The power of cloud computing, IoT and machine learning combined
Edge intelligence is a new approach to data collection, storage, and processing that combines edge computing with machine learning. The aim is to enhance the quality and speed of data processing, improving connectivity as well as security. By 2021, the edge intelligence market is expected to reach $7.96bn.
In edge intelligence systems, data is processed ‘at the edge’ – in other words, outside of the core communication network or the cloud. The network may direct the data source (for example, a sensor) to send specific data, building up an accurate picture of how devices normally run. The data source can decide what information matters and what doesn’t, sending relevant metrics to the centre of the network for analysis. Through edge intelligence, devices can take control of their own data and communications management, improving accuracy and quality, and reducing time delays. In practice, this means that faults can be detected and dealt with before they become a serious issue.
There are obvious advantages to edge intelligence, namely the ability to make instantaneous decisions at the source of data collection. Some existing IoT platforms lack the bandwidth to backhaul data to centralised locations, leading to data culling and ultimately a lower quality of information. Edge intelligence addresses this issue as less time and energy is spent sending data to the network’s centre. Making quick, real time decisions is integral to the expansion of the Internet of Things, and its usefulness in real world applications.
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