Challenge Submission
17th January 2020
Contact:Celso L. [email protected]
Smart Buildings Challenge
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond
the people not involved in the evaluation process.
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Celso L. Masid
http://cubelizer.com/
http://cubelizer.com/shopping-centers/
Use Case #1 – Smart Space Flow Analytics
Submitter contact data:Company name:
Links:
Use case
About CUBELIZER’s Team
Page 2
Cubelizer® helps Shopping Centers to be transformed in high Performance Assets.
WHAT CUBELIZER DOES
Executive Summary | More than Footfall: Enhancing Shopping Centers Through Actionable Analytics
Main References
Clustered operators (affinity between tenants-
visitor’s profiling)
Operators & space performance analysis
Real time alerts and information (occupancy,
capture ratio, traffic, length of stay)
Trajectories (Actual Visitor’s Shopping Sequence)
WHAT DEKA AND ECE CAN GET
Multisite benchmarkIdentify the best practices between different malls and
compare multisite tenant’s performance.
Multisite predictionsPrescriptive design, compare different assets, identify
patterns and detect anomalies in an automatic way.
Performance and commercial mix forecastsDetect low performance operators in advance and
identify best commercial mixes to design and redesign
them
Technical Description
Why Cubelizer is the best solution Solution Design Category
Design new mall’s layouts in advance and redesign current ones (based on current data and future mix predictions).
Set new leasing rules based on new KPIs beyond
current and traditional ones (win-win contracts).
How good are performing their asset management
companies.
Set new marketing strategies based on “universes”
and “affinity” and know the specific traffic impact of
events in each tenant (individual ROI).
Improve profits and sell more, so the mall owner gets
more from the asset as a fee over sales.
Be a proactive and dynamic manager and
anticipate problems: Quick identification of potential
underperforming tenants, real time alarms and predictions.
Gain power in negotiation process with tenants with real and complete performance.
Location precision. (below 20 cm vs. 3-10 m other
technologies)
Full Control and Integration. Control over every element
(HW & SW) what gives total flexibility in our value proposition
and further customer requirements.
100% people coverage. No need of smartphone, no
need of downloading and app to gather data
No personal data involved. GPRD compliant. Fully
anonymous gathering data and process. No privacy issues.Standalone solution for smart space flow analyticsCUBELIZER solution is an end-to-end one (SaaS model) for the goal of
the challenge. Moreover, delivered data could be easily integrated
in a cockpit or bigger management platform using our M2M API.
Current stage: prepared for scaling-up
Continuous development process as needs are detected
CUBELIZER solution is ready for scaling up. The platform is stable and
designed for growth and support site and multisite approach. It has
capacity to absorb and implement new features or functionalities in
case they are identified as we develop them.
There is room for new features and functionalities, as well as, certain
level of customization if it is required.
IoT | Fog computing | Computer Vision | Machine
learning | Deep learning | API |Real Time Processing
On-site infrastructure of multiple IoT devices that perform people
detection and tracking, using computer vision and machine and
deep learning algorithms. Per-device tracking data is sent to the
cloud where full path trajectories are built and then transformed in
real time into actionable quantitative metrics (traffic, flow,
occupancy, store capture rate, store dwell time, store traffic
origin, etc). Cubelizer provides a real time and historical
visualization dashboard and a M2M API.
Computer vision Detection and tracking of persons in real time, using a combination of classical algorithms + machine learning algorithms + deep learning algorithms, for different purposes and stages.
Machine learning Used for detection classification, people tracking, data forecasting, (*) data anomaly detection, (*) clustering and (*) device health monitoring.
Deep learning Used for people detection, object detection and extraction of high-level features.
IoT Autonomous devices sensing and gathering data. Remote operation, update, supervision, self diagnosis and different failure modes.
Fog computing Devices are not just sensors, but processing nodes. The computer vision algorithms run on the IoT device.
The backend infrastructure is highly agnostic and can be
executed in very different environments and architectures. In
detail:
- Cloud services used are mostly IaaS and some PaaS, but
no SaaS.
