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Streamlining IoT and Cyber Physical Systems

As technology grows increasingly complex, so do our ways of dealing with it. A perfect example of this relationship is known as the Internet of Things (IoT): the system that provides network technology in regular objects (such as your phone, car or home). Also known as cyber-physical systems, the Internet of Things combines the untouchable concept of coding with the very real objects that make up our daily lives. Unfortunately, most manufacturing systems are not designed to handle cyber physical systems. This hindrance has provided a large stumbling block for the technology’s advancement — until now.

Scientists from numerous universities across the countries have joined together to improve the Internet of Things and make cyber physical systems more streamlined and effective. According to their first joint paper, the real problem with these systems is their complexity: engineers must wrangle with both physical and digital aspects, to say nothing of the fallibility of human users.

A better design system would help things enormously, but the real focus must be in changing how people perceive the IoT:  it’s not two systems joined together, it’s a whole new form of technology. Until that is accepted, it will be a serious challenge to address the issues and concerns plaguing cyber physical systems. Users and engineers will end up only taking on part of the problem, instead of facing the whole thing head-on.

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A Dash of Maxwell’s: A Maxwell’s Equations Primer – Part Two

Maxwell’s Equations are eloquently simple yet excruciatingly complex. Their first statement by James Clerk Maxwell in 1864 heralded the beginning of the age of radio and, one could argue, the age of modern electronics.

Another concern the scientists looked at is cyber-security. They insist that security measures must be built into the base level of the designs, instead of added on at a later date. So how do we manage to protect the digital and physical aspects of the IoT? Researchers believe the answer lies in big data, which combines model-based design and data-based learning.Figuring out how to improve the register-transfer-level (RTL) design flow is an additional factor in making sure the IoT runs smoothly — if scientists could work out how to mimic that methodology in cyber physical systems, the results would be astounding.

How do we achieve these lofty goals? According the experts the secret lies in improving the design process itself. Human and computer learning, increased sensor quality, and improved communication interfaces: they’re all important aspects in the future of the Internet of Things.

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