  Today, wearable internet-of-things (wIoT) devices continuously flood the
cloud data centers at an enormous rate. This increases a demand to deploy an
edge infrastructure for computing, intelligence, and storage close to the
users. The emerging paradigm of fog computing could play an important role to
make wIoT more efficient and affordable. Fog computing is known as the cloud on
the ground. This paper presents an end-to-end architecture that performs data
conditioning and intelligent filtering for generating smart analytics from
wearable data. In wIoT, wearable sensor devices serve on one end while the
cloud backend offers services on the other end. We developed a prototype of
smart fog gateway (a middle layer) using Intel Edison and Raspberry Pi. We
discussed the role of the smart fog gateway in orchestrating the process of
data conditioning, intelligent filtering, smart analytics, and selective
transfer to the cloud for long-term storage and temporal variability
monitoring. We benchmarked the performance of developed prototypes on
real-world data from smart e-textile gloves. Results demonstrated the usability
and potential of proposed architecture for converting the real-world data into
useful analytics while making use of knowledge-based models. In this way, the
smart fog gateway enhances the end-to-end interaction between wearables (sensor
devices) and the cloud.
