Beautiful Places Pitch 26 October

© Beautiful Places AI Community Interest Company 2023 www.beautifulplaces.ai
A COMMUNITY DRIVEN
AI APPROACH TO
CREATE MORE BEAUTY
IN OUR LIVES….

www.beautifulplaces.ai 2
© Beautiful Places AI Community Interest Company 2023
From breathtaking
landscapes to
stunning
architecture,
beautiful places have
enchanted humans
for centuries.

© Beautiful Places AI Community Interest Company 2023 Photo by Maxence Werp
Beautiful places
stimulate our
imagination. We
often look to
beautiful scenery
for inspiration
and awe.

© Beautiful Places AI Community Interest Company 2023 Photo by Ben Bird
Beautiful places
beckon us to venture
beyond familiar
surroundings, taking us
out of our comfort
zone, enabling us to
discover new places,
cultures and
experiences.

© Beautiful Places AI Community Interest Company 2023 Photo by Mason Dahl
Be it the picturesque
town square or the
verdant local park,
beautiful places
serve as rich
gathering points for
local communities.

© Beautiful Places AI Community Interest Company 2023 Photo by Dwinanda Nurhanif Mujito
Beautiful places can
have a profound
impact on our
emotions. We seek
them out whenever
we need respite
from our busy daily
lives.

Beautiful surroundings help
local economies flourish by
attracting people to live, work
and spend time in such areas,
stimulating consumer
spending and boosting local
businesses.

Despite our deep
appreciation for beauty,
the inherent beauty of
many places now stands
at risk or is fading with
time...

© Beautiful Places AI Community Interest Company 2023 Photo by Celil DOĞAN
Urban sprawl and
congestion are
reshaping once-idyllic,
walkable cities, evoking
images of dystopian
landscapes veiled in
pollution.

Extreme weather
events due to climate
change are threatening
biodiversity, affecting
our lush forests and
diverse flora, degrading
the beauty of our
natural landscapes.

Developing buildings without
considering beauty often leads
to monotonous designs and
lacklustre neighbourhoods
that deprive residents of
vibrant outdoor experiences
and discourage community
engagement.

While hasty and
ill-considered
development can
erode the charm of
captivating
landscapes…

…well-planned
design not only
preserves their
beauty but also
paves the way for
sustainable
economic
progress.

We intuitively grasp the
profound influence of
beautiful places. They
enhance our personal joy,
solidify community bonds,
and act as catalysts for
economic prosperity.

However, their quantifiable
value remains elusive.
Beautiful Places AI bridges this
gap, delivering vital data to
empower initiatives that help
safeguard and create more
beauty in the world.

WHO WE ARE

Chanuki Illushka Seresinhe, PhD
Co-Founder
Chanuki received a PhD in Data Science from the
University of Warwick. Her research at the
University of Warwick and the Alan Turing Institute
involved understanding how the aesthetics of the
environment influences human wellbeing. Her
research has been featured in the press worldwide
including the Economist, Wired, The Times, BBC,
Spiegel Online, Guardian, Telegraph, Scientific
American, Newsweek and MIT Technology Review.
Commercially, Chanuki currently works as the
Head of Data Science at Zoopla and HomeTrack.
Stephen Law, PhD
Co-Founder
Dr Stephen Law is a Lecturer, Assistant Professor,
and Convenor, directing the MSc Social and
Geographic Data Science at UCL, and a Turing
Fellow at the Alan Turing Institute. His research
interests spans GeoAI, geographic data science,
computer vision, network science, urban
economics, urban planning and urban design. He
has completed a PhD in UCL studying the
economic value of spatial networks in the housing
market and has over 10 years’ international
consultancy experience delivering urban design
projects in the UK, Europe, Asia and the US, with
multidisciplinary teams in both Aecom Hong Kong
and Space Syntax in London.
Gianni Giacomelli
Advisor
Experienced innovation leader and
C-suite of large information technology services
and software (SAP, Genpact); affiliate to leading
academic research institutions (Head of
Innovation Design, MIT Collective Intelligence
Lab), management consultant (BCG); and start-
up executive. Now full-time focused on the
sustainability (environmental, and social)
innovation agenda and the AI-enabled real-world
transformation that will accompany it
(Supermind.design)
Introducing Us

Beautiful Places AI is a
Community Interest Company
– A Community Interest Company (CIC) is specifically structured for social
enterprises that aim to benefit the community rather than private interests.
– Our organisational foundation is "Limited by Guarantee," which solidifies
our position as a non-profit entity.
– With a CIC we can still monetise curated data, for example, selling high level
Beautiful Places insights to entities such as property or travel companies.
The profits generated are purposefully directed towards various social good
projects and research initiatives that we choose.
– Fundamentally, being established as a CIC ensures the Beautiful Places
Data itself is securely protected with an asset lock. This allows the data to
continuously serve and empower global communities, reinforcing our
unwavering commitment to positive social impact.

