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Enhance README with project details and features
Added detailed project description and features of the IR thermometer simulation.
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README.md

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# Digital-IR-thermometer-Simulation
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# Digital-IR-thermometer-Simulation
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Python simulation of an IR thermometer demonstrating real-world sensor behavior including noise, drift, outliers, and signal processing techniques (moving average filter & outlier rejection).
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A Python-based simulation of a Digital Infrared (IR) Thermometer for body temperature measurement.
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This project demonstrates how real-world environmental factors affect temperature readings over a
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60-second period, including:
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- Random measurement noise (Gaussian distribution)
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- Temperature drift (-0.1°C/min)
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- Emissivity mismatch bias
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- Occasional outliers and spikes
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The simulation implements signal processing techniques to improve measurement accuracy:
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- Moving average filter (window size: 5)
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- Statistical outlier rejection (3σ threshold)
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Based on the Stefan-Boltzmann Law for infrared radiation, this project visualizes the difference
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between raw sensor data and processed measurements, demonstrating the importance of signal processing
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in real-world sensor applications.
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Developed as part of the "Artificial Intelligence for Industrial Applications" program at
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OTH Amberg-Weiden.

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