Abstract
The Internet of Things (IoT) has made it possible for previously
unconnected items, such as vehicle engines, to be connected to the network, leading to
the emergence of numerous active data streams. The IoT and big data analytics have
made considerable strides, opening up intriguing new possibilities for medical and
healthcare solutions. Many organisations still struggle with the usage of AI and ML
technology when attempting to expand their digital transformation programmes and
utilise IoT data.
The most current trends involve modifying IoT data for smart applications using
artificial intelligence techniques. Numerous apps use data science and analytics to
extract conclusions from gigabytes of data. However, these applications do not deal
with the issue of constantly identifying patterns in IoT data. The introduction of the IoT
and the cloud has further enhanced things by offering smart business recommendations
as well as insights into how people operate and how lives are changing. We discuss a
variety of AI capabilities and how to apply them to IoT devices in Hands-On AI for
IoT.
The logic-based substrate provides low energy footprints and higher cognitive accuracy
during training and inference, which is a crucial requirement for effective AI with long
operating life. The use of AI in the industrial sector has enormous potential. However,
it frequently necessitates expensive and resource-intensive machine learning
professionals as well as in-depth knowledge of complex statistics and how they are
implemented in practical use cases.