LAKE WALES, Fla. — 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.
Modeled here are the three levels: the sensory level represented by the wrist-worn wearable taking Big Data real-time readings; the level two hub (here a smartphone), which summarizes in trending graphical forms which it then sends to level three, the cloud, every few minutes.
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"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."
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