Internet of Things (IoT)

Internet of Things (IoT) and Big Data are growing as at astronomical rate and this can open new horizons for business in terms of new business models, products design, intelligent operation and improved customer services – which is why they occupy places at or near the peak of analyst firm Gartner’s most recent Hype Cycle for Emerging Technologies.

Source: Hype Cycle of Emerging Technology

As products are becoming increasingly sophisticated, so does the swathe of data produced through these devices. – the connected smart car, smart mobile, wind turbines, connected trains. These devices in turn have potential to provide us with real time data – this data is only meaningful, once it is transformed into meaningful information to make decision. Internet of Things (IoT) is interconnected devices providing real time data which enables businesses/customers to process this data in order to improve their existing services and providing an insight on how to further expand to newer service lines.

Companies are aware, providing products/services might achieve profits, but providing continuous betterment in services is also highly pivotal to gain an edge on the competitor. IoT can be used to provide smarter solutions and help maintain better relations with customers directly helping in growth of operators.

Big Data on the other hand comprises of 4Vs: volume, variety, velocity and veracity – comes in large volume in form of  structured and unstructured data, arrives at (often real-time) speed (velocity), and can be of uncertain provenance (veracity).

Such data is unsuitable for processing using a traditional SQL-queried relational database management system (RDBMS), which is why a host of alternative tools—notably Apache’s open source Hadoop distributed data processing system and various NoSQL databases and a range of business intelligence platforms have evolved to process such data.

Fig: Hadoop Vendors for various stages                                       Fig: Typical Bid Data Architecture

IoT Data Processing:

It has been recognized from the onset that analytics technologies are critical to the swathe of streaming source data into informative, aware and useful knowledge – but how do we analyze data as it streams nonstop from sensors, devices and traditional sources?

In traditional analysis, data is stored and then analyzed. However, with streaming data, the models and algorithms are stored and the data passes through them for analysis. This type of analysis makes it possible to identify and examine patterns of interest as data is being created – in real time.

So before the data is stored, in the cloud or in any high-performance repository, you process it automatically. Then, you use analytics to decipher the data, all while your devices continue to emit and receive data – with advanced analytics techniques, data stream analytics can move beyond monitoring existing conditions and evaluating thresholds to predicting future scenarios and examining complex questions.

Summary:

It is expected 20.8 billion will be connected globally as IoT  – as result we expect to see major cyber security and safety issues . Another key issue is the cost factor which the end users have to bear for these products.

The Internet of Things and big data share a closely knitted future. There is no doubt the two fields will create new opportunities and solutions that will have a long and lasting impact.