We’ve been busy lately testing some available RTLS solutions from a few different major wireless players and fell absolutely in love with the topic to the point, where we shake from overexcitement when thinking or talking about it ????
This summarises how we feel:
Steve Jobs once said, “people don’t know what they want until you show it to them”. He was right.
20 years ago, WiFi was “a nice to have”. 18 years ago, paper maps were at peak of their popularity, until GPS receivers got small enough to be put in the handheld devices. Is anyone not using Google Maps on their mobile? 15 years ago, not many people felt they needed a wireless headset, until Bluetooth was introduced. 7 years ago, NFC was a niche. Today, most of us use contactless payments using cards, phones or watches.
Indoor wireless RTLS is at the early adoption stage. Technology is available, we just need to make it more interesting and rewarding to use.
Satellite-based location positioning services are not always practical indoors. We could offer wireless RTLS functionality based on WiFi, BLE or soon, possibly, Ultra Wide Band (UWB). Modern smartphones have both WiFi and BLE radios built in. Additionally, new iPhones support UWB. Wireless vendors leverage cell of origin, trilateration, triangulation, angle of arrival, proximity and more with WiFi, BLE, UWB, GPS, NFC, mobile networks or any combination of those methods and technologies, offering different levels of accuracy and functionality. RTLS market is growing fast – according to Bluetooth.com, 1.7 billion devices will use indoor BLE RTLS by 2023, translating to even 500% increase in BLE RTLS implementations in some verticals!
So, what do we need to see the RTLS market explosion? We’ll be speculating, but our hearts tell us that indoor RTLS needs solve real challenges like indoor wayfinding or call for help and simply be more interesting not only for the business’ IT and marketing, but for everyone. We also need more skilled wireless professionals willing to embrace broader wireless technologies and emerging use-cases, like BLE and RTLS, on top of WiFi design, security and analysis skills, while not forgetting about programmability elements.
But enough of the babbling, let’s cut straight to the juicy content! Here is what we will cover in this blog:
Note, that number of APs has tripled!
Generally speaking, if the design is good for RTLS, it’s also good for any
other use case (data, voice, most high-density scenarios, etc.). Sometimes some
WiFi radios need to be put into non-client-serving mode as too much WiFi can be
damaging to the performance of the network (topic for a different discussion).
Let’s look at the video showing CMX app, CMX Dashboard and Matt walking around my house ????
The video screams million words! Let’s take a look ????
Below is a quick summary showing results of our tests for different indoor RTLS solutions!
We have recently worked on project for a beautiful, listed retail store in London, where following a very successful design and implementation of Meraki data WiFi network in the store, retail RTLS topic has emerged. With RF design crafted for data, we have faced a very real challenge – would the existing placement, type and number of APs be useful for indoor Real Time Location Services with a zone-level accuracy?What would be the challenges, limitations and reasonable expectations in terms of RTLS usage and accuracy? Could Meraki API help achieve goals set by the business?
RTLS was not in the original scope and, combined with a store physical environment, we have faced some challenges:
Floor diagrams below show the difference in RF Design for Data (what we have) vs RF Design for RTLS (what we would need for WiFi Trilateration to work):
Based on the additional very detailed survey (more than 100 test locations across multiple floors with 3 different device types: flagship Windows 10 laptop, Android phone and iPhone), where we temporarily installed several new APs on tripods, we concluded that achieving satisfactory and reliable zone-location accuracy (10m 90% error distance) using WiFi trilateration would require to approximately double the number of APs. The business has decided not to install additional APs and knowing that a mixture of Meraki and Purple could not offer reliable location insights and that WiFi trilateration would not be practical to use at all (because of the design, regardless of a vendor), we looked for alternative solutions and new success criteria were defined:
We have gathered some facts: data & voice performance over WiFi, capacity, coverage and roaming were all rock solid across all WLANs (MAB/CWA for guests and EAP-TLS machine auth for corp) and for all test devices (company issued laptops, major OSes, newer and older phones). High density areas, like ground floor entrance hall, could get very busy during holiday periods (200+ associated devices in a small 15x20m area) and were covered by three high-gain dual-band sector antennas. 5GHz was almost free of channel contention with careful APs placement around atriums and use of properly tweaked RF Profiles: 20MHz channels width, limited max and min Tx power, disabled data rates of 11Mbps and lower. 2.4GHz was tweaked even more, with several APs having their radios off and max Tx power set to the level, where RSSI was generally lower on 2.4GHz than on 5GHz throughout the store and only OFDM rates were allowed. 2.4GHz was still considered best effort. Presence & analytics with Purple was spotless.
Switching focus to location zone analytics, we have confirmed with a detailed post-deployment survey, that our test clients were reliably associating with APs installed in the zones they were in. WiFi scans from unassociated devices taken in multiple spots in each zone revealed that we could use strongest RSSI reading from one best AP to accurately pinpoint the probing or associated device to the zone it was in. We concluded that we could potentially leverage two attributes to correlate WiFi devices with their current zones:
Two things to note:
To further simplify our zone analytics calculations, we have decided to use just one attribute moving forward – MAC address of the AP that reports the probing or associated devices with strongest RSSI.
