Beating IoT Big Data With <span style='color:red'>Brain Emulation</span>
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Beating IoT Big Data With Brain Emulation

　　To beat Big Data, according to German electronics company Robert Bosch, we need to tier the solution by making every level smart — from edge sensors to concentration hubs to analytics in the cloud.　　Luckily, we have the smart sensors of the brain — eye, ears, nose, taste-buds and touch sensitivity — as the smartest model in the universe (as we know it) after which to fashion our electronic Big Data solutions to the Internet of Things (IoT), said Marcellino Gemelli, head of business development at Bosch Sensortec.　　"We need to feed our Big Data problems into a model generator based on the human brain, then use this model to generate a prediction of what the optimal solution will look like," Gemelli told the attendees at the recent SEMI MEMS & Sensor Executive Congress (MSEC). "These machine learning solutions will work on multiple levels, because of the versatility of the neuron."　　Neurons are the microprocessors of the brain — accepting thousands of Big Data inputs, but outputting a single voltage spike down their axon after receiving the right kind of input from thousands of dendrites mediated by memory synapses. In this way the receptors of the eye, ear, nose, taste-buds and touch sensors (for presence, pressure and temperature, mainly) can pre-process the deluge of incoming raw Big Data before sending summaries — encoded on voltage spikes — up the spinal cord to the hub called the "old brain" (the brain stem and automatic behavior centers such as those handling breathing, heart beating and reflexes). Finally the pre-processed data makes its way through a vast interconnect array called the white matter to its final destination in the conscious parts of the brain (the gray matter of the cerebral cortex). Each part of the cerebral cortex is dedicated to a function like vision, speech, smelling, tasting, the sensations of touch as well as the cognitive functions of attention, reasoning, evaluation, judgement and consequential planning.　　"The mathematical equivalent of the brain's neural network is the perceptron, which can learn with its variable conductance synapse while Big Data is streaming through it," said Gemelli. "And we can add multiple levels of perceptrons to learn everything a human can learn, such as all the different ways that people walk."　　Moore's Law also helps out with multi-layered perceptrons — called deep learning — because it offers a universal way to do smart processing at the edge sensor, in the hub and during analytics in the cloud.　　"First of all, volume helps — the more Big Data the better," said Gemelli. "Second, variety helps — learning all the different aspects of something, such as the mentioned different gaits people use to walk. And thirdly, the velocity at which a perceptron needs to respond needs to be quantified. Once you have these three parameters defined, you can optimize your neural network for any particular application."　　For example, Gemelli said, a smartwatch/smartphone/smart cloud combination can divide-and-conquer Big Data. The smartwatch evaluates the real-time continuous data coming in from individual users, then sends the most important data in summaries to the smartphone every few minutes. Then just a few times a day, the smartphone can send trending summaries to the smart cloud. There the detailed analysis of the most important data points can be massaged in the cloud and fed back to the particular user wearing the smartwatch, as well as to other smartwatch wearers as appropriate suggestions of how anonymous others have met the same goals as they have set.　　Bosch, itself, is emulating this three-tiered brain-like model by putting processors on its edge-sensors so they can identify and concentrate Big Data trending before transmitting to smart hubs.　　"Smart cities, in particular, need to make use of smart sensors with built-in processors to perform the real-time edge sensor trending," said Gemelli. "Then they send those trends to hubs, that analyze and send the most important ones to the cloud for analysis into actionable information for city managers. That is Bosch's vision of the smart cities of the future."
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Release time：2017-11-20 00:00 reading：1529 Continue reading>>

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