The Internet of Things (IoT) may be barely off the ground, but developers are already looking for ways to imbue the technology with high degrees of intelligence.
On one level, an intelligent IoT is a reason unto itself given that the scale and complexity of the data environment is beyond the capabilities of today’s management tools. But ultimately, the expectation is that much of the IoT will govern itself, and that includes the basic interactions between systems and users.
Zebra Technologies’ Tom Bianculli gave eWeek a good overview of all the ways in which intelligence is likely to affect the IoT. From the intelligent enterprise itself, capable of dynamic data streaming, real-time analytics and self-managing applications, to advances in health care, transportation, retail and virtual every other industry, the intelligent IoT has the potential to revolutionize the way we live, work and play. And this will certainly wreak havoc on today’s business processes, leading to new industry titans that tap into the power of intelligence to provide goods and service more reliably and at a lower cost basis.
The key to all of this is the analytics platform that will gather reams of sensor-driven data and make sense of it for the enterprise, says Accenture Analytics’ Gavin Stephenson. After all, he notes, the IoT will generate a lot of unstructured data, but without the ability to analyze it all, and at a very fast pace, it simply becomes a monument to wasted effort. But intelligent analytics is not simply a tool to be deployed, but an architectural construct that must be built into the very fabric of the IoT – from the centralized data facility to the user application. Not only will this take time to implement, but it could be a while before all the cogs in this giant analytics machine are working in tandem.
Indeed, says Fujitsu Chief Architect Cheng Jang Thye, one of the top misconceptions about intelligence is that, like a traditional system, it starts working exactly the way you want it to right out of the box. But the very reason we call it “artificial intelligence” is because it has the capacity to learn, which means it will take some time for any intelligent platform to analyze a given process and start making decisions based on available data. Like a thinking human, AI needs to be trained not just how to do a job, but how to do it well and within the boundaries of legal and ethical behavior.
The experiences of field service software developer ServiceMax offers a good template for what others should expect from intelligent systems, says ZDNet’s Bob Violino. While the technology shows a lot of promise in optimizing work processes and enabling field techs to complete jobs quickly and with a higher degree of customer satisfaction, it also requires a fair amount of training to get both humans and machines to work together. Any computer-driven process, after all, is governed by the quality of data it receives, and this can be a challenge for even the most advanced system as it navigates through numerous steps across multiple human- and machine-oriented functions like dispatch, back-office communications and mobile device management.
Ultimately, intelligent systems will provide entirely new levels of data utilization and service delivery, but experts caution that nothing is fool-proof. As with humans, mistakes will be the product of inaccurate information, miscommunication, and a general lack of knowledge regarding outcomes and expectations.
The IT industry has chosen “intelligent” and “smart” to describe this new class of technology, but they are by no means perfect.
Arthur Cole writes about infrastructure for IT Business Edge. Cole has been covering the high-tech media and computing industries for more than 20 years, having served as editor of TV Technology, Video Technology News, Internet News and Multimedia Weekly. His contributions have appeared in Communications Today and Enterprise Networking Planet and as web content for numerous high-tech clients like TwinStrata and Carpathia. Follow Art on Twitter @acole602.