- OS is open source Linux and used features are common
between distributions.
- Open source standard libraries are used for data
processing, computer vision and machine learning.
- Open source standard packages are used for deployment,
process automation maintenance and other support tasks.
Page 3
General Descriptionof Solution
Page 4
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Solution Design| Why
Page 5
Information is power
Life happens in physical spaces
No measure, no management
Retail is detail
You must
squeeze all
your shopping
centers
opportunities
Our beliefs:
Transforming shopping centers into high performance assets
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Solution Design| How
Page 6
Short-term information Medium-term information
Clustered operators (affinity
between tenants-visitor’s profiling
Operators & space
performance analysis
Real time alerts and
information (occupancy,
capture ratio, traffic, length of stay)
Trajectories (Actual Visitor’s
Shopping Sequence)
Multisite benchmarkIdentify the best practices between
different malls and compare multisite
tenant’s performance.
Multisite predictionsPrescriptive design, compare different
assets, identify patterns and detect
anomalies in an automatic way.
Performance and
commercial mix forecastsDetect low performance operators in
advance and identify best commercial
mixes to design and redesign them
The more assets and more time, more value.
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Device
Device
Solution Design | What
Page 7
CUBELIZER happens to provide business intelligence, benchmarking and
customer behavior insights using a computer vision based IoT solution
Computer vision
Machine learning
In-house developed technology
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Solution Design| Objective
Page 8
Asset Owner Malls Operator Tenants
Delivered value: helping ECE and Deka Immobilien to:
• Understand and demonstrate how
good are performing their asset
management companies.
• How they should design new mall’s
layouts in advance and redesign
current ones based on actual
layouts and tenant's performance.(See Use Case about Choosing the best
Commercial Mix)
• Detect potential new business
opportunities and set new leasing
rules based on new KPIs beyond
current and traditional ones (win-
win contracts). (See Use Case about
new leasing rules)
• Gain power in negotiation process
with tenants with real and complete
performance. (See Use Case about
new relationship with the tenants)
• Be a proactive and dynamic
manager and anticipate problems.
• Quick identification of potential
underperforming tenants. Take
action before it is late.
• Set new marketing strategies based
on “universes” and “affinity” and
know the specific traffic impact of
events in each tenant (individual
ROI). (See Use Case about the impact of
marketing campaigns)
• Create a win-win relationship
between operators, owners and
tenants.
• Improve profits and sell more. At
the same time, mall owner gets
more from the asset as, they
usually charge a fee over sales.
PR
IVA
TE A
ND
CO
NFID
EN
TIA
L. T
he
in
form
atio
n in
clu
de
d in
th
e d
oc
um
en
t is
just
fo
r th
e S
ma
rt B
uild
ing
Ch
alle
ng
e
ev
alu
atio
n. Th
is in
form
atio
n m
ust
be
ke
pt
un
de
r se
cre
t b
eyo
nd
th
e p
eo
ple
no
t in
vo
lve
d in
th
e e
va
lua
tio
n p
roc
ess
.
Solution Design | Solution Category
CUSTOMIZED PRODUCT
Standalone solution for smart space flow analyticsCUBELIZER solution is an end-to-end one (SaaS model) for the goal of the challenge. Moreover,
delivered data could be easily integrated in a cockpit or bigger management platform using our
M2M API.
Current stage: prepared for scaling-up
Continuous development process as new pains/needs are detected
CUBELIZER solution is ready for scaling up. The platform is stable and designed for growth and
support site and multisite approach. It has capacity to absorb and implement new features or
functionalities in case they are identified as we develop them. CUBELIZER aims to deploy the
solution in new many customers in 2020 and following years.
There is room for new features and functionalities, as well as, certain level of customization if it is
required. As we manage whole solution, we can adapt many parts to new needs.
