In this work, we introduce and use an innovative approach for adaptive piecewise linear
interval approximation of sensor characteristics, which are differentiable functions. The aim …

Applications for adaptive (sometimes also called smart) Cyber-Physical Systems are
blossoming thanks to the large volumes of data, sensed in a continuous fashion, in large …

Piecewise linear approximation of sensor signals is a well-known technique in the fields of
Data Mining and Activity Recognition. In this context, several algorithms have been …

Data are naturally collected in their raw state and must undergo a series of preprocessing
steps to obtain data in their input state for Artificial Intelligence (AI) and other applications …

The growing interest in data analysis applications for Cyber–Physical Systems stems from
the large amounts of data such large distributed systems sense in a continuous fashion. A …

Data streams produced by mobile devices, such as smartphones, offer highly valuable
sources of information to build ubiquitous services. However, the diversity of embedded …

In the past decade, inertial measurement sensors have found their way into many wearable
devices where they are used in a broad range of applications, including fitness tracking, step …

Energy consumption is the major constraint in the design and the deployment of Wireless
Sensor Networks (WSNs). Since the transmission of data induces high energy costs in WSN …

Today, ubiquitously sensing technologies enable inter-connection of physical objects, as
part of Internet of Things (IoT), and provide massive amounts of data streams. In such …

Energy consumption is one of the most important factors to consider in the design of
Wireless Sensor Networks (WSNs). Many research works have been focused on lowering …