Ubiquitous Computing for Big Data Insight: Helpful Tool or Privacy Breaker?

The next generation of devices able to access to the Internet and the Web may not be characterized by computers, smartphones, tablets or appliances designed for this specific purpose. Every common item of daily life might be able to connect to online services whilst people using them are completely not aware of it. The Apple Research center study describes the future of computing and of people interaction in a networked society rising a new computing concept. The Apple vision is briefly explained by Frank Casanova, who says:
”The Concept of computers as things that you walk up to, sit in front of and turn on will go away. In fact, our goal is to make the computer disappear. We are moving towards a model we think of as a ’personal information cloud’. That cloud has already begun to coalesce in the form of the Internet. The Internet is the big event of the decade […]. We’ll spend the next 10 years making the Net work as it should, making it ubiquitous.” [Frank Casanova].
This new concept has been named by Mark Weiser as Ubiquitous Computing (UC). The original idea can be summarized as follow:
”Dwelling with computers means that they have their place, and we ours, and we co-exist comfortably. Unfortunately, our existing metaphors for computers [are] inadequate to describe the ’dwelling’ re- lationship. Over the next twenty years computers will inhabit the most trivial things: clothes labels (to track washing), coffee cups (to alert cleaning staff to moldy cups), light switches (to save energy if no one is in the room), and pencils (to digitize everything we draw). In such a world, we must dwell with computers, not just interact with them.” [Mark Weiser, 1996].
The aim of UC is to move the computation in many small, embedded and spe- cialized devices present in our dynamic environments while remaining totally trans- parent to the users around. Ubiquitous concept is a new revolutionary paradigm that will widespread information systems inside our society, creating a cutting-edge networked society.
To understand possible candidates of UC devices, it may be useful to mention Dick Rijken’s own vision of UC:
”It can drag interactivity away from technological fascination and wizardry into the realm of human experience and action. What is be- ing designed is no longer a medium or a tool in the traditional sense, but something far more intangible, embedded in a continuously chang- ing environment where everything is connected to everything else.” [Dick Rijken, 1994.].
In short, a product to be defined an UC product has to be present everywhere, to be small and to be aware of the context where he is located. These three char- acteristics permits the user to interact with the devices with a complete freedom of movement and without technical knowledge dependency.
All of this is sustained by the industry interests in ubiquitous applications, their business opportunities and the growing of related technologies such as: Internet of Things, Smart Spaces, Sensors Networks and so on. Yet, there are some limitations due to the hardware costs, maintenance and low scalability, but also and foremost for the distrustful public opinion regarding the massive adoption of these new technologies.
This implies developers and manufacturers of ubiquitous technologies to care- fully consider the social and ethic impact, which may negative influence the busi- ness model and market value of the product. Nevertheless, UC technologies applied in a non-invasive manner can lead to new important instruments.
This essay is strongly concentrated on the treatment of huge amount of data, recently called with the name of Big Data. It will first give an idea of the size and the worth of these Data, then it will focus in deep on the Ubiquitous Computing concept as a new channel for data gathering and his impact in the society and for new business opportunities based on Customer Insight Data. Finally we will conclude with particular importance and carefully understanding of all the related privacy issues and proposed solutions.

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About Gianmario

Data Scientist with experience on building data-driven solutions and analytics for real business problems. His main focus is on scaling machine learning algorithms over distributed systems. Co-author of the Agile Manifesto for Data Science (datasciencemanifesto.com), he loves evangelising his passion for best practices and effective methodologies amongst the data geeks community.
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