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              <text>Farm field security system using CNN and GSM module</text>
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              <text>Loss of crops and the destruction of livestock have been a major problem for many people in rural areas due to grass-fed animals whose food is derived from plants. According to research 32% are herbivores [1]. Reduced emissions from deforestation as well as deforestation are the main reason for wildlife moving towards urban areas. It results in wildlife infestation and human and animal conflicts. Therefore, compensating for the rapid loss of crops and the slaughter of livestock requires animal shelter and isolation in order to restrict the entry of animals into farm fields. The paper describes an effective and reliable way to identify and repel wildlife from farmland and to send real-time data to the farmer indicating animal attack on fields. An image of an animal will be obtained by convolution neural networks using intensive reading algorithms that provide a message to the farmer using the GSM module. It uses a user alert system and the animal scaring method. The test results show that the proposed algorithm has high visual accuracy. The detection level of the test set is achievable and the detection result is reliable.  2024 Author(s).</text>
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              <text>Singh M.; Chauhan S.; Chauhan S.S.; Chauhan S.</text>
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              <text>AIP Conference Proceedings, Vol-3121, No. 1</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1063/5.0222347" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0222347&lt;/a&gt;
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              <text>ISSN: 0094243X</text>
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              <text>Singh M., Christ, Deemed to Be University, Delhi - NCR Campus, Ghaziabad, India; Chauhan S., Dronacharya Government College, Gurugram, India; Chauhan S.S., EY India, Gurugram, India; Chauhan S., Altimetrik, Vancouver, Canada</text>
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