Machine learning has dramatically altered what manufacturers are able to do with IoT. Today, there are numerous industries that have specific IoT needs. For example, the internet of medical things (IoMT) has devices such as outpatient heart monitors that can be worn at home. These devices often require large amounts of data to be sent over the network or large compute capacity on the edge to process heart-related events. Another example is agricultural IoT (AIoT) devices that are often placed in locations where there is no Wi-Fi or cellular network. Prescriptions or models are pushed down to these semi-connected devices. Many of these devices require that decisions be made on the edge. When connectivity is finally ...
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