Page 9
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Our solution | Features (1/6)
Real time alerts
Dynamic global management
Northern Male Toilet
5.00 PM ALERT 1
2
Page 10
The system gathers the data and processes it in real time. So, managers
and operation team know the usual intensity and specific anomalies. Push
notifications can be delivered if an anomaly is detected. It allows shift
management to balance the cleaning services, litters checking or even
make events to heat underperformance areas in real time. Cool Eastern Area
5.00PM ALERT 2
MEETING ROOM #4
28
18
2831 31
4449 51
57 58 59
0
10
20
30
40
50
60
70
9 10 11 12 13 14 15 16 17 18 19 20
aggregate people inside
Alert 1
COFFEE MACHINE 2ND LEVEL
50
200
280310
360430
580625
655 675 685 690
0
100
200
300
400
500
600
700
800
9 10 11 12 13 14 15 16 17 18 19 20
aggregate num. coffees
Alert 2
Northern Male Toilet Cool Eastern Area
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Our solution | Features (2/6)
Real time information
Proactive management
Page 11
The system gathers the data and processes it in
real time. So, managers and operation team
know the real time performance of the mall and
the tenants by comparing information with past
information.
Footfall and entries are showed comparing with
expecting data from the past. It allows to know
in real time for example:
• How it is going and take actions to improve
tenants with low performance.
• Or if there is an event or a marketing
campaign knowing which tenants are being
the most impacted.
REAL TIME TENANT INFORMATION EXAMPLE
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Clustered shops according to performance patterns, not just categories
Our solution | Features (3/6)
Clustered operators
CLUSTERS EXAMPLE (based on trajectories)As the system gathers information about tenant
performance (traffic passing by and coming in
each store) based on shoppers' behavior, the
solution provides detail about how the different
stores match to each other, based on
performance similarities.
ECE will have the information about the affinity
between operators to better design the location
of the stores or even provide promotions
suggestions to operators (see daily-time limited
discounts).
HMORSAY
ANSON'S
GERRY
WEBER
ORSAY
MAC BODYSHOP
SEGAFREDO
IL VINO
JACK AND
JONES
KENTUCKY RITUALSMANGO
SUPERDRY
BEST TENANTS' CAPTURE PERFORMANCE - AVERAGE
LABOR FRIDAY WEEKEND
MO
RN
ING
LUN
CH
AFT
ERN
OO
N
Page 12
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Add new KPIs to operator's analysis to improve their performance
Our solution | Features (4/6)
Operators Performance Analysis
TENANT INFORMATION EXAMPLE As the system gathers information about tenant
performance as traffic passing by, coming in,
dwell time (length of stay),… in each store based
on shoppers' behavior.
The solution provides detail about how the
different stores are performing, analyzing weekly
pattern, daily pattern, everyday pattern and
evolution.
ECE will have the information about the same
tenants in different locations, identifying the
benchmark between different assets.
Daily
Average
Traffic
Daily
Average
Entries
Average
Capture
Ratio
SEP19 1,954 851 43.5%
MOM 3.94% 8.98% 6.09 p.p.
YOY -1.23% -5.69% -7.0 p.p.
0
1000
2000
3000
4000
5000
6000
7000
8000
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY SUNDAY
WEEKLY TRAFFIC/ENTRIES - H&M
TRAFFIC ENTRIES
47.2% 46.8% 45.7%48.7%
44.1%40.5% 40.4%
MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY SUNDAY
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
WEEKLY CAPTURE RATIO - H&M
CAPTURE RATIO
0
500
1000
1500
2000
2500
0
1000
2000
3000
4000
5000
6000
7000
MONTHLY TRAFFIC/ENTRIES - H&M
TRAFFIC ENTRIES
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
MONTHLY CAPTURE RATIO - H&M
CAPTURE RATIO
0
50
100
150
200
250
10 11 12 13 14 15 16 17 18 19 20 21 22 23
HOURLY ENTRIES - H&M
ENTRIES M-T ENTRIES - F ENTRIES -WKD
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
10 11 12 13 14 15 16 17 18 19 20 21 22 23
HOURLY CAPTURE RATIO - H&M
CAPTURE- M-T CAPTURE F CAPTURE WKD
H&M
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
50.00
0
100
200
300
400
500
600
700
800
900
APR 19 MAY19 JUN19 JUL19 AGO19 SEPT19 OCT19
H&M EVOLUTION
Average Entries Capture Ratio (%)
Page 13
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Analyze areas and detect flow problems
Our solution | Features (5/6)
Space performance analysis
HEATMAP SAMPLE
As the system gathers information about people
flow, it is possible to analyze space performance
in order to improve costumers experience and
detect high/low activity areas.
