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@article{204451,
        author = {Ashwin G Singerji and Adharsh RK and Gifton C S and Jershan J},
        title = {IoT-Based Intelligent Plant Care System Adaptive Irrigation Control},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {103-107},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204451},
        abstract = {Efficient irrigation control is fundamental to sustainable horticulture and small-scale agriculture. This work presents the design, modeling, and experimental validation of an Internet of Things (IoT)-enabled intelligent plant care system that integrates environmental sensing, adaptive threshold-based irrigation control, and cloud-based analytics. Unlike conventional timer-driven watering systems, the proposed approach models soil moisture dynamics as a first-order nonlinear system and employs adaptive decision logic to regulate water delivery. The system incorporates soil moisture, temperature, relative humidity, and ambient light sensors interfaced with a Wi-Fi-enabled microcontroller. A cloud server stores and visualizes time-series environmental data, enabling remote supervision. Experimental validation demonstrates improved moisture stability, reduced water consumption, and enhanced plant growth consistency under varying environmental conditions. Mathematical modeling, calibration procedures, and statistical performance metrics are provided to substantiate system effectiveness.},
        keywords = {IoT, Smart Irrigation, Soil Moisture Modeling, Embedded Systems, Adaptive Control, Precision Agriculture},
        month = {June},
        }