The Internet of Things Mentality

Aug 22, 2016 10:10:59 AM / by Brittney Borowicz posted in analytics, connected, developers, Edge Analytics, General, Internet of Things, IoT, Sensors


By Joe Duncan, Marketing

Whatever there is to be said about the development of connected devices in recent years, it is obvious that the attitude behind the Internet of Things (IoT) has been mostly visionary up until this point. Some products have had more success than others, but on a broad scale, the adoption of IoT tech has been a slow process. Many people still don’t know how the conceptual term “Internet of Things” could apply to their lives, and to some, the idea even appears trite and unnecessary. However, the buzz surrounding connected technologies cannot be disregarded due to the fact that more devices are hitting the market every month, with tech giants like Amazon, Apple, and Google leading the bunch with their respective platforms and hubs.

These products have definitely excited developers and consumers alike, as many have pointed out, and have accelerated the recognition of the Smart Home. The big question now is: “where is the IoT?” It would seem a bit presumptuous to say that we’ve arrived considering the strides that have yet to be made in adoption of devices, yet so many product headlines continue to read “the IoT is here.” The IoT is not an event or a bar to be reached, but the continuing interconnectedness of objects in our environment. So it’s no wonder that, in the early stages of IoT technology, widespread acceptance is still forthcoming. Developers should be more worried about continuing to search for progressive solutions and adaptations to the expanding platforms. One of the big areas for growth in IoT products has been widely referred to as Edge Analytics.

The “Edge” is a term that could easily be lost in the technical jargon of networking capacities, but it is a simple idea: the sort of computations and data sorting that used to require a server, can now be accomplished on the connected device itself. “A simple example is monitoring a camera. If you think about a video camera set up to count cars at the intersection of two roads, you don’t really need to watch video of the cars going by, you only want the count and timing of cars.” (Forbes) Moving analytics closer to the Edge provides a number of benefits. First, bandwidth costs money, and the growing amount of data that will be sent via sensors and other devices is not going to make this expense any cheaper. Developing a product that can monitor and synthesize information valuable to its local functionality will be much better off than the product that will have to send the data away before it can act. This is the second benefit of moving toward the Edge, and this Idea has been called the latency of a product, or its time to action. Products that can act quicker, and with a higher data reflex will be the most progressive in their market. “You no longer need to land the data for analysis; you can now take analytics to the data, while it is in motion” (SAS)

Depending on the application, developers may want to consider a number of different options when thinking about how to move analytics closer to the Edge with their products. Gateways have also become incredibly powerful, and have taken on a number of characteristics that used to only be present in servers. In all cases, the ability to analyze and respond quickly to sensor data is at the heart of the IoT. Connectedness is given more power when it is able to respond in a cohesive and accelerated way to the information present, and acceptance will rise with the recognition of this capacity.

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The Internet of Things: Changing Big Data Analytics

Jun 13, 2016 2:14:53 PM / by Brittney Borowicz posted in analysis, analytics, Big data, big data analytics, Consumer, data, data-gathering, device, General, internet, Internet of Things, IoT, Nathan Rockershousen, outscale, technology, Will Hayles


By Nathan Rockershousen, Technical Writer

The collection of data through large datasets is becoming increasingly popular among businesses. The prominence of the Internet of Things (IoT) has created a surplus of data that is now being utilized for statistical analysis. Big data analytics and IoT devices are interconnected in the sense that IoT devices enable companies to access large quantities of information. This information is then used to help gather details about the consumer and the product. IoT technology is transforming the collection of data and the information that the data provides allows for the development of more advanced IoT devices.

As more devices become connected to the internet, there will be more data that companies will be responsible for sorting through. Once IoT technology matures and becomes widely adapted, big data analytics will no longer be optional. The analytical value in having access to large datasets that are continuously updating can be substantial for any organization. Not investing in big data technology that can sort through the immense quantity of the data gathered will be a major hindrance in maintaining IoT devices. Will Hayles, a technical writer for Outscale, reinforces this concept by stating, “Without the proper data-gathering in place, it’ll be impossible for businesses to sort through all the information flowing in from embedded sensors.” This essentially means that the inability to utilize data efficiently will create obstacles in terms of competing with other IoT-based companies as analytics can provide insight into consumer wants and needs.

The integration of IoT technology and big data has the potential to create higher expectations for technological innovations. Simply being able to collect data from IoT devices will not be sufficient. Companies need to implement some sort of analytical platform that can sort through the vast amount of data gathered. Big data analytics and the IoT are interdependent. When organizations are able to access information about their products, they are able to immediately update the technology to provide new and improved content to users in addition to being able to improve any issues. Essentially the influx of data is creating a higher standard for technological innovation. Any business that does not wield the power of big data analytics will quickly lose relevance due to an inability to recognize the potential for improvement that is provided by collected data.

The adoption of big data analytics within the corporate environment is inevitable as wirelessly enabled devices begin to play a larger role in the consumer lifestyle. This change will not happen overnight, but it is crucial that organizations start to develop the analytical tools necessary to manage vast amounts of data. This means that the infrastructures of many businesses will need to be modified in order to compensate for the changing nature of IoT technology.

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Data Analytics and the Internet of Things

Aug 31, 2015 8:17:29 AM / by Brittney Borowicz posted in analytics, Big data, connected devices, data, data security, General, Internet of Things, IoT, manufacturers, pedometer, security, Sensors


One of the major promises that discussions of the Internet of Things (IoT) have put forward, is the advances to be made in consumer insight. The idea is that sensors and connected devices can send data on an open loop back to the manufacturer for analysis. This process would presumably secure many advances in a wide variety of things; not only would companies be able to understand their clients, but sensors may even be able to tell us more about the product in general. For example, pedometers on livestock have given scientists more knowledge about when cows are in heat, allowing for a 66% increase in insemination rates.

Many have referenced discoveries such as these to be the real goldmine of the IoT. Using big data analytics, manufacturers could generate the type of insight that could propel future developments. However, the concept of big data analytics is still a bit fuzzy to most people. A lot of the general knowledge of analytics is overshadowed by the half-belief that information is fed to a group of ancient mystic palm readers who come up with practical applications for the infinite mass of soundbite data. In reality, the sorting mechanism used to interpret the data from connected sensors is rarely earth-shattering and could even be accomplished on a closed loop. This is critical to keep in mind, especially as companies make decisions regarding data security.

Read more at ReCode.

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