1. Big Data and Social Enterprise
By applying wireless sensor technology to humanitarian issues,
we can help empower social enterprises to play a significant
role in the industry and replicate similar solutions across a
broad span of global development challenges.

2. The Future of Big Data
The need for a unified system
The information Wireless Sensor
Networks (WSNs) are capable of
providing today is limitless. Big Data
has the tools and the infrastructure
to perform and be computed on an
advanced level. However, therein lies
the problem. How do we create a
system that would assist NGOs and
newly emerging companies in the
processes of taking visualization and
data analytics to a civilian level? The
necessity is not in the technology; it
is in the understanding. Actionable
data is accessible data, data that
does not require an entire
infrastructure in itself to understand.
Companies like Amazon, Google,
Microsoft, IBM and Apple already
have massive infrastructures in place
to support current and future growth
in Big Data. It is necessary to utilize
that engineering enterprise and
translate it into social enterprise. Our
goal is
to enhance the capabilities of the
engineering enterprise of data
analytics to fully encompass the
developing world. More people
have access to Wi-Fi and cellular
data than they do water (Fig 1) so we
address this factor by using it to our
advantage. Our next step is to
create the technologies capable of
connecting with pre-existing
networks, available and easy to use.
“More people have
access to Wi-Fi and
cellular data than
they do water”
The caveat is the juxtaposition
between creating an easily
accessible network and a secure
network.

3. consumption, street congestion and pollution. These applications are not even at
the pinnacle of their potential. So with that, we again see that, WSN’s access to
data is limitless. The ability to take a heat sensor, like Lumkani (Fig 2), that can
measure the rate in rise of temperature, to send an SMS text to employ the
necessary resources, is just the beginning of the end to mitigating shack fires in
South African slums and across the globe. Sensor networks are just beginning to
optimize and are not working at maximum efficiency yet. Our goal is streamline the
process of data collection, analytics and visualization to create an actionable
network resources that can be employed immediately without compromising the
security to ensure that systems remain as “Information Systems” and not
0
1
2
3
4
5
6
Mobile Phones Water
Fig 1. Access to Water vs Mobile Phones (in billions)
To enhance data visualization it is necessary to expand audiences, create devices
that have the ability to interpret and deliver a universally, understandable piece of
information. Take Siri for example, Siri allows users to pull from all over the internet
to answer a question as simple as, “What should I wear today, Siri?”. A device that
takes all the guesswork out of picking one’s daily outfit, by taking data from all over
the Internet, to provide one user friendly answer. Further, the city of Barcelona saves
close to $10 Million dollars a year by sending trash trucks to only empty trashcans
that are full and direct cars to parking garages with open spots to limit fuel
4.5 Billion 5.4billion
3 Billion 3.5 Billion
2015 2020
“Surveillance Systems.”

4. The limitation isn’t within the data, it is
within the locations we wish to employ
such groundbreaking technology. Big
Data is the space time continuum of
the future, the internet began by
easing the barrier of communication
across the globe. Big Data takes that
one step further; Big Data marries
communication and action,
consequently garnering appropriate
resources and personnel in solving a
problem halfway across the globe is
much more tangible.
.Detects fires via measuring rate of
rise in temperature
.Sends SMS to activate necessary
resources
.Sold at USD$8.50 (Cost Price)
3000 units distributed
across SA:
Johannesburg
Durban
Cape Town
3000
Detectors
protects
10,000or more from fires
Fig 2. LUMKANI

5. The developing world will be the breeding ground for some of
the most exciting and impactful applications of WSN technology.
Social enterprises across the globe are increasingly using WSNs
to create new and improved solutions for many of the world’s
most pressing development challenges, from monitoring the
“cold chain” delivery of vaccines, to detecting the arsenic
Global Development Challenges
Fig. 3: % of Urban Population living in slums, 2010
0% 100%
262Min South
Central Asia & 166M in
South Africa live in
informal settlements
7949Shack fires in
Cape Town in 2014, 20
deaths. Someone dies in
a shack fire every two
days.
“cold chain” delivery of vaccines, to
detecting the arsenic content of water
in Bangladesh, and optimizing crop
production in Kenya. Particularly
within the realm of humanitarian relief
work, the benefits of the real-time
infor
information that WSNs can gather and
store are enormous. Unlike traditional
sources of information, WSNs provide
organizations with information that is
untainted and immediate, which can
result in more efficient and effective
serv