We have discovered that it is possible to get the RSSI attribute for every client seen by all near APs with Meraki API location data. Readings are provided every minute and contain RSSI values covering last 60 seconds. While it’s not very fast and could not be used for a blue dot experience, it is enough for our use case – historical view of zone paths and analytics.
Using strongest RSSI proved to be 95% accurate across entire building and 100+ test spots when correlating user (reporting AP) location with a zone.
Raw Data from Meraki API – note ap_mac, seen_time, client_mac and RSSI
As we know exactly which zone all the APs are installed on, we could easily generate reports showing clients paths with zone accuracy, time spent in each zone, number of clients per zone, etc. without relying on wrongly pre-calculated Meraki XY coordinates.
To automate the zone paths visualisation and zone analytics, client’s software development team has created a tool to do just that. At this point, imagination was the limit.
Sometimes we are limited by a solution functionality when trying to meet
client’s requirements. In our example, Purple could only use Meraki
pre-calculated XY coordinates and it was not practical or accurate enough (even
for a zone-wide accuracy) to use with a data / voice RF design. Let’s answer
our initial question. Do You Need RTLS RF Design for WiFi Location, Presence
& Analytics? Short answer is “no” for presence & analytics
and “it depends” for location. Presence & analytics provide us with
network-wide stats, without the location awareness and therefore will not require
RTLS design. Location, however, requires very careful RF design to provide
different levels of accuracy. With a solid data RF design, where
association and roaming trends are reliably predictable, we could expect solid zone-wide
accuracy. Anything more accurate (trilateration, Hyperlocation, vBLE) would
require more APs, detailed survey, RTLS RF design, careful placement of
APs/antennas and pedantic maps services configuration with spotless APs
positions, height and azimuth set.
At Natilik, we’re currently in the process of upgrading our showcase with Cisco DNA. The plan is to have full SDA Fabric, C9800-based Fabric Wireless, proper RF design with Cisco 4800 APs, CMX and DNAS in one part of the office and a mixture of AP43 with BT11 in the other part. We’d love to not only showcase Cisco Hyperlocation and Mist BLE Arrays in action, but also leverage the tech to offer indoor wayfinding with turn by turn navigation and onboard guests using Hotspot 2.0 (called Open Roaming by Cisco) for our visitors WiFi.
As of today, we don’t have the new showcase fully running yet, so all we have to play with is ‘standard’ corporate WiFi design for Voice and Data.
The above shows one out of the two floors we occupy. With current design, all we can use is Cell of Origin and, around reception, WiFi Trilateration. And that’s it. Location Calculation Frequency of 11-15 seconds is not enough to offer blue dot experience, but we thought it could still be good enough to solve some wayfinding challenges!
We have Cisco AireOS Wireless with CMX, Cisco WebEx Teams and everyone has a corporate phone enrolled with Meraki MDM.
We would love to use the kit we have today to locate a colleague, zone or a meeting room by asking WebEx Teams chatbot about the location of person/location we’re after without the need to install the mobile application, as we can’t have a turn-by-turn indoor navigation just yet anyway.
Let’s imagine that Mac wants to find Matt (yeah, we don’t hold our hands all the time and sometimes attend different meetings on different floors, lol). How do I do it? How would WebEx Teams chatbot know about my or Matt’s location? How could it show or tell me how to find him? Is it really that helpful with approximately 10-12m 90% error distance accuracy? Can we still draw an indoor map showing where should Mac go to find Matt?
First, we had to set realistic expectations. We shouldn’t expect the solution to pinpoint user to his or her desk knowing, that calculated user location has 10-12m accuracy. Instead, we have decided to use zones that are big enough to account for that location accuracy.
Here are the zones we’ve created, ensuring that each zone has at least one AP. We’ve also considered expected AP association ensuring it all makes sense:
Now, we need to figure out what happens when Mac is asking WebEx Teams chatbot about Matt’s location.
Wait, what is a chatbot? Good question! Most modern enterprise messaging solutions allow to create custom chatbots with custom functionality. We are fortunate enough to have a proper coding nerd in our ranks, Darren, that finds coding chatbots as easy as you probably find putting your socks on. Darren has created NatBot (I wonder where the name comes from!), that can translate natural language with certain key words to specific actions.
To make it all fly, we’ll leverage Cisco CMX Location API, Cisco Meraki MDM API and a cloud map service (i.e. Mapwize) to visualise the results.
Finally, let’s look at detailed steps that are happening in the background when Mac is looking for Matt ????
Sounds complicated? Watching this short video should clear things up!
This is just the tip of the iceberg and we have some more ideas about what to do next, once the new showcase is in! ???? Here is the list:
Lastly, here is some stuff that we think might save you some ball ache ????
You’ve made it! This blog has almost 6000 words. Well done! ????
With tons of love,
WiFi Ninjas x