Smart cities, self-driving cars, intelligent machines—the IoT market is exploding with “Things.” The ease with which they cross over from sci-fi to real life makes it look like a breeze, thanks in part to data engineers who do the heavy lifting behind the scenes.
In our previous posts, we discussed sensors and wireless communications—the two components that underpin the Internet of Things technology. Our current post looks at how these technologies take effect in real life and help make a difference to operations. Two of these cases deal with real-time location systems (RTLS) implemented in healthcare and logistics and the other with condition monitoring in wind farms. (more…)
The Internet of Things would not be the exciting prospect that it is without a key component – wireless technologies. These technologies are defined under various standards and protocols and choosing the right one depends on the context and the requirement.
Some IoT implementations require data to be transmitted over long distances, others short; some devices transfer small volumes of data, others large. Some are deployed in inaccessible environment and their life needs to be sustained longer. This diversity in requirements and devices necessitates different communication standards and protocols in different contexts.
Twenty eight years ago, the Internet took over the world by storm and turned it to the global village we know today. Enter the Internet of Things, and there are more sentient objects in that village—8.4 billion as per Gartner. Everything from industrial pumps and wind turbines to self-driving cars and household appliances now share the digital space with us. By 2020, their number is set to touch 20 billion.
The connected world may be shrinking by the day, but the digital universe is expanding at a mind-boggling rate. Organizations now handle data in the range of terabytes and petabytes. This data looks nothing like what RDBMS traditionally dealt with. New distributed databases, known by the umbrella term NoSQL, help in the efficient handling of this unstructured and scaling data.
Technology, the inveterate disruptor, is at it again. Granted, it’s always kicking up dust. But every now and then it coughs up something major, sending a shiver down the industry’s spine. So it is with blockchain, a distributed database.
Insurers are turning to big data analytics to strike a difference in the highly commoditized insurance market and improve risk management in the context of growing regulations. This move is helping the industry reap rich benefits across the value chain. In this white paper we examine some of the emerging practices in the Property and Casualty insurance sector particularly in relation to product pricing, underwriting, claims handling, customer relationship management, and reinsurance.