CNN Based Rat Detection using Thermal Sensor Article Swipe

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Yogesh Kumar , N.A. Priyanka , Madhavi Reddy , P. Sushma ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.30534/ijeter/2023/0911122023

The detection and control of rats in commercial buildings and industries are crucial issues due to the damage they can cause to Godowns and equipment. Traditional methods of rat detection and control can be time-consuming and expensive and may not always be effective. This has brought the exploration of machine learning-based approaches, which can provide more accurate and efficient detection of rats. One such approach is the use of thermal sensors in conjunction with machine learning algorithms to detect rats in commercial buildings, industries, etc. Thermal sensors can detect the body heat of rats, and machine learning algorithms can be trained to analyze thermal data and accurately identify the presence of rats. This approach has several advantages over traditional methods, including higher accuracy, long-range and faster detection. The machine learning algorithms used in this approach can be trained using large datasets of thermal images of rats, which can be obtained using thermal cameras

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Type: article
Language: en
Landing Page: http://doi.org/10.30534/ijeter/2023/0911122023
PDF: https://doi.org/10.30534/ijeter/2023/0911122023
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DOI: https://doi.org/10.30534/ijeter/2023/0911122023

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Title: CNN Based Rat Detection using Thermal Sensor

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Publication year: 2023

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Publication date: 2023-12-07

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Authors: Yogesh Kumar, N.A. Priyanka, Madhavi Reddy, P. Sushma

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Landing page: https://doi.org/10.30534/ijeter/2023/0911122023

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Concepts: Computer science, Artificial intelligence, Machine learning, Thermal, Control (management), Physics, Meteorology

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