Integrating IoT and Sensor Technologies for Smart Agriculture: Optimizing Crop Yield and Resource Management

This research paper explores the implementation of Smart Agriculture solutions in the context of modern farming. The project employs a range of sensor technologies, IoT devices, and cloud-based data analytics to collect, process, and provide real-time insights to farmers. The study’s objectives include enhancing data-driven decision-making, improving resource efficiency, ensuring environmental sustainability, and promoting affordability and accessibility for a wide range of farmers. The research methodology involved the deployment of advanced sensors, such as soil moisture, light intensity, temperature and humidity, and barometric pressure sensors, across an agricultural field. Data collected from these sensors was integrated into a cloud-based system, which allowed farmers to access real-time information and insights through a user-friendly interface. The results of the experimentation phase demonstrated the effectiveness of the system in optimizing irrigation schedules, enhancing crop health, and conserving resources. Challenges related to data accuracy, connectivity, and initial setup costs were addressed through calibration, network stability, and affordable subscription plans, ensuring the system’s practical applicability. This research paper contributes to the field of precision agriculture by providing an integrated, scalable, and accessible solution for farmers. The study emphasizes data-driven decision- making and sustainable farming practices, making it a valuable resource for enhancing agricultural productivity in the face of modern challenges.