All too often in technology, we see concepts with real possibilities go stupid on us. Lately many of the key concepts have doubled down on stupidness, departing so far from relevant market benefits that there’s little hope of success. IoT, probably the most hyped of all technology concepts in recent times, has surely had its own excursions into the realm of stupid, but unlike many tech notions it seems to have a chance of escaping back to reality. You can see useful points being recognized, and it’s not too late for IoT to realize its potential.
The notion of a literal “Internet of Things” where all manner of sensors and controllers are put online to be accessed, exploited, and probably hacked by all, is one of the dumber excursions from a value perspective. The notion that an IoT strategy is a strategy to manage the devices themselves isn’t any better. From the first, it should have been clear that IoT is a big-data, analytics, and cloud application, and that it has to first exploit those sensors already deployed on largely private networks, often using local non-IP protocols. Now we’re seeing signs of a gradual realization of what the real IoT needs to be.
Startups in the IoT space have provided some support for data storage and analytics for well over a year. A Forbes article summarizes some of the key players in the space, but if IoT is a potential market revolution then startups are really selling themselves and not their technology. IoT adopters will generally want to bet on somebody with a big name, and that’s particularly true of network operators looking for a realistic IoT service strategy.
In November of last year, I blogged about the GE Digital Predix platform, which as I said was the first credible IoT story from a major provider. With strong analytics and a good strategy for capturing current sensor data, Predix has all the pieces to be a universal IoT framework, but the company has stressed “industrial IoT” rather than the universality inherent in its platform. One thing the breadth of Predix may have done is to encourage other IoT vendors to focus their efforts on specific applications in either a horizontal or vertical sense.
One example of focus is addressing what many IoT users would see as the high first-cost barrier to IoT applications. The cloud is a natural heaven for a logical ease-into-IoT model, and so it’s not surprising that cloud providers have IoT service offerings:
- Amazon, the cloud leader, has an IoT offering that focuses on a unified model for device and cloud applications and facilitates the integrated use of a variety of “foundation services” hosted by AWS. Their approach is more development-centric than productized.
- Google has a streaming and publish/subscribe distribution model that adds predictive analytics and event processing to IoT, all based on Google’s ubiquity as a cloud provider. Their Cloud Dataflow programming model may be a seminal reference for both batch and streaming IoT development.
- Microsoft offers both premises tools for developing IoT applications and Azure cloud tools. They also integrate Cortana capability with inquiries and analytics, and they’ve won some very public deals recently.
- Oracle offers its IoT Cloud Service, which focuses explicitly on the two key truths about IoT—you have to exploit current sensors connected through legacy private networks and you have to focus on data storage and analytics.
- Salesforce’s IoT Cloud extends sensor and analytics concepts to websites and other customer information, and offers event triggering of cloud processes. The focus, not surprisingly, is on CRM but it appears that broader in-company use would also be possible.
- Operators like AT&T and Verizon have IoT services that focus on connectivity, but AT&T also provides industry-specific integrated solutions.
Then, back in May, HPE talked about its IoT model in “platform” terms, which is how the media and market is now distinguishing between the sensor-driven IoT nonsense and the more logical application-and-repository concept. The HP story had an unfortunate slant in its title, in my view: “Hewlett Packard Enterprise Simplifies Connectivity Across the IoT Ecosystem”. The announcement does contain device and connectivity management elements, and the title tended to focus everyone on that aspect. But HPE also provided a repository, data conversion, and analytics platform vision that should have been the lead item. HPE is also partnering with GE Digital to power the Predix platform, which may suggest the company wants to be an IoT host for multiple software frameworks.
The most recent announcement is from IBM and Cisco. The companies have agreed to provide Cisco hosting of Watson analytics so that event processing can be managed locally, making control loops shorter. The move is not only potentially critical for both Cisco’s and IBM’s IoT differentiation, it’s an illustration that one of the key values of IoT in process management and event handling would best be supported by functionality hosted close to the sensors. This explains why so many cloud IoT stories are gravitating toward complex event processing, and it also illustrates why IoT could be a very powerful driver for NFV. Data centers close to the edge could host IoT processes with a shorter control loop, and that could help justify the data center positioning. Edge data centers could then host service features.
Cisco’s ultimate IoT position could be critical. The company has, in the past, been dazzlingly simplistic in its view of the future—everything has to come down to more bits for routers to push. You could view complex-event-process (CEP) IoT that way, of course. On the other hand, you could view it as an example/application of “fog computing” or the distribution of intelligence across the network. The latter view would be helpful to Cisco, IBM, and IoT overall, and given that Cisco has recently had some management changes that suggest it’s moving in a different direction than Chambers had taken it, perhaps there’s a chance we’ll see some real IoT insight and not just another report on traffic growth.
Insight is what IoT is really about. We could expect to capture more contextual data from wide use of IoT if we could dodge the first-cost problems, privacy issues, and security challenges of the inherently destructive model of “everything on the Internet”. This is a big data and analytics application in one sense, complex event processing in another sense, and that’s how IoT has to develop if it’s going to develop in any real sense. At some point, some platform vendor is going to step up and frame the story completely, and that could put IoT on the fast track. Wouldn’t it be nice for some “revolutionary” technology to actually revolutionize?