Connected Mobile Experiences Design & Implementation

Cisco Confidential© 2010 Cisco and/or its affiliates. All rights reserved. 1

Connected Mobile Experiences Design & Implementation

Jimmy Ray Purser, PE/MSEE

Engineer, TechWiseTV

© 2013 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 2

Connected Mobile Experiences

GUEST PRESENCE GUEST ACCESS GUEST EXPERIENCE

Customer: Presence in the venue. IT: understand network utilization, peak usage, number and types of devices on the network.

L O C A T I O N A N A L Y T I C S

The customer’s personal mobile device and its characteristics are detected before they enter the venue.

The customer is seamlessly and securely connected to the Wi-Fi network based on their personal preferences and profile, including device type and roaming credentials.

The customer receives highly relevant content and services based on their preferences, profile, and real-time location within the business venue.

Business: insights into customer online and onsite behavior, most traffic paths, dwell times, location density etc.

DETECT CONNECT ENGAGE


Vertical Use Cases

Consumers Guests Passengers

• Context rich promotions

• Informed purchase decisions

• In-store experiences

• Maps with featured attractions

• Happy hour show tickets

• Gift shop promotions

• Staff security to passenger traffic flow

• Flight updates gate directions

• Improve travel experiences

RETAIL HOSPITALITY TRAVEL

• Wayfinding patient apps

• Improved patient experiences

• Medical device location history

• Campus maps directions

• Stadium sales athletic event experience

• Real-time bus maps

Patients

HEALTHCARE

Students

EDUCATION


Connected Mobile ExperiencesHow does the vision map out to Solutions?

DETECT CONNECT ENGAGE

• Presence Detection

• MSE Location Services

• Location Analytics

Mobile App

• Auto On-Boarding

• Hot Spot 2.0

• Lobby Ambassador

• ISE

Mobile ConciergeSDK

Meridian App Editor

Browser(Future)

On Device without

Application 802.11u

/MSAP (QC)

Concierge enables engaging with customers via different media

Different ways to implement app

Mobile Concierge


Connected Mobile Experiences Software Requirements

Platform Min SW versions

Wireless LAN Controller 7.2

Access Point 7.2

Cisco Prime Infrastructure 1.3

Mobility Services Engine 7.4


Location Analytics ThinkSmart Integration

Transforming device positioning information into actionable Business Intelligence


Overview – Location Data Usage < 7.4• The MSE collects and maintains device location data obtained from Wi-

Fi enabled devices such as smartphones, tablets and laptops as they pass through the Cisco Wi-Fi network, saving it “as is” in the database

— The basic data is of the form, <MacAddress, time, coordinates, attribute1... attributen>

• In previous versions of the Cisco Wi-Fi network architecture, this data was simply retrieved by an API call from the Cisco Prime Infrastructure and used to display device location information to the user via the GUI or in a simple report

• In 7.4 the ThinkSmart Analytics engine has been directly integrated into the Mobility Services Engine

— Analytics GUI is served directly from the MSE platform

— Shares the same database while using a separate table space


Overview – Location Data Usage > 7.4• Analytics engine uses location information in the MSE database to create new

knowledge about an environment by summarizing activities in terms of:

— Areas

— Dwell times

— Paths Taken

• Choice of direction

• Routes taken

• When analyzed in ThinkSmart, the location data produces information and knowledge on movement and behavioral patterns on the devices at a specific location, transforming previously underutilized device positioning information into actionable Business Intelligence

— Aggregates separate but related pieces of location data: such as client ID, position, dwell time, etc. into a single data point

— Identifying different types of behavior even in the same building

• An analyzable location can be a shop, mall, airport or a city center, provided that it has a network of wireless access points enabling devices moving within that space to be located


Enabling the Analysis Engine• Although the ThinkSmart Analytics engine is installed on the MSE during

the 7.4 software installation process, it must be enabled for use via the PI before the Web interface is accessible.

— Requires an Advanced Location Services license for MSE


Network Preparation• In addition to licensing, before analytics visualization and reporting is available

floor plans and coverage areas must first be defined in the Prime Infrastructure and synchronized with the MSE

• A coverage area in the MSE correlates to a zone for the purpose of analysis

— A zone is a user defined space with a name and can be used for reporting or path description purposes; zones can be overlapping and need not cover all the building

— For example: If a customer wants to analyze user behavior within a specific area of a location, such as an individual store within a larger mall complex, then a coverage area defining that store must be defined in the PI.