ECE will have the opportunity to identify cold
areas and conflictive zones and adopt solutions
to transform them into hot spots and improve
conversion funnels.
High activityLow activity
Problem Flow
Page 14
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Clustered shops according to performance patterns, not just categories
Our solution | Features (6/6)
Visitors Shopping sequence
As the system gathers information about visitors'
trajectories, the solution provides the distribution
of the traffic between the different tenants and
entrances and what it is the main destinations
from one point to another inside the mall.
ECE will have the information about the favorite
cross-selling behavior made by their visitors. So
ECE could activate some marketing strategies to
stimulate sales.
TRAJECTORIES VIDEO SAMPLE
See the video sample here
Page 15
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Our solution | Scale Up Features (1/3)
Identify patterns and anomalies
When the system is deployed for a medium time, it is possible to set
patterns and detect anomalies out of these patterns and create
alarms to the shopping center manager to be prevented of theses
anomalies.
Analyze data to identify patterns and detect anomalies
Cubelizer’ssystem
80% probability of losing an operator
OPERATOR ALERT
0
200
400
600
800
1000
1200
1400
0
10
20
30
40
50
60
70
SEP
17
OC
T 17
NO
V 1
7
DE
C 1
7
JAN
18
FEB
18
MA
R 1
8
APR
18
MA
Y 1
8
JUN
18
JUL
18
AU
G 1
8
SEP
18
OC
T 18
NO
V 1
8
DE
C 1
8
JAN
19
FEB
19
MA
R 1
9
APR
19
MA
Y19
JUN
19
JUL1
9
AG
O1
9
SEP
T19
OC
T19
NO
V1
9
Entries (daily average) Capture Ratio (%) Average Traffic
Page 16
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Identify the best practices between different malls.
Our solution | Scale Up Features (2/3)
Multisite benchmark
When the system is deployed in different malls and for a medium time, we
can identify benchmark and best performance assets.
See Use Case at Cubelizer’s Web about Comparing the Efficiency Between Assets.
Page 17
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Prescriptive optimized commercial mix to improve revenue
Our solution | Scale Up Features (3/3)
Predictions
When the system is deployed in different malls and for a mid term, intelligence artificial
algorithms may deliver prescriptive optimized commercial mix to improve revenue or
to increase traffic. It is possible to define some selected operators and the system
selects the best operators to fit with them.
Selected Operators
Zara
H&M
Mango
Müller
Benetton
Puma
Douglas
Cubelizer’ssystem
Predicted Operators
Zara Home
Intimissimi
New Yorker
Nike
Decathlon
The Body Shop
Superdry
Page 18
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Technical description
Page 19
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
The edge tier collects data from our distributed IoT
optical devices. Cubelizer deploys a network of
identical IoT devices in each location (shopping
center). We have many locations an in each
location, many devices.
The platform tier receives, processes and forwards
control commands from the enterprise tier to the
edge tier.
▪ Data transformation: Cubelizer mapping, full
trajectories and metrics generation (counters,
origin-destiny, dwell time, etc.)
▪ Analytics: Cubelizer business metrics,
generation, time patterns, anomalies, affinity,
etc...
▪ Operations: Remote supervision, private
communication server, software update.
The enterprise tier implements domain-specific
applications, decision support systems and
provides interfaces to end-users including
operation specialists. Cubelizer enterprise tier is
built by the dashboard, the real time alerts, the
asset/store comparison and the prescriptive
actions
Cubelizer IoT devices are currently connected with our cloud infrastructure using Wi-Fi connection.