WHAT WE WILL DO

Using a combination of crowdsourced
data and machine learning, we want to
create large scale, high resolution
beautiful places data for every country
in the world in order to provide
objective information on beauty to
support decision making worldwide.
While we will start with data for the
United Kingdom, next year we plan to
launch our data for cities around the
world.
1

Measuring Beauty with AI
It all started with our 2017
paper that explores how
online data combined with
deep learning algorithms
can provide a deeper
understanding of which
environments we find
beautiful.
We also found that deep
learning algorithms can
accurately predict the
beauty of outdoor scenes.

217,000 images
1.5 million votes
1 image per 1 km2

Data Source: Scenic-Or-Not.
Contains National Statistics,
NISRA, NRS and Ordnance
Survey data © Crown copyright
and database right 2013.

Place categories
skyscraper: 0.60
tower: 0.27
o
ffi
ce_building: 0.09
Scene attributes
clouds, openarea, manmade, naturallight,
mostlyverticalcomponents, far-awayhorizon,
metal, vacationingtouring, wire
Place categories
coast: 0.35
ocean: 0.30
boardwalk: 0.07
Scene attributes
far-awayhorizon, openarea, naturallight,
natural, directsunsunny, swimming,
sailingboating, ocean, vegetation, warm
MIT Places for Scene
Recognition

Scenic
Coast Forest
Trees
Valley
Mountain

Scenic
Coast
Valley
Mountain
Forest
Trees

Scenic
Cottage Viaduct
Aqueduct
Lighthouse
Coast
Valley
Mountain
Forest
Trees

6.8
Scenic
Cottage Lighthouse Viaduct
Aqueduct

Scenic
Industrial
Highway
Lighthouse Viaduct
Aqueduct
Unscenic
6.8
Cottage

Scenic
Unscenic
Industrial
Highway
6.8

Scenic
No Horizon
Unscenic
6.8
Industrial
Highway

0.8
Scenic
Unscenic
Industrial
Highway
No Horizon
6.8

Scenic
Grass
Unscenic
Highway
6.8
0.8
Industrial
Highway
No Horizon

Places Categories
and Probabilities
Tower 0.19
Bridge 0.13
Church 0.10
River 0.10
Skyscraper 0.05
...
Scenic Score
4.54463
Convolutional Neural Network
(e.g. AlexNet, VGG16, GoogleNet, ResNet152) Output
Input
Pre-trained Places365 Convolutional Neural Network
Scenic Convolutional Neural Network
164,937
Training
Images from
Scenic-Or-Not
Transfer Learning
...
...
...
Convolutional
& Relu
Pooling Convolutional
& Relu
Pooling Fully Connected
Layers
...
Flatten
...
...
Convolutional
& Relu
Pooling Convolutional
& Relu
Pooling ...
...
Fully Connected
Layers
Flatten

HAMPSTEAD
HEATH
UNSCENIC SCENIC

HAMPSTEAD
HEATH
UNSCENIC SCENIC
6.2
Lake Natural
Swimming Hole
River
Swimming
Sailing/Boating
Still water
0.255
0.236
0.096
0.997
0.002
0.001
Hampstead Heath
Ponds
Chelsea Physic
Garden
5.0
Formal Garden
Botanical Garden
Vegetable Garden
Vegetation
Shrubbery
Foliage
0.393
0.193
0.141
0.858
0.098
0.034
Big
0.4
0.3
0.0
0.9
0.0

CENTRAL
LONDON
UNSCENIC SCENIC

CENTRAL
LONDON
Regent’s Park
Regent’s
Canal
The Thames
Hyde Park
St Jame’s Park
UNSCENIC SCENIC

CENTRAL
LONDON
1.7
Raceway
Highway
Industrial Area
Grass
Natural Light
Open Area
0.297
0.186
0.15
0.813
0.164
0.017
1.7
Parking Lot
Picnic Area
Park
Trees
Leaves
Open Area
0.350
0.098
0.086
0.828
0.042
0.037
UNSCENIC SCENIC

TOWER HILL
UNSCENIC SCENIC
c
5.0
den
Garden
Garden
Big Ben Tower of London
4.5
Tower
Church Outdoor
Palace
Man Made
Natural Light
0.422
0.351
0.079
0.988
0.012
4.7
Castle
Palace
Moat Water
Man Made
Open Area
Natural Light
0.501
0.103
0.099
0.997
0.002
0.001

