Trends such as artificial intelligence and automatic learning are beginning to be integrated into the most advanced IoT platforms thanks to the incorporation of sensors capable of understanding, adapting and operating on their own.
The Internet of Things (IoT) is already present in many facets of our lives and in environments that we continually relate to like cities, buildings, industries, homes or vehicles. In all cases, a new generation of more intelligent and autonomous sensors with which the processing capacity and the possibilities of the IoT devices are being introduced on the market.
It is precisely the IoT Solutions World Congress (IoTSWC 2017) that identifies some keys that are marking the adoption of these new sensors that are merged with microprocessors and that will produce in the short term a huge qualitative leap in the IoT ecosystem. First, they stand out for their efficiency and safety. In this sense, scientists Jesús Pacheco and Salim Hariri, members of the National Science Foundation Center for Cloud and Autonomic Computing of the University of Arizona (USA), defend the increase of the efficiency of the sensors through the integration of IoT with fog and cloud methodologies, which not only provides the processing potential that such environments require, but are also capable of building a new ecosystem of affordable and cost-effective services.
US IoT security expert Roopak Venkatakrishnan calls for the use of redundant sensor mechanisms to detect anomalous safety-related responses. Venkatakrishnan argues that systems based on redundancy tests are more robust and effective against sophisticated cyber-attacks, compared to the classical reactive defenses systems that work when attack methods are known.
Another of the outstanding features of these intelligent sensors is the integration of microprocessors, performing autonomous functions of calibration and diagnosis. This fusion between the sensor and the signal processing functions is redefining the sensor landscape, which has traditionally been relegated to discrete elements such as thermocouples and accelerometers. Thanks to this, an intelligent sensor can make use of the local computational power to process and interpret the data in isolation; make decisions based on measurable physical parameters; and establish the relevant communication. What’s more, these types of sensors make decisions about what data to process locally and what others are to refer to the cloud through the IoT infrastructure.
And from there, the sensors will have capabilities of understanding, learning, prediction, adaptation and potential to operate autonomously. “Systems can learn and change their future behavior, leading to the creation of smarter devices and programs. In parallel, the combination of computational power, advanced algorithms and data sets that arrive massively to feed these algorithms is giving birth to a new era “, concludes David Cearley, vice president and partner of the consulting firm Gartner Research.
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