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 Data Analytics and the Internet of Things

Data Analytics and the Internet of Things

binary-code-63529_640Guest Post by Abhik Banerjee – Chief Engineer at Samsung India Software Operations.
It has often been said that the best technology is the one that disappears. Indeed, Jack Dorsey, the Twitter co-founder, said so sometime not so long ago, including Twitter itself in the list of such technologies. The Internet of Things hopes to change this aphorism by starting from the invisible. The Internet of Things envisions a world where everyday objects are connected to the internet. At its best, it envisions a world where ubiquitous computing is a reality, i.e. computing becomes so widespread that it truly becomes invisible.
Ever since its birth 24 years ago at CERN, the internet has revolutionized the way the world interacts (indeed, it must be said, still just over a third of the world’s population). In addition to make it easier for people to connect, the internet has also made all forms of information available at fingertips. However, as the internet gains in maturity, it has become increasingly evident that the same information, the easy access to which has been a source of fascination up until now, is not taking on a more overwhelming role, making it more difficult to manage and make sense of. The advent of the Internet of Things means that the complexity of this task of managing data will grow manifold. In the rest of this chapter, we will look at different aspects of our lives where Internet of Things is expected to play a major role in the immediate future and the role of data analytics therein.
Internet of Things
The first stop in our tryst with data and the Internet of Things does not concern objects, but rather inevitably, people. Though historical examples abound, crowdsourcing has caught the imagination over the past decade, thanks to a heady combination of online tools such as Twitter and Wikipedia and the popularity of smartphones. The role of data analytics in this space can be particularly well understood when looked in context of events shaping human society, whether natural or man-made.
One such event was the 2007 Kenyan presidential election, which foresaw the birth of one very significant crowdsourcing initiative, Ushahidi. In the midst of widespread allegations of electoral manipulation and violence, Ushahidi provided a visual platform to represent eyewitness reports obtained using emails and text messages by plotting them on a map, thereby help identify pockets of trouble. In the years since, the platform has been used around the world for a variety of causes, including large scale natural disasters such as the Haiti earthquake of 2010. A similar kind of visual map helped map radiation levels in the aftermath of the Fukushima nuclear disaster in Japan in 2011. In this case, however, restricting the data to visual reports of eyewitnesses could not have been useful alone as they don’t contain details of the radiation levels in the surroundings. Instead, digitized readings from geiger counters, which measure radiation levels, were the internet using a platform called Pachube (since renamed to Xively), allowing for monitoring of the spread of radiation.
Beyond singular events such as disasters, however, analysis of data obtained from mundane, everyday activities can help provide services that affect daily life positively. We start off with information provided by humans about daily activities. Popular social networking websites such as Facebook, Twitter and Foursquare provide a steady stream of data pertaining to the movement patterns of people. This includes not just the absolute location coordinates of people movement but also information about the routes they take and the places they visit. Just this information alone is enough to power a range of services. Individual business operators can trigger personalized services for their customers.
For instance, a departmental store may seek to enhance the shopping experience based on its knowledge of when a customer is expected to visit next for his/her monthly grocery shopping. At a personal level too, a user’s activity pattern can be mined to provide personalized recommendations, such as the best route on the way to work and back or even reminders for bill payment. Indeed, some services such as these are already in place. Analysis of data obtained from a large set of users can help glean additional insights for businesses.
As an example, consider a popular amusement park which has just introduced a new set of attractions for the festival season. The park operator would naturally be interested in identifying the customer response as quickly as possible. A quick look at the statistics for how long people spend at each ride and how often they return would allow the operator to make the best adjustments.

Internet of Things

Source: PC World

An important area which expects to be influenced by the Internet of Things is transportation systems. The same set of information highlighted above can be used for obtain traffic information for busy junctions as well as subway routes. Not only can individual users use this information to decide on their routes, but it can also allow the authorities to plan accordingly. Frequency of trains for a particular subway line can be increased based on the number of user checkins at stations.
Beyond just crowdsourcing however, traffic prediction and route planning accuracy can be improved by making use of information obtained from devices deployed on roads. In recent focus, for instance, has been IBM Africa’s new initiative for predicting traffic patterns using data obtained from CCTV cameras.The service allows citizens in Nairobi to get route advice by sending text message queries. However, what is really interesting is the fact that the service runs on visual data gathered from just 36 cameras installed around, thereby illustrating the extent to which data analytics can impact. The benefits are not just limited to route planning, though. In Santander, Spain, a network of sensors help improve parking experience for cars by identifying suitable free parking spots.
In addition to traffic systems within a city, the Internet of Things is expected to shape up a diverse range of transportation systems. Aviation systems, for instance, seek to improve passenger experience by making use of data from different parts of an airport.  Further, the efficiency of flight management systems can be improved by better coordination among all divisions. The latter is crucial for cargo delivery where it is crucial to both coordinate and track vehicle fleet. A high level of coordination required in emergency response scenarios can also be solved by correlating sensor information which detect emergency situations to the actual response systems.
While we have seen the applications of the Internet of Things to a few selected areas above, in reality they are expected to impact every facet of life. Many such applications are likely to be truly invisible, as they involve systems that typically operate in the background. For instance environment monitoring systems can involve deployment of air quality monitoring sensors, data from which is used to identify areas of high air pollution and subsequently take appropriate measures. They can also be used for early detection of potential natural disasters such as forest fires. Further, sensor based systems play a crucial role in agriculture by providing crop monitoring data.
Lastly, we take a look at how data analytics and the Internet of Things is set to shape the personal space. The number of devices that operate within an individual’s personal space is set to grow manifold not just because of the purported explosion of wearable devices but also due to the fact that everyday devices will join the connected world.
Thus, in addition to the smart watches, glasses and health bands that will be at every beck and call, household objects such as the coffee maker and even the switchboard are set to act as network components. What this means is that, at the end of day’s work, one will be greeted at home with everything from a steaming cup of coffee to a recommendation for the late evening jog.
Abhik Banerjee
Chief Engineer at Samsung India Software Operations

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