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Agriculture continues to be the backbone of many economies, yet traditional irrigation and pesticide management practices often rely on manual observation, resulting in either over-irrigation, water scarcity, or excessive pesticide use. With advancements in the Internet of Things (IoT) and predictive analytics, smart agriculture solutions have gained popularity due to their ability to automate decision- making and improve resource utilization. In this study, we propose AgriSense, an IoT-enabled smart irrigation system that combines ARIMA-based time series forecasting with real-time pesticide detection. ARIMA models are well-suited for soil moisture prediction due to their ability to capture temporal dependencies. Pesticide detection ensures safe food production and prevents harmful effects of chemical residues. Integrating these features enables farmers to monitor field conditions, automate irrigation, and ensure crop safety using a unified system