Today, the sensing devices play an important role for various system automation and
monitoring of different physical and chemical parameters. Nonlinearity is an important long …

This paper presents a network for indoor and outdoor air quality monitoring. Each node is
installed in a different room and includes tin dioxide sensor arrays connected to an …

This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System)
biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors …

The node of a wireless sensor network (WSN), which contains a sensor module with one or
more physical sensors, may be exposed to widely varying environmental conditions, eg …

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the
input–output characteristic of most sensors is nonlinear in nature, obtaining data from a …

Temperature sensors are widely used in industrial production and scientific research, and
accurate temperature measurement is crucial for ensuring the quality and safety of …

A novel artificial neural network (NN)-based technique is proposed for enabling smart
sensors to operate in harsh environments. The NN-based sensor model automatically …

High precision and smart sensors make up an indispensable data entry for the Internet of
Things technology. Nonetheless, conventional calibration algorithms mainly implemented …

This paper treats the problem of designing an optimal size for a lookup table used for sensor
linearization. In small embedded systems the lookup table must be reduced to a minimum in …

Thermistor is most widely used sensor in the temperature measurement due to its high
sensitivity and fast response. The non‐linearity of the thermistor gives rise to several …