HomeMy WebLinkAboutBack-Up DocumentsSole Source Letter
Changing Environments, Q.B.A. Soofa
24 Thomdike Street
Cambridge, MA 02141
To: Lina Blanco, City of Miami, FL
From: Edward Krafcik, Soofa
Date: 12/02/15
Dear Lina,
This letter is to confirm that the Soofa Bench is a sole source product, manufactured only by Changing
Environments, D.B.A. Soofa and sold and distributed in Florida exclusively by Changing Environments,
D.B.A. Soofa. No other company makes solar powered park benches capable of USB phone and smart
device charging with upgradeable features like usage monitoring and spatial activity sensing through
custom built WiFi scanning sensors. Additionally, no other company makes outdoor furniture, including
park benches, that transfers data to a cloud based application where it can be downloaded as raw data or
viewed through a custom built dashboard or via standard and customizable reports for specific date
ranges.
Ultimately, there are no other like items or products available for purchase that would serve the same
purpose or function as the Soofa Bench for the City of Miami Parks and Recreation Department. Should
you need any additional information, please don't hesitate to contact me. Thank you very much!
Best regards,
Edward Krafcik
Director of Partnerships J SOOFA
edward@soofa.co
908-295-4210
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"Soofa data gives us
new insight into how
our parks are used
which can help us
better optimize the
services we provide
and how we provide
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data, we believe
that it could also
help our
organization make
better informed
decisions about
capital
improvements and
long-term planning
and most
importantly, help us
tell a fuller story of
the impact of our
parks to our
community."
— Bobbi Nance, Senior Manager of
Strategy & Innovation, Park District of
Oak Park
;BEAD THE LAK PARK CASE STUD'
How Soofa Beta Cities Helped Create Soofa Pro
In May 2016 we launched the Soofa Beta Cities network to deploy
Soofa Pro, the sensor -enabled version of the Soofa Bench and the
Soofa Core, which measures pedestrian activity in outdoor spaces. The
sensor passively listens for WiFi enabled devices within about a 150
foot radius of the bench or core in which it is embedded. With this data
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it was our beiiet initially that by providing city leaders with a novel data
set revealing how places like parks, downtown main streets, public
plazas, and trail systems get used by people, city leaders would be
able to plan capital improvement projects more effectively and
measure their success post implementation, analyze the attendance of
events to learn which ores to repeat and which ones to enhance or
change, and reduce staffing costs by optimizing maintenance
schedules based on how much use different locations actually get.
Now about nine months later our original hypothesis has been
validated with the help of a Beta Cities network that includes over a
dozen innovative cities and counties across the U.S. Through our
collaborative product development process with city agencies like
NYC Parks and the Mayor's Office of Tech+Innovation, Oklahoma City,
OK Parks, Sunny Isles Beach Parks and the Mayor's Office, Doral, FL
Parks and IT, county park systems like Prince George's County, MD
Parks, and park districts like the Park District of Oak Park, IL, we have
built out a standard data report to analyze pedestrian use of outdoor
spaces and have also had an amazing experience watching our clients
use our raw data in creative and impactful ways.
Standard Monthly Data Report
Gathering data for the sake of having data doesn't help solve problems
facing cities. In fact, it does quite the opposite as it generally demands
more time from staff members to analyze it and figure out what to do
with when they are already stretched too thin. Therefore, our goal with
the Soofa Monthly Data Report is to provide city leaders with a set of
data analysis tools and insights, including the option to export raw
data, which are action oriented and outcome driven, and displayed
through intuitive, beautiful, and easy to navigate visualizations and
graphs.
The report begins with an overview of all the benches and/or cores in
a city's Soofa network, highlighting the pedestrian activity level at each
Activity
Overview Graph
On the Activity
Overview each
location (1, 2, and 3)
is an individual
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bench or core with a Soofa Sensor. The number of devices seen per
day (the y-axis) is the number of WiFi enabled devices the sensor
passively hears over the course of a single day.
This graph reveals many things about the three different locations that
one would not be able to see without having an eye on each space all
day, every day. For instance, it is clear that although location 2 is the
most active location on average, location 3 actually attracts more
people en masse through a variety of events both on the weekdays
and weekends.
Armed with this easy to understand data visualization, the Parks and
Recreation Department in this particular example is now able to
correlate the spikes in use at location 3 with events that happened in
the park on those days. Additionally, by knowing that location 2 is
routinely the most frequented location of all three, the department is
able to analyze the maintenance schedules of each space to see if
there is an opportunity to alter maintenance hours and number of staff
to achieve the desired quality outcome based on actual use. This
action will lead to direct cost savings while still providing high quality
service to the park goers.
For this example, we will continue to dig deeper into location 3
because of its unique spikes in use. The next way to visualize this
location is with our Daily Breakdown Visualization.
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the activity level of each zam
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day of the month (October
2016 in this example) for a s M T w R F s
particular location. Yellow
indicates the most activity while dark blue indicates the lowest level of
activity seen over the course of the month.
When cross referencing
the Daily Breakdown with
the Activity Overview one
can see each day where
there is a spike in use
indicated by yellow,
green, and light blue on
the Daily Breakdown.
