Adapting physically complete models to vehicle-based EMI array sensor data: data inversion and discrimination studies

2010 ◽  
Author(s):  
Fridon Shubitidze ◽  
Jonathan S. Miller ◽  
Gregory M. Schultz ◽  
Jay A. Marble
Keyword(s):  
Sensor Data ◽  
Array Sensor ◽  
Data Inversion

scholarly journals Indoor Human Detection Based on Thermal Array Sensor Data and Adaptive Background Estimation

2017 ◽  
Vol 05 (04) ◽  
pp. 16-28 ◽  
Author(s):  
Anna A. Trofimova ◽  
Andrea Masciadri ◽  
Fabio Veronese ◽  
Fabio Salice
Keyword(s):  
Human Detection ◽  
Sensor Data ◽  
Background Estimation ◽  
Array Sensor

Guided-Mode Resonance Sensor Data Inversion for Bulk and Surface Variables

2020 ◽  
Author(s):  
Joseph A. Buchanan-Vega ◽  
Mohammad G. Abdallah ◽  
Brett R Wenner ◽  
Jeffrey W. Allen ◽  
Monica S. Allen ◽  
...  
Keyword(s):  
Sensor Data ◽  
Data Inversion ◽  
Guided Mode ◽  
Resonance Sensor ◽  
Guided Mode Resonance

Applying a volume dipole distribution model to next-generation sensor data for multi-object data inversion and discrimination

2010 ◽  
Author(s):  
Fridon Shubitidze ◽  
David Karkashadze ◽  
Juan Pablo Fernández ◽  
Benjamin E. Barrowes ◽  
Kevin O'Neill ◽  
...  
Keyword(s):  
Sensor Data ◽  
Distribution Model ◽  
Next Generation ◽  
Data Inversion

scholarly journals Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4062
Author(s):  
Cristian Perra ◽  
Amit Kumar ◽  
Michele Losito ◽  
Paolo Pirino ◽  
Milad Moradpour ◽  
...  
Keyword(s):  
Low Cost ◽  
Synthetic Data ◽  
Field Evaluation ◽  
Sensor Data ◽  
Indoor Environments ◽  
Stress Tests ◽  
Ambient Conditions ◽  
Time Pattern ◽  
Array Sensor ◽  
Depth Analysis

We propose a device for monitoring the number of people who are physically present inside indoor environments. The device performs local processing of infrared array sensor data detecting people’s direction, which allows monitoring users’ occupancy in any space of the building and also respects people privacy. The device implements a novel real-time pattern recognition algorithm for processing data sensed by a low-cost infrared (IR) array sensor. The computed information is transferred through a Z-Wave network. On-field evaluation of the algorithm has been conducted by placing the device on top of doorways in offices and laboratory rooms. To evaluate the performance of the algorithm in varying ambient temperatures, two groups of stress tests have been designed and performed. These tests established the detection limits linked to the difference between the average ambient temperature and perturbation. For an in-depth analysis of the accuracy of the algorithm, synthetic data have been generated considering temperature ranges typical of a residential environment, different human walking speeds (normal, brisk, running), and distance between the person and the sensor (1.5 m, 5 m, 7.5 m). The algorithm performed with high accuracy for routine human passage detection through a doorway, considering indoor ambient conditions of 21–30 °C.

Camp Beale live-site handheld-sensor data inversion and classification using advanced EMI models

2012 ◽  
Author(s):  
I. Shamatava ◽  
J. P. Fernández ◽  
B. E. Barrowes ◽  
K. O'Neill ◽  
A. Bijamov ◽  
...  
Keyword(s):  
Sensor Data ◽  
Data Inversion
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