• As analytics information is derived directly from the device positioning information in the MSE database, it is only as accurate as the information contained in the MSE database

— To obtain the most accurate information the Wi-Fi network contributing location information to the database must be deployed in accordance with Cisco best practices for location awareness


Cisco Analytics Architecture

Thinksmart AnalyticsEngine

DataMediation

MSEDatabase

Device/PathDatabase

WLC Location

Data

Reporting

Graphical UserInterface

ResultsDatabase

Lo

catio

n

Da

ta

Floor plans

& zones

JBoss ApplicationServerMobility Services Engine

MSE Location Analytics Architecture for Release 7.4

Reports

Will be updated to Apache TomcatIn 8.0 timeframe

Automatic conversion of data to results on: dwell, device no., movement, frequency


The Analysis Process• Full data analysis is comprised of six individual processes:

— Data Checking

— Data cleaning

— Tagging

— Filtering

— Parameter estimation

— Behavior mining

• By combining these processes the system can handle very large amounts of data that can be correlated and analyzed to summarize activities, which allows us to both visualize the data and output it in a report format as well

• The ability to visualize the results in both 2D or 3D formats provides the user an improved understanding of the results

— This is especially true in a multi-story environment where paths and dwell times must take vertical movement into account


Accessing the Analytics UI• Open a WEB browser and navigate to http://<mse_IP_address>:8080/ui

Default login is:Admin/Adminalthough any username configured on the MSE will work


Visualizing the Data• Both 2D and 3D views are available, with 3D as the default

3D building representation requires using a browser that supports WebGL

Note: Not all browsers support WebGL on all hardware

Ideally the hardware would have a

3D graphics card to

ensure compatibly with WebGL

Birds-eye or Overhead view


Browser Verification• Test your browser for suitability at http://get .webgl.org/

— If this is successful, you should see a WebGL rotating cube

— If the support is not there, it may be possible to update your video driver

For Firefox, confirm suitability by going to: Help->Troubleshooting Information, then scroll down to Graphics and WebGL Renderer. This will indicate if your system can support WebGL and if not what is recommended.

For Chrome, follow: http://support.google.com/chrome/bin/answer.py?hl=en&answer=1220892


Intro to the Analytics UI• Analytics View with default building

Analysis Control Panel

3D Result Visualization Area


A Better Analytics UI For Outdoors• Two Dimensional Analytics View with Open Street Maps

2D Result Visualization Area

Identical Analysis Control Panel


Analysis Control Panel• Allows the customer to define the type of analysis they want to carry out

and on what subset of devices, such as date, time, zone, etc.

Rule types to specify which devices are considered in the

analysis

Start the analysis

Type of analysis to conduct

Building to conduct the analysis on

Switch between analysis and reporting


Navigation and Information Panel• The panel in the upper right-hand corner provides navigation, view, and

parameter selections

Point, Orbit, Pan and Zoom controls

Select 3D view

Select 2D view or overhead perspective

Result Visualization controls

Parameter SelectionAdditional

Information


Available Reports• With this release of analytics processed on the MSE we are limited to

five pre-canned report options


Focusing the Report Output

• Although reporting is limited to pre-designed formats, each report can still be customized to focus the output to a smaller data set.


Report Output Format• Once a report is run the results are returned as a downloadable .pdf file


MSE Wi-Fi Location Based Services Planning GuideUnderstanding Location Services Impact on Network Design Decisions


• Wi-Fi AP measures and reports RSSI (Receive Signal Strength Indicator) to WLC

• WLC (unified/Flexconnect) aggregates and periodically reports them to MSE via NMSP

• MSE applies advanced positioning algorithms

• Determine location (RF fingerprinting/modeling)

• Location notifications (e.g. to Meridian)

• Statistical processing for Location Analytics

• Displaying all devices on a map in CPI

Location Based Services Architecture

Cloud-basedapplication(e.g. Meridian)OpenAPI

(SOAP/XML)