October, 2016
S M T W R F S
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650
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For comparison, location
2 is shown to the right. Note that on average there is more activity,
however, the total number of people on the busiest day is still far
below the total number of people seen on the busiest day at location
3. This data is often used to identify patterns of use between
weekends and weekdays and analyze the patterns of activity across
many locations. One can also refer to this type of analysis as
understanding the "use profile" of a certain park, city street, public
plaza, or trail network.
At this point in using the Soofa Monthly Report a city agency now
knows how busy different locations are, how each of those locations
compare with one another, and how the patterns of use change or
remain similar between the weekend and weekdays. The next level
of detail available to analyze outdoor space use is the Hourly
Activity Level Graph. This visualization lets an agency analyze
activity per hour on any given day.
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The Hourly Activity
Level Graph above
shows the activity
per hour in location
3 on October 29th.
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This day was the busiest day of all of October at not only location 3 but
all locations. It is now possible to look at exactly when the park traffic
occurred, and for how long people stayed. The graph shows that there
were two distinct peaks of activity. When the Parks and Recreation
Department went back to look at this day, it noticed that there were
community basketball league games taking place. The data shows that
the first game happened in the late afternoon while the second
happened in the early evening.
With this data the agency not only is able to see the peak traffic times
and the number of people in attendance, but also is able to see how
fast the event attendance picked up and let out. This data can be used
to help plan for things like park cleaning and crowd management in
the future.
Having analyzed just a few graphs and space analytics visualizations,
the Parks and Recreation department in this example has an
unparalleled understanding of how their spaces are getting used. It
knows which space is generally the most active, which space sees the
most dramatic rise and fall of attendance, when people tend to visit
and hang out, and how the overall profiles or space use relate to one
another. To be able to look more closely at the average use profile, we
have developed the Activity Profile Average Comparison.
Activity
Profile
Average
Compariso
Weekday Weekend
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many community tournaments. The graphs for the weekday and
weekend profile are developed by averaging hourly pedestrian count
data for the entire month of October. One can see that this location is
much more popular on average in the afternoons and evenings. The
context of this park is in a residential neighborhood and close to a
school. Many of the events that are organized or take place
spontaneously happen after the school day is over or in the date
afternoon on the weekend.
For comparison, location 1 is shown below. Location 1 was originally
believed to see more walking and biking commuters in the early
morning, as shown by the spike on the weekday profile. However,
upon further investigation it was found that many people were actually
out for early morning exercise routines like walking, jogging, cycling.
By using this data it is now possible for agency leadership to make
planning decisions and programming decisions. For example, the
agency can ask questions like, "how can we increase use of location 3
during the earlier hours of the day on a weekend as opposed to just
the afternoon and evening?" and "can we add an amenity like an
outdoor fitness station at or near location 1 because of how many
people are already ,passing by on their morning workout routine?" The
data can be used to inform planning and design decisions and then
used after the completion of an intervention to see if the outcome that
was desired actually happened.
The last component of the Standard Data Report is to analyze
pedestrian flow. The Soofa Flow Analysis Map enables city leaders to
identify popular routes of travel for pedestrians and see which
locations are most popular within a neighborhood or park.
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Pro sensor embedded.
Now, Eike never before,
city leaders, designers,
planners, and developers
can visualize popular
routes of pedestrian travel
by foot. The map above is
to be read as the
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percentage of all people
who were seen at each different location (as indicated by the colored
dot) who were seen at both locations. So, for example, in this location
1796 of all people who have passed by the benches at the locations of
the orange and green dots were actually seen at both locations. This
lets one understand that the connection between these two locations
is the strongest of all connections in this particular park.
This type of flow data is incredibly powerful for measuring the success
of capital improvement projects in parks or downtown neighborhoods.
By gathering reliable baseline data using the Soofa Pro sensor, a city
can measure and analyze how a new amenity, park design, public
plaza activation, and the like actually impact the pedestrian use of
those spaces.
Another way to measure and analyze pedestrian flow is with the
Popular Entrances Map.
Popular Entrances Map
The colored bars 40%
represent different
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benches within a park.
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the park, the graph identifies which bench they passed by first.
Applying this logic to the graph it is then clear that the bench identified
by the orange bar and the bench identified by the green bar are
located at the two most popular entrances of the park.
Raw Data
For cities and agencies who are already very advanced with data
collection and analysis, Soofa shares raw data In the form of csv files
and an API. Organizations like the Park District of Oak Park currently
import Soofa's raw data into the agency's dashboard. The data on
pedestrian traffic and use patterns in the District's parks is correlated
with weather, marketing activities, and events hosted by the District
directly as well as those permitted for the community.
Do you want to be first to deploy Soofa Pro when it officially
launches as a product this March? Simply sign up to join our wait list
and get in line for exclusive benefits by being first.
;01N THE 5OOFA PRO 'WAIT LIS?
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Manuel Alvarez-Campana
3 months ago
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POST COMMENT...
Interesting. We've been something similar in our University
Campus in Madrid.
We have deployed a sensor network (70 nodes) distributed on
a 5.5 Km2 area
which have been collecting data since March 2015.
You can have a look to our dashboard to see some results
(both real-time and historical data),
http://ceiboard.dit.upm.es/dashboardfwifi_pub
Best regards
Prof. Manuel Alvarez-Campana
Universidad Politecnica de Madrid
Newer Older
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