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.
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