NMSP

Mobility Services Engine (MSE) w/Mobile Concierge & Location Analytics

Wireless LAN Controllerunified or FlexConnect

Wi-Fi Access Point(AP)

Wi-Fi Access Point(AP)

Wi-Fi Client Wi-Fi Client

Cisco PrimeInfrastructure

Intra/Internet

LAN orWANSOAP/

XML


General Architecture ConsiderationsCo-located (AP, WLC and MSEin the same LAN)

Partly Distributed (AP on LAN, WLC& MSE remote)

Fully Distributed (AP & WLC in the same LAN and MSE remote)

Location application

In-house E.g. corporate HQ Server Cloud based E.g. Meridian Cloud based E.g. Meridian

MSE MSE+WLC per site E.g. campus MSE+WLC per DC E.g. retail HQ MSE per DC E.g. Regional HQ

WLC MSE+WLC per site E.g. unified WLC

MSE+WLC per DC E.g.Flexconnect WLC

Unified WLC per site E.g. property/venue

Bandwidth considerations

Insignificant (links >=100Mbps vs. LBS traffic <1Mbps)

Significant (MSE & app server link ~ T-1 vs. 5Mbps for 100K client for northbound API)

More Significant (MSE & App server link + WLC & MSE link ~T-1 vs. 1.5Mbps for 10K client for NMSP traffic)

TPS considerations

Over 1000 TPS for 100K client per campus/venue



Cloud-basedlocation application(e.g. Meridian)

MSE per data center(e.g. Regional HQ)

Unified WLC per site(e.g. property/event)

Internet(e.g. T-1)

WAN/Intranet (e.g. T-1)

GigE LAN

Cloud-basedlocation application(e.g. Meridian)

MSE+WLC per data center(e.g. Retail HQ)

e.g. FlexConnect WLC

Internet(e.g. T-1)

WAN/LAN

GigE LAN

In-house/ITlocation application(e.g. corporate HQ)

e.g. Unified WLC

Intranet(e.g. OC-1)

GigE LAN

GigE LAN

MSE+WLC per site(e.g. Campus)Flexible MSE

deploymentoptions


Advanced Location Based Services(Mobile Concierge)• Bandwidth considerations

— BW between MSE and Meridian servers

— BW between WLC and MSE

• TPS considerations— Transaction rate of MSE (Each

location/zone based location updateis a distinct SOAP/XML transaction)

CoreApp

Mo

nit

ori

ng

&R

ou

tin

g

SDK

Sent to Meridian Cloud- Location Notifications- Map data

Calls to Meridian- Get map Data- Get Current Location

Response from Meridian- Map data (images)- Current location (x,y, time)

Client App

All oth

er data to

/from App

- App data

Positioning information

(MSE detects device & location)

Cisco MSE

Cisco WLC

Meridian/Cloud-basedLocation Server

App Server

Considered in planning guide/calculator

Not considered in planning guide/calculator

MSE TPS


RF planning for Location Based Services

Use case Event Action

Presence user enters building/store

send welcome message form Mobile Concierge

Proximity user is close to product display

send advertisement

Asset-tracking devices/tags has moved outside area

alert loss prevention

Mobility/path tracking

Subject movements Location Analytics updates

Zoned(Geo Fenced)

Un-zoned

RF Network supports such applications based on expected accuracy and currency.


Location accuracy/currency examples• Accuracy: function of AP density & AP height

• Currency: function of AP density and client type (client probes network at different rate)

Application Venue type AP density Avg. Accuracy Currency

Presence Mall, airport … 10+K Sq ft 30ft N/A

Proximity Retail … <2.5K Sq ft 15ft ~30s

Asset-tracking Enterprise, mall … 5K Sq ft 20ft >> 1min

Mobility-tracking Mall, airport … <2.5K Sq ft 15ft ~30s


Average expected accuracy examples

CUWN with an average of2500 – 5000 sq. ft cells

5 – 7 meter


Total location error

Movement error(currency)

RF Uncertainty

Client speedUncertainty

Estimation error(accuracy)

uncertainty in exact RF propagation loss between the client and the AP

uncertainty on speed of the user since the client device reports position periodicallyInitial position estimation error

+ Movement error

TOTAL LOCATION ERROR


Designing Location Services - Best Practices • Based on accuracy and environment type (office vs. indoor high-

ceiling), the density of APs (average cell-radius) can be determined and maintain average cell-radius throughout the service area on each floor.

