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Utilization of IoT in the Horticulture Sector: Innovative Solutions for Agriculture Support

Smart Agriculture Smart Horticulture IoT
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Catalog Summary

"Dataset documenting IoT sensor deployments in horticulture operations including greenhouse monitoring, fruit/vegetable cultivation parameters, and automated control systems for temperature, humidity, light, and nutrient delivery."

Catalog Notes

Overview

The Utilization of IoT in the Horticulture Sector dataset published on Mendeley Data in August 2025 provides real-world data from IoT-enabled horticulture systems, showcasing innovative technological solutions for controlled environment agriculture.

Scope and Context

  • Data collected from greenhouse and controlled environment horticulture facilities.
  • Focus on fruit and vegetable cultivation including tomatoes, cucumbers, lettuce, strawberries, and ornamental plants.
  • Integration of multiple sensor types and automated control systems for optimal growing conditions.

Measured Parameters

  • Environmental Controls: Temperature, humidity, CO₂ concentration, and light intensity (PAR - photosynthetically active radiation).
  • Irrigation and Nutrients: Soil or substrate moisture, pH, electrical conductivity (EC), and nutrient solution composition.
  • Plant Health Indicators: Growth measurements, leaf temperature, and visual monitoring data.
  • Energy and Resources: Water consumption, energy usage for heating/cooling/lighting, and ventilation system status.

IoT System Architecture

  • Wireless sensor networks deployed throughout greenhouse facilities with centralized data collection.
  • Automated actuator control for irrigation valves, ventilation fans, heating systems, shade curtains, and supplemental lighting.
  • Cloud-based monitoring and control interfaces enabling remote management.
  • Data logging at configurable intervals (typically 5-15 minutes) for comprehensive environmental tracking.

Use Cases

  • Precision horticulture: Optimizing growing conditions for specific crops and growth stages.
  • Resource efficiency: Minimizing water, energy, and fertilizer use while maximizing yield and quality.
  • Climate control algorithms: Developing and testing automated greenhouse climate management systems.
  • Crop modeling: Building predictive models for growth, flowering, and harvest timing based on environmental data.
  • Decision support systems: Creating tools to assist growers in real-time management decisions.

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Mendeley Data.

Preview on Mendeley Data

Cite This Dataset

Frameswara, G. (2025). Utilization of IoT in the Horticulture Sector: Innovative Solutions for Support Agriculture. [Dataset]. Mendeley Data. https://doi.org/10.17632/6sckkmyhyj.1

Source metadata: Mendeley Data (2025) · DOI: 10.17632/6sckkmyhyj.1

Indexed by IoTDataset.com on Jan 31, 2026

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