Abstract
In economies heavily dependent on agriculture, such as India, the farming sector plays a crucial role, yet it faces various challenges that hinder its profitability and, unfortunately, contribute to farmer suicides. Pest attacks stand out as a significant factor contributing to the agricultural woes, causing substantial harm to crops. This research proposes a solution leveraging Raspberry Pi technology, incorporating a mathematical model known as Beta regression analysis. The model utilizes farm humidity and temperature as inputs to predict environmental conditions conducive to pest formation and attacks. The resultant Beta regression factor serves as a risk indicator for environmental health. Based on this factor, the system forecasts the likelihood of pest occurrences. By offering advance predictions of pest activity, farmers can strategically apply the right amount of pesticides, effectively mitigating the impact of pests on their crops. This proactive approach allows farmers to manage potential damage before it occurs, fostering a more sustainable and profitable farming environment. The innovative system outlined in this paper aims to empower farmers with accurate pest control predictions, thus enhancing their ability to navigate and overcome challenges in the agricultural landscape.
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