Sandra Guzman

Assistant Professor University of Florida

Gainesville FL

Sandra Guzman develops IoT and AI decision‑support tools to optimize water and nutrient use in specialty crops like fruits and vegetables.

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Biography

Sandra Guzman is an assistant professor and extension specialist based at the Indian River Research & Education Center, leading the Smart Irrigation and Hydrology Lab. Her program develops precision‑smart irrigation, agrohydrological modeling and IoT/AI decision‑support systems that integrate field sensors, weather and stakeholder input to reduce water use and nutrient losses in citrus and vegetable systems. She implements adoption‑focused programs for data-based agricultural water management. One of her tools includes the IrrigMonitor software, which is used in commercial operations. She collaborates on multi‑site projects and translate data‑driven solutions from field scale to watershed planning.

Areas of Expertise

Hydrology

Precision Irrigation

Smart Irrigation

Social

Articles

Bridging the gap between water-saving technologies and adoption in vegetable farming: insights from Florida, USA

Frontiers in Agronomy

Athelly, et al.

2025-08-26

This study examines the willingness of Florida vegetable growers to adopt water-saving irrigation technologies, focusing on socio-economic factors, perceived barriers, and opportunities for enhanced outreach.

Adaptive and predictive decision support system for irrigation scheduling: An approach integrating humans in the control loop

ScienceDirect

Conde, et al.

2024-02-01

Reported technological tools for irrigation scheduling lack the integration of real-time crop measurements, weather forecasting, and the limitations and variabilities introduced by human operation. Moreover, most of these tools do not provide practical irrigation recommendations, limiting their adoption and benefits in enhancing agricultural efficiency and reducing environmental impact. To address these challenges, we propose an adaptive and predictive irrigation management decision support system by formulating a feedback plus feedforward algorithm that uses modeling, estimation, prediction, and control strategies.