Big companies are stepping up.  This week at IBM Corp.’s World of Watson show, the company is putting its weight behind big data to drive into the IoT marketplace. So are lots of competitors such as Amazon Web Services, Microsoft Azure, Oracle Corp. and a slew of new startups.

In hopes of making more sense of the IoT landscape, Wikibon Research published a recent reporting breaking down the key segments and how to deal with IoT data.

Segments of the IoT market

Personal IoT

Smart phones, smart ­cars, entertainment, location, travel, wearables, etc.

Home IoT

Smart meters, security and access control, smart appliances, health & safety, etc.

Government IoT

Federal, state & local government: criminal justice, internal security, traffic management, emergency response, etc.

Health IoT

Smart equipment, home health, electronic medical records, provider and payor applications,  etc.

Small Business IoT

Asset management, smart retail, customer management, inventory, security, health & safety, etc.

Office IoT

Building management: security and access control, equipment management, utilities management, maintenance, etc.

Industrial IoT

Plant operations, equipment maintenance (predictive and preventive), vehicle and fleet management (aircraft, trucks, shipping, trains, etc.), warehouse operations and inventory management, site health & safety, security and access control, etc.

My Angle

It will be very difficult to justify big data projects as security concerns will put efforts on hold. Another issue is that if all the data is extracted and sent to the cloud, the cost and elapsed time for data transmission is likely to be prohibitive, and the results delayed and reduced in value.

Some of the smartest engineers working on IoT are using distributed data analytics at big data centers, and extracting small amounts of data for further analysis in the cloud. Connected devices and industrial projects can also turn on specific filters to save additional data at the edge of the network for processing and onward transmission of results.

What about security in IoT?

What can be done is not easy, but according to Wikibon, companies can rethink how to deal with IoT. Connecting systems to share information around big data is something Splunk is doing. Security software that has native big data capabilities, native in devices that send notifications for any vulnerability activity. Cloud-based software to manage scaling agile software development practices as hackers tend to use holes in new software to find entry points from IoT devices. Even last week, Dave Vellante reported on theCUBE that IoT devices are shipping with default passwords increase the scale of potential hacks.

Digital business goals require greater cooperation and coordination of modern technologies and organizations. To extract the maximum value from big data it will need to be streamed, reduced and processed locally. IoT projects should focus primarily on giving value to the connected business processes. Value of data can be processed and delivered to upstream parties who pay for it, subject to careful review. Big data projects will be designed with distributed big data analytics combined with hybrid cloud services.

Most importantly, companies need to find a cloud and big data partner whose products are state of the art, where security is designed into the overall plan from the start.

Chart provided by Wikibon