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Mobile supercomputers are the trend with edge computers in the AI Transportable part of the market, pushing datacenter power to the sensor location. The larger scale sensor ingest requirements above are much more demanding than what a 200-watt laptop may offer. This was used to log & adjust fuel maps, fuel injector duty cycles at pending RPM and boost with turbo-powered cars, while the car is strapped to a dyno machine. Sensor data must be ingested, conditioned, and converted to digital, then run through application algorithms, and finally sent to a communication device for the pending actions.Īs a car enthusiast, it was common practice for the past couple of decades to have a laptop connected to the OBD2 port. The AI Transportable applications' radar/camera field in these vehicles are much larger in scale, with calculation speeds demanding faster results. Larger and heavier vehicles such as planes, tractors, ships, and semi-trucks would demand larger and stronger edge computer appliances to handle the data ingest and processing power. While passenger vehicles are limited to size and number of sensors required to cover the perimeter field, these require smaller compute power and sensor network.
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Kelly Blue Book states that there has been a 50% reduction in frontal collisions with these smart safety systems in place. The stats also show 23% less lane change collisions that result in injury. This may be used to stop abruptly or weave out of harm’s way. These may be programed to make direction changes if one or more of the sensors detect something in its path. If an incident occurs, programmed scripts, AI or machine learning, is taking over before the human brain and muscle reflexes can react, which will vary depending on brand of car you own. Sensor data is reading current speed, load, road gradient, and tire slippage, all while radar sensors buffer the perimeter to calculate incoming objects. Multiple sensors and calculations are occurring every millisecond as you drive to work, school or the store. One of the most common everyday features can be found in the cars we drive today.
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Why is the speed important with on-premises edge computing? It’s already part of our everyday lives. Edge computers of all sizes are taking the power of the data center and access of the cloud into environments where sensors and/or cameras are located. Tires screeching to a halt, your car’s edge computer has predicted a collision warning and acted according to its scripted protocol without communication to a network.