IIC 3-Tier IIoT System ArchitectureSolution Fully Managed by Cubelizer
Technical description | Architecture
Page 20
PR
IVA
TE A
ND
CO
NFID
EN
TIA
L. T
he
in
form
atio
n in
clu
de
d in
th
e d
oc
um
en
t is
just
fo
r th
e S
ma
rt B
uild
ing
Ch
alle
ng
e
ev
alu
atio
n. Th
is in
form
atio
n m
ust
be
ke
pt
un
de
r se
cre
t b
eyo
nd
th
e p
eo
ple
no
t in
vo
lve
d in
th
e e
va
lua
tio
n p
roc
ess
.
IoT Autonomous devices sensing and gathering data. Remote operation, update, supervision, self diagnosis and different failure modes.
Fog computing Devices are not just sensors, but processing nodes. The computer vision algorithms run on the IoT device.
Key Technologies
IoT | Fog computing | Computer Vision | Machine learning |
Deep learning | API |Real Time Processing
On-site infrastructure of multiple IoT devices that perform people detection and tracking, using computer vision and machine and deep learning algorithms. Per-device tracking data is sent to the cloud where full path trajectories are built and then transformed in real time into actionable quantitative metrics (traffic, flow, occupancy, store capture rate, store dwell time, store traffic origin, etc). Cubelizer provides a real time and historical visualization dashboard and a M2M API.
Deployment Models
Both cloud and on-prem deployments are possible, because open systems and standardized protocols and architectures are used and cloud vendor-specific solutions are avoided.
CUBELIZER standard deployment is cloud based. On-prem deployment would be considered and studied if explicitly demanded by the customer.
Emerging/Deep Tech Used
Computer vision Detection and tracking of persons in real time, using a combination of classical algorithms + machine learning algorithms + deep learning algorithms, for different purposes and stages.
Machine learning Used for detection classification, people tracking, data forecasting, (*) data anomaly detection, (*) clustering and (*) device health monitoring.
Deep learning Used for people detection, object detection and extraction of high-level features.
TECHNOLOGY OVERVIEW
Technical description | Technology
Page 21
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Is A Detailed Description of The API
Available?
Is The Data Exchange Format Described?Are Standard Protocol Like HTTP, MQTT, AMQP, COAP or Websockets Supported?
Are API Defintions Available (Swagger, Odata, Etc.)?
What Kind of Standards for Wireless Communication Is Supported?
Are Standard Formats for the Data Exchange Supported (JSON, XML)?
Yes, there is an OpenAPI specification. Yes. Swagger / OpenAPI specification files are available (v3.0.0.)
The API is based on HTTP. Yes, it is fully described in the OpenAPI specification files.
Data exchange format is JSON, and MIME encoding for multimedia files.
WiFi. In terms of capacity and coverage, the standard infrastructure of a shopping center, even the one providing courtesy internet to visitors, could be used.
Technical description | APIs and Communication
Page 22
Advantagesand Differentiation
Page 23
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Tech advantages
Page 24
Cubelizer use advance video processing algorithms:
High precision location Below 20 cm vs. 3-10 m of other technologies (wi-fi tracking or beacon location).
Full control and integration on the solution Control over every element (hardware and software) what gives CUBELIZER’s solution
total flexibility in our value proposition, capabilities and further customer requirements.
100% people coverageNo need of smartphone, no need of downloading and app to gather data.
No personal data involved. GPDR Compliant. Fully anonymous gathering data and process. No privacy issues.
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Competitors comparison
Page 25
Wifi tracking
App, SDK, Web App
- Customer collaboration: smartphone and Wi-Fi “on” (40-
50% visitors)
- Tracking errors about 5-10 meters.
- Returning visitors (problem with generation of random IPs)
- Less accuracy, mixed data from different levels and zones.
- Customer collaboration: smartphone and downloaded app
or web registration (2-5% visitors).
- Tracking errors about 3-5 meters.
- Returning visitors: ONLY for downloaded app customers.
