DATA ANALYTICS opportunities around data . No company has ever said they want less data , but they do need to consider the cost and effort of storing and processing it , as well as keeping it safe . IoT devices and sensors will be some of the biggest creators of data .”
Challenges remain , however , before the technology is fully realised . “ We need to be able to minimise the reliance of smart devices on the cloud and begin transitioning towards an IoT model that integrates AI locally ,” says Lippett . “ Today ’ s smart devices are typically dependent on resource-hungry and costly cloud-based compute . This comes marred with challenges around latency , connectivity , privacy and energy consumption . The flaws in cloud networking are well documented , particularly as they ’ re usually reliant on a similarly imperfect network , Wi-Fi , to make that connection .” Overcoming that hurdle involves use of edge computing . “ We ’ re now beginning to see processors that allow AI to operate on the edge of the network — locally on the device itself , independent of the cloud . These devices , boasting both a sophisticated suite of IoT sensors ( voice identification , imaging capabilities , presence detection etc .) and effective digital signal processing ( to interpret the results ), no longer need to lean on the cloud to perform .”
IoT devices , then , are now an inescapable presence in our lives , whether that ’ s the smart speakers in our home lives or sensors in a work setting . Thanks to AI , IoT is only becoming more versatile – expect to continue to feel its transformative impact in the coming years .
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