Our goal now is to continue gathering
crowdsourced data on beautiful places
to keep training our deep learning
computer vision models to:
– enable better quality findings for
urban settings
– create the framework to allow us to
generate beauty ratings for any
country in the world at a future date

We will use this data for research
projects to understand the impact of
beautiful places on human and
economic wellbeing.
Armed with quantitative evidence,
public good organisations and local
communities can make more
informed decisions about the
creation and conservation of beauty
in neighbourhoods.
We aim to use the insights from our
algorithm to guide how to design our
cities to be more beautiful and
liveable spaces
2
Papers already published:
Seresinhe, C. I., Preis, T., & Moat, H. S. (2015). Quantifying the Impact of
Scenic Environments on Health. Scientific Reports, 5, 16899.
Seresinhe, C. I., Preis, T., Mackerron, G. & Moat, H. S. (2019). Is Happiness
Greater in More Scenic Locations? Large Scale Evidence From Mobile
Phone And Online Data. Scientific Reports, 9, 4498.

Current research
Using generative models to better understand intrinsic urban design
factors and combinations that contribute to Beautiful Places
Related research:
Law, S., Hasegawa, R., Paige, B., Russell, C., & Elliott, A. (2023).
Explaining holistic image regressors and classifiers in urban
analytics with plausible counterfactuals. International Journal of
Geographical Information Science, 1-22.
Law, S.; Seresinhe, C.I., Yao, S. Upcoming. The intangible value of
street-level urban design using a machine learning approach: urban
beauty, active frontage and street greenery.
Could include:
ornateness
greenery
density
activity
..

We will collaborate with like-minded,
researchers, organisations and
institutions that share our vision,
offering them insights into the
potential benefits of beautiful places.
In addition, we'll grant complimentary
access to curated datasets and
insights, to help amplify the positive
impact this information can have on
human and economic wellbeing.
3

Our Collaboration with Go Jauntly
Go Jauntly is a free community-based walking app
that encourages outdoor exploration. It connects
users to local walks, rich in green spaces, that are
lovingly curated by knowledgeable locals,
enhancing the walking experience through shared
community insights.
We are planning to work with Go Jauntly to create a
series of walks to make beautiful places more
accessible to everyone.
The Beautiful Walks feature will be available free of
charge.

We plan to harness our data on beautiful
places to craft tools that aim to bring
the world's beauty closer to everyone –
both globally and locally.
– Envision an app guiding you to nearby
scenic gems around the world
– Picture immersing yourself in
breathtaking landscapes in the
comfort of your home, tailored to your
preferences.
– Imagine transforming a mundane
street into an enchanting avenue
using augmented reality on your daily
commute.
4

Our ultimate vision is to
ensure everyone can access
and appreciate beauty,
regardless of where they are.

HOW YOU CAN HELP

We are now seeking funding to establish
the groundwork for Beautiful Places AI:
– Establish our first comprehensive database of beautiful places, starting with
the United Kingdom
– Lay the foundation for extending our data collection internationally
– Launch a user-friendly website allowing public exploration of our 'beautiful
places' data
– Develop an API to empower like-minded organisations with tailored access for
their research needs

Our Proposed Timeline
October 2023
8 Nov 2023
Kickstarter Campaign:
Raise money for UK Beautiful
Places dataset + Go Jauntly
collaboration
Coming soon
Beautiful Places
Voting Website
Launch
January 2024
Publicly Available
Neighbourhood
Beauty Ratings Map
Website
Spring 2024
Kickstarter
Campaign:
Global Cities
dataset launch
Summer 2024
Beautiful Places
Data API
February 2024
Beautiful Places
Free Non-Commercial
& Paid Commercial
Licenses Available
September 2024

How you can help
Beautiful Places AI is on the brink of launching a transformative Kickstarter
campaign. Be the first to contribute to this our vision by signing up to be
notified as soon as we go live.
Your early support is crucial in bringing this innovative project to life!
We need your voice.
Whether or not you can contribute financially, your help in spreading the word
is invaluable. Share our mission across social media and in your
conversations. Your enthusiasm and advocacy will fuel our journey and
amplify our impact, helping to make Beautiful Places AI a resounding
success!

How you can help
You can also contribute directly to the Beautiful Places Dataset! Your invaluable
insights will shape the beauty ratings across the United Kingdom. Vote here.

© Beautiful Places AI Community Interest Company 2023 www.beautifulplaces.ai
THANK YOU!
FOLLOW US:
SUPPORT OUR MISSION:
beautifulplaces.ai/contribute
linkedin.com/company/
beautifulplacesai/
beautifulplaces.ai
kickstarter.com/projects/beautifulplaces/
beautiful-places-united-kingdom

Beautiful Places Pitch 26 October

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Beautiful Places Pitch 26 October