- Invasive and annoying messages delivery.
- How to get users in an affordable way? Extra cost for
boosting the use or download the app (offers, discounts)
▪ 100% people coverage.
▪ Precision below 20centimeters
Magnetic Positioning- A mobile phone is needed (SDK integration in an app, see
above).
- Positioning errors about 2-4 meters.
▪ Without people collaboration: no app, no smartphone, no login.
▪ There is not possibility of mixed data between levels or zones.
▪ No hidden extra costs
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Ascertainment of pilot scope
Page 26
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
POC implementation | Details
Page 27
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
POC implementation | General data
Page 28
Ettlinger Tor Karlsruhe(Karlsruhe, Germany)
2 + 3.5 months POC
38,800 sqm mall
33,000 sqm GLA
130 stores
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
POC implementation | Description
Page 29
• In the covered area, Cubelizer will gather data about visitor's
behavior: visitor positions along the time that will be
processed and aggregated to generate higher value
information: activity maps, capture ratios of each operator,
flow distributions and patterns, origins and destinations,
traffic, entries, dwell time, etc.
• Cubelizer will deliver a dashboard, API or monthly reports
about space and tenant performance.
• Cubelizer will build the process and the mean to provide
ECE real-time alerts for dynamic global management and
real time information about shopping center
performance.
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
POC implementation | Reason Why
Page 30
Anchor Brand Analysis How anchor brand is working inside the mall in
terms of traffic and traffic distribution. Origins and
destinations from and to the anchor brand.
Common area behaviorAnalyzing how common area is used by visitors,
entries, used, length of stay, …
Optimizing cleaning intervalsAnalyzing the use of the toilets to adapt cleaning
interval to the real use by creating alarms when threshold is passed.
Tenant analysisAnalyzing traffic, entries, capture ratio, dwell time,
patterns, …
Space analysisObtaining information about hot/cold spots, flow
distribution, dwell times,…
Detailed Traffic FlowObtaining information about flow distribution and
people behavior in elevators, escalators and other
accesses with footfall, traffic, patterns and
destinations.
TrajectoriesObtaining origins and destination between tenants
to understand the commercial mix and their
relationship.
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Disclaimer: this picture is a representation of an
imaginary situation that is not linked with reality.
The dashboard shows REAL TIME information
related with accesses, tenants and mall flow.
POC Solution | Information Example: Real Time Information
Page 31
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Comparing evolution data shows tenant's
performance along the time. This information
could be shown comparing malls, tenants in
different floor… or any other aggregation.
POC Solution | Information Example: Tenant Performance
Disclaimer: this picture is a representation of an
imaginary situation that is not linked with reality.
Page 32
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond the people not involved in the evaluation process.
Disclaimer: this information is a representation of an imaginary situation that is not
linked with reality. It has been done to show tenant information.
Cubelizer´s solution
completes the tenants sales
funnel with the following
information:
• passing-by traffic
• entries
• capture ratio
• dwell time inside the shop
or in front of the window
POC Solution | Information Example: Tenant information
Page 33
References and credentials
Page 34
SHOPPING CENTERS10,000 m2 of common areas
(35+ millions visitors).100+months
WORKPLACES7,000 m² of workplaces
analysis in real time.
EXPERIENCE
Page 35
Supported by
Recognized as Innovative Company by “Centro para el Desarrollo Tecnológico
Industrial” on behalf of the Spanish Ministry of Science, Innovation and Universities
Recognized as Innovative Company and funded by the Spanish Ministry of Industry,
Energy and Tourism.
Funded by the European Union's Horizon 2020 research and innovation programme.
Top 2018 “European Retail Tech Startups” by
Top 2018 “Spanish PropTech Startups” by
Acknowledgments
More than Footfall:
Enhancing Shopping Centers Through Actionable Analytics
Smart Buildings Challenge
PRIVATE AND CONFIDENTIAL. The information included in the document is just for the Smart Building Challenge evaluation. This information must be kept under secret beyond
the people not involved in the evaluation process.