6. being delivered to affected populations. As the
UN Broadband Commission for Sustainable
Development has identified, the high
coordination, self-organization, and research
capabilities of WSN technologies mean that
they will have the highest potential impact in
urgent developmental economy areas such as
natural resource management, healthcare,
energy, and disaster relief. With numerous
social enterprises - such as Nexleaf Analytics
(USA) (Fig. 3), SweetSense (RWA), and Lumkani
(SA) (Fig. 2) - already producing cost-effective
sensors at scale and gathering valuable data
from their WSNs, the lucrative opportunities for
WSN deployment are only bounded by the
unprecedented range of applications that we
can apply this technology to.
Fig. 3: Nexleaf Analytics ColdTrace
Uses Real Time Monitoring for
vaccines, cost price of less than $50.
As 38 percent of the potential $11.1 trillion annual
economic impact of IoT applications (by 2025) will be
in developing economies, many of which have acute
failings in a variety of sectors, we expect that future
lowlow-cost WSN
technologies will
drastically increase both
the profitability and
effectiveness of social
enterprise operations in
the developing world.
Despite the exciting possibilities
brought about by WSNs and Big
Data, significant challenges persist.
Inadequate human capacity and
barriers to consumer adoption are the
two big limitations to the use of WSNs
in social enterprise operations. In
terms of inadequate human capacity,
technical literacy is a major issue.
There are often not enough tech

7. technically literate people with IT skills in local
areas that have the capacity to implement
sensors, or to respond once a system signals a
problem. As such, social enterprises will have
to ask themselves how they intend on
providing the human or technical capacity
necessary to maintain and repair sensors,
especially if their target markets are in
remote areas. Barriers to consumer
adoption of WSN innovations will be
driven by two key factors: resistance to
change, and the costs associated with
sensors. People are often resistant
and reluctant to modify their behavior
to fit with new technologies, especially
if the initial learning curve of adoption
is very high. Deloitte cites the example
of one electrical utility company which
installed smart meters in millions of homes
in North America, expecting that
consumers would consult online dashboards
of monthly usage. Three years after the meters
were deployed, only 6% of households had
viewed the dashboard at all. Although the
newness of wireless sensors may deter
consumers; the costs associated with them may
prove a more significant barrier to adoption
than anything else. Although strides are
currently being made in making WSN products
cost-effective, the electrical and labor costs
associated with the sensors, connectivity
modules and the connectivity service can still
prove prohibitive for many populations within
the developing world (such as for individual
small shareholding farmers).
Inadequate
human capacity
and barriers to
consumer
adoption are the
two biggest
limitations to the
use of WSNs in
social enterprise
operations.
.38% in developing
economies
$1.1
Trillion
Annual Economic
Impact Of IoT
Applications (2025)

8. The profitability of a social
enterprise is dependent on the
complexity of their business
model. A complexity that is
measured in regards to the
degree of difficulty in operating
and managing a business
successfully. A social enterprise
is defined by a company’s focus
on the social good and the
common good and can be
seen in all business from for-
profit to non-profit to
corporate. Across the board,
the employment barriers
greatly affect social enterprise
financially. profitability of a
social
Social Enterprises
For-profit social enterprise business models tend to have an
easier time attracting capital, whereas non-profit companies
have to utilize ongoing fundraising strategies to maintain
standing. Other factors do however play into the profitability of
a social enterprise. The skills and training needed to optimize
the business model are significant game changers in its overall
success. A well-rounded, efficient team of employees can be
pivotal for any business models, whether it be social
For profit vs non-profit?
CVP: building the
social good and
the common good
For-
Profit
Non-
Profit
Cooperative

9. All that to say, there are still more costs to be considered
once the right team is in place. While it is easier for for-
profit social enterprises to allocate and attract capital to
acquire the resources needed to support the business
model, they often have conflicts within the realms of their
corporate social responsibility. The forward-thinking
companies want to embed sustainability into their daily
operations while still trying to make money.
Consequently, these social enterprises are not the only
people looking to gain a buck while still helping out. One
of largest limiting factors in data center development is
lack of required investment. At the end of the day, money
becomes the force driving away social enterprise and
keeping away Big Data development in developing
nations.
pivotal for any business model, whether it be social
enterprise-specific or a different industry altogether.
There are high costs associated with achieving this
optimization. In conjunction with the necessity for
enterprises to hire experts, they must also gather the
necessary resources for their company to function: Big
Data Center access and facilities.
Ultimately,
money is
the
force
driving
away
social
enterprise
and
keeping
away
Big
Data
development
in
developing
nations.

10. TEAM
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..
.
.
Charlottesville, Virginia, USA
Singapore
Hong Kong
Jarkata, Indonesia
Cape Town, South Africa
ASH LE Y
YAP
WILLSON
C H RIST IAN TO
AN D RE W
H UAN G
N ATALIE
E LSAWY
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