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@article{197724,
        author = {S. Abu sumaiya and M. Mohamed Rafi},
        title = {FOREST ALERT SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12082-12085},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197724},
        abstract = {The Python Forest Alert System is an intelligence alerting solution that leverages Artificial Intelligence and Convolutional Neural Networks (CNN) to identify animal in real time using CCTV video footage. In agriculture, one of the major social problems that is existing in the present is the damaging of the crops by the wild animals. Wild animal intrusion has always been a persisting problem to the farmers. Some of the animals that act as a threat to the crops are deer, wild boar, moles, elephants, monkeys and others. These animals may feed on crops and also run around the field in the absence of farmer and thus cause damage to those crops. This may in turn results in significant loss in the yield and will cause additional financial protection in order to deal with the aftermath of the damage. Every farmer, while utilizing his production, should also be aware of the fact that animals are also existing in the same place and that they need to be protected from any probable suffering. This problem must be attended immediately and an effective solution must be created and accomplished. Thus, this project aims to address this problem. One of the significant issues that is faced by farmers are their yields get damaged by wild animals that intrudes their crops. Wild animal interruption has forever been a continuing issue to the ranchers. A portion of the animals that go about as a danger to the yields are wild boar, deer, wild buffalo, elephants, tiger, monkeys and others. These animals might benefit from crops and furthermore go around the field without any rancher and accordingly make damage those yields. This may thus bring about critical misfortune in the yield and will make extra monetary security all together arrangement with the result of the damage. In any case, wildlife-friendly cultivating regularly brings about lower effectiveness. In this manner, endeavor have been made to foster programmed frameworks fit for identifying wild animals in the harvest without superfluous discontinuance of the cultivating activity. For instance, a recognition framework in light of infrared sensors has been answered to lessen wildlife mortality in Germany A UAV-based framework for roe deer grovel location is introduced. The creators show that warm imaging can be utilized to identify roe deer grovels based on elevated film, but the location is as yet performed physically.},
        keywords = {convolutional neural network (CNN), Artificial intelligence (AI), Deep learning, Crop protection, Rural area protection},
        month = {April},
        }