Tuesday, May 01, 2012
The “Internet of Things” is rapidly becoming a very real phenomenon. IBM has one of the most aggressive outlooks for connected devices, predicting
one trillion by the year 2015. These devices, which will take advantage of advances in miniaturization, processing power, and networking capability, will be able to collect vast amounts of data for analysis. From smart cities
to smart homes
, from applications in weather
to applications in healthcare
, these networks of sensors and devices are poised to change our understanding of the world around us and our ability to make decisions.
The power of these networks lies in the fact that the sensors are able to communicate with each other and in many cases learn from the data they are exchanging. The fields of machine-to-machine (M2M) communication and machine learning focus on these abilities, and as the technology becomes more affordable and accessible, the opportunities for those with expertise in these fields will grow dramatically.
Machine-to-machine communications is not exactly a new trend. Technically, these communications can occur over a wired network, so the history starts with primitive sensors and circuits in the 19th
century. More commonly though, the data is transferred wirelessly. Telemetry systems using private radio frequencies are well established in areas such as meteorology, space exploration, and retail, but the ubiquitous nature of cellular and Wi-Fi networks have lowered the barrier for implementing an M2M system.
If the system goes beyond simple data gathering and performs some additional function, the ability to learn from the data and improve automatically can be a key feature. Machine learning has always been a hot topic in the field of artificial intelligence, and it has reached down to the consumer market in applications such as speech recognition software and especially the algorithms that drive search and recommendation engines. Stanford University offers a free online course
in machine learning thanks to the widespread interest in the topic. Through the increased computational power that can be packed into sensors and the connection to high-speed networks, wireless sensor systems can have the same capability to receive and act on feedback that was previously only available to larger, self-contained systems.
Enterprises are becoming more dependent on technology in ways that fall outside a traditional IT definition, and M2M communications is a prime example of an area where technology-savvy third parties can provide assistance. The installation and support of wireless sensor networks crosses many disciplines, including the sensor hardware, the wireless/cellular network, storage, and software for analytics or monitoring. Building out a system is likely to involve multiple parties, and a solution provider with experience in partnering with other specialists can drive a project and remain the focal point for support.
CompTIA’s market research department will be exploring the topic of Big Data in more detail this summer, and as part of that study we will be bringing specific focus to M2M and machine learning. If you would like to provide input on the study while it is in its planning stages, contact us at email@example.com