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How to increase output voltage of PIR sensor? 

Electro-optical sensor
Triboelectric effect
Voltage
Offset (computer science)
Microbolometer

Answers from top 9 papers

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Papers (9)Insight
Open access•Journal Article•DOI
A self-powered triboelectric nanosensor for PH detection
Ying Wu, Yuanjie Su, Bai Junjie, Guang Zhu, Xiaoyun Zhang, Zhanolin Li, Yi Xiang, Jingliang Shi 
01 Jan 2016-Journal of Nanomaterials
54 Citations
Experimental results show that the output voltage of the TENG sensor increases with the increasing PH value, which indicate that the PH value of different solution can be real-time monitored.
Proceedings Article•DOI
Enhanced performance PIR security sensors
Kevin Charles Liddiard
03 Apr 2008
4 Citations
The enhanced performance PIR upgrade sensor has two significant advantages over current technology: extended detection range and ability to detect developing fire or equipment failure.
Open access•Journal Article•DOI
Investigation of a Sensitive Element for the Pressure Sensor Based on a Bipolar Piezotransistor
Mikhail Basov, Denis Prigodskiy 
30 Nov 2017
9 Citations
The sensitivity increase allows for the following sensor improvements: die size reduction, increase of diaphragm mechanical strength while keeping high pressure sensitivity, and simplifying requirements to external processing of the pressure sensor output signal.
Proceedings Article•DOI
Online digital offset voltage compensation method for AMR sensors
Andreina Zambrano, Hans G. Kerkhoff 
11 May 2015
7 Citations
This voltage changes with sensor aging and hence should be compensated not just at the moment of manufacturing but also during the sensor lifetime.
Open access•Journal Article•DOI
A Fiber-Optic Voltage Sensor Based on Macrobending Structure
Pengfei Wang, Yuliya Semenova, Qiang Wu, Gerald Farrell 
01 Jul 2011-Optics and Laser Technology
34 Citations
The sensor can be easily scaled to suit other voltage levels and be effectively combined with optical current sensors.
Open access•Journal Article•DOI
An Integrated Framework for Binary Sensor Placement and Inhabitants Location Tracking
Maria Pia Fanti, Gregory Faraut, Jean-Jacques Lesage, Michele Roccotelli 
01 Jan 2018-IEEE Transactions on Systems, Man, and Cybernetics
27 Citations
can affect the detection capacity of PIR sensors.
Proceedings Article•DOI
PIR security sensors: developing the next generation
Kevin C. Liddiard
27 Apr 2007
8 Citations
Establishment of a new generation PIR security sensor technology also paves the way for high performance low cost IR sensors for numerous short range applications.
Proceedings Article•DOI
A 30.1μm 2 , < ±1.1°C-3σ-error, 0.4-to-1.0V temperature sensor based on direct threshold-voltage sensing for on-chip dense thermal monitoring
Seongjong Kim, Mingoo Seok 
30 Nov 2015
9 Citations
The proposed sensor also achieves a 0.2V better voltage scalability than the previous best voltage-scalable design.
Proceedings Article•DOI
Multi-agent based wireless pyroelectric infrared sensor networks for multi-human tracking and self-calibration
Jiang Lu, Jiaqi Gong, Qi Hao, Fei Hu 
19 Dec 2013
13 Citations
Initial experimental results illustrate the advantages of the proposed MAS based PIR sensor networks.

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How to apply DCNN on data from PIR sensor?5 answersDeep Convolutional Neural Networks (DCNN) can be applied to data from Passive Infrared (PIR) sensors in the following way. First, the data collected from the PIR sensor is preprocessed by selecting optimal features such as coefficients of Fourier transform (FFT), discrete wavelet transform (DWT), and the absolute value of an acceleration filter. These features are then normalized and subjected to principal component analysis (PCA). The preprocessed data is then used as input to the DCNN model for classification and recognition tasks. The DCNN model is trained using a deep learning approach, which allows it to learn complex features from the data. The performance of the DCNN model can be compared with other classical machine-learning classifiers such as random forest, and the accuracy of the DCNN model can be evaluated. Overall, applying DCNN on data from PIR sensors involves preprocessing the data and training a DCNN model for classification and recognition tasks.
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