Some introduction thoughts. Analytics (Or AI) should have as an option the ability to execute close to the edge (the delivery point) of its implementation. This is not always necessary, but should clearly be an option.
Data intelligence — is edge analytics the saviour of IoT? in 7wData
As it stands, the existing IoT model isn’t working. The concept of transferring vast amounts data that’s collected from an army of sensors to a central repository is neither sustainable or affordable
With IoT, businesses were meant to be able to leverage local data that would drive local decisions and improve local performance. What has actually happened is the creation of a huge data source that, at best, has added to the depth of overall business intelligence. The sheer scale is proving overwhelming and is starting to echo the disappointment that ‘big data’ created. And, if businesses believe the arrival of 5G will enhance this process — think again. Bandwidth will continue to come under extreme pressure, filling up quickly with the movement of voice and audio.
It is now time that everyone stops, takes a giant step back and ask themselves: ‘what value is the business wanting to get from IoT?’ The outcome should be to facilitate better, faster and more informed local decision making — both automated through machine learning and to equip individuals with the insight they need to be able to make instant decisions on the front line. ..."
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