IoT (Internet of Things) will go nowhere without cloud computing and big data analytics

This is part of Bill’s series of posts on the Internet of Things (IoT) topic

In my last post on this topic, I discussed how advances in connectivity and networks and in sensor and microprocessor design are helping to make the future of the Internet of Things a reality. In this post, I’ll cover two other important technology trends that are enabling the Internet of Things: cloud computing and big data/analytics.

Cloud computing

Cloud computing, just a buzz word five to six years ago, has ushered in a new way of computing that leverages networks and operating software to provide virtually unlimited computing capability whenever it is needed – and that includes Internet of Things applications.

Image credit: IBM
Image credit: IBM

Businesses are starting to rely more heavily on cloud environments. Gartner has stated that Cloud Computing will garner the bulk of all new spending on IT by 2016 and that spending on public cloud will reach $250 billion by 2017.   In fact, enterprises and government agencies of all sizes are shifting from small-scale application deployments to hosting and running large, mission-critical operations in the cloud that are secure and open.

Image credit: IBM
Image credit: IBM

New public and hybrid cloud and mobile-based cloud platform technologies are providing companies with an easy way of connecting traditional enterprise-based information systems to both private and public IoT-enabled devices. This capability will allow enterprises to quickly and economically build Internet of Things based sense and respond systems that can scale up or down based on changes in the environment and transaction level.

In addition, new cloud-based developer services, like the IBM Internet of Things Foundation, are providing developers with the ability to quickly and easily extend an Internet-connected device such as a sensor or controller into the cloud, build an application alongside the device to collect the data and send real-time insights back to the developer’s business. At the same time, developers can quickly build mobile apps that act as remote controls to connected devices.

Big data and analytics

Image credit:  IBM IBV
Image credit: IBM IBV

As I’ve stated in my previous post, the Internet of Things will require improved analytic capabilities to make sense of all the data coming in. It is useless to have all that data if there is no capability to quickly store, manage, and analyze data for insights and decision making. In the past few years, we have seen significant improvements in big data tools and analytics technology and that is laying the groundwork for processing the data generated by large networks of devices and sensors.

Big data tools: Big data tools for managing and analyzing the vast data sets generated by swarms of sensors are rapidly maturing. Emerging open source software frameworks like Hadoop, a data processing framework and distributed file system, promote efficient analysis of ever-growing data sets being generated by the Internet of Things. Expect more advancement in big data tools like Hadoop in the coming years that are specifically designed to manage and leverage Internet of Things generated data.

Image credit:  IBM System X
Image credit: IBM System X

Analytics: Also maturing are real-time and predictive analytics systems, which will be the most crucial part of the Internet of Things ecosystem.  These analytic systems will need to transform data into dashboards, insights, and recommendations for decision makers. There is tremendous opportunity for new data to be collected that will enable improved customer experiences via new engaging applications. As an example of the announcements in this area, IBM recently teamed up with US carrier AT&T to help cities and utilities analyze large volumes of data by extracting it from meters, cameras and sensors.

In summary, the adoption of cloud computing and big data/analytics is creating enormous opportunities to connect with new types of devices and ‘things’ at the edge of the enterprise. This will allow developers to implement new types of applications, new types of workflows and new value propositions for enterprises. These devices and services are increasingly being stitched together better with online services that will enable the Internet of Things applications of the future.

At the same time, there are challenges to the accelerated adoption of the Internet of Things, and that will be the topic of my next post.


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