• Plan for location (e.g. using the PI planning tool)— Design for good coverage first (RSSI of >= -85dBm on all channels clients

support)

— Design for good cell-edge delineation (i.e. ensure client roams between adjacent cells)

— Each client should be within convex-hull of 3+ APs on the same floor

— Place perimeter AP’s first then place interior AP’s to minimize coverage gaps

— Staggered AP deployment (not in a straight line) [esp. in long narrow coverage areas like hallways, corridors, tunnels, etc]

• Use location rails, exclusion regions, and inclusion regions to constrain the location prediction to valid areas of the map with the PI Map editor.


Designing Location Services - Best Practices • Characterize the CUWN RF environment either using the pre-

canned RF Fingerprinting models (preferred) or via RF calibration (measurement) followed by a location accuracy assessment.

• Four default pre-packaged RF models are provided with PI:— Cubes & walled offices

— Drywall office only

— Outdoor open space

— Indoor high ceiling

• If the provided default RF models do not sufficiently characterize the floor layout, custom calibration models can be created using PI and applied to the floor to better represent the RF characteristics of a given environment.


Designing Location Services – Access Point Deployment Considerations• Proper placement and density of access points is critical in achieving the

quoted location tracking performance

— Original design may have been based on coverage model

— Evolving needs may require a different AP-deployment model

• Access Point Density recommendations— Use smaller, overlapping cells (lower data rates disabled)

— For wireless data only deployments: 10% AP cell overlap

— For wireless data + voice deployments: 20% cell overlap

— AP density [Cell radius/area] 28ft/2500sqft – 40ft/5000sqft

• Antennas should be oriented horizontally (vs. vertically)

• Antenna diversity should be enabled (ClientLink not relevant for location)


Advanced Location Based Services(Location Analytics)Location Analytics Application (LAA): co-located with MSE

• LAA shares DB with MSENo additional BW needed between MSE & WLC

• background task ran infrequentlyNo compute resource impact

• DB schema distinct from MSE• Estimated DB storage is

200MB/million points

• Number of points =#_clients * duration_in_days *(#_location_reports_per_client_per_day + #_zone_crossings_per_client_per_day)


Location Services Calculator• Calculates MSE BW and

TPS Due to location tracking & location altering (LT & LA)

— Based on rate at which client roams between APs and

— Rate at which client enters/exits user defined zones.

— Above rates are estimated based on network topology (e.g. client, AP density) Venue type (e.g. retail, office) and building dimensions (floor size, number of floors …)


Location Services Calculator• Inputs:

client types,

network nodes in volume

(# clients, # AP, # WLC) or density

(sq.ft/client, sq.ft/AP),

venue type and building parameters

(sq.ft/floor, # floors).

• Outputs:NMSP Bandwidth per WLC (bps)

NMSP Bandwidth per MSE (Mbps)

SOAP/XML Bandwidth per client (bps) [due to both LT and LA activity]

SOAP/XML Bandwidth per MSE (Mbps) [due to both LT and LA activity]

MSE Transactions per MSE (TPS) [due to both LT and LA activity]

Accuracy (ft)

Currency in distance (ft) and time (s)

Incremental Location Analytics storage (GB)


Location Services Calculator – BW, TPS, Storage, Currency and Accuracy

Samsung Tab (small)Samsung Tab (large)Samsung PhoneIntel PhoneApple iOSIntel LaptopGeneric (mix)

Client Access Point

Controller

Physicalaspects

OfficeRetail


For More InformationCisco Documentation

• Cisco Prime Infrastructure Configuration Guide for Software Release 1.3

• Connected Mobile Experiences Deployment Guide using Cisco Mobility Services Engine (MSE)

Via the Web

• CMX External Web www.cisco.com/go/mobileexperiences

• Cisco Internal Webhttp://iwe.cisco.com/web/view-post/post/-/posts?postId=234200126

For any inquiry –

[email protected]

http://www.cisco.com/go/mobileexperiences

http://iwe.cisco.com/web/view-post/post/-/posts?postId=234200126

mailto:[email protected]

Technology

Connected Mobile Experiences Design & Implementation