Utilization of IoT in the Horticulture Sector: Innovative Solutions for Agriculture Support
Abstract
"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."
Description
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, COâ‚‚ 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, Gendri (2025). Utilization of IoT in the Horticulture Sector: Innovative Solutions for Agriculture Support. [Dataset]. Mendeley Data. https://doi.org/10.17632/6sckkmyhyj.1
Select your preferred citation style above. The citation will automatically update and you can copy it to your clipboard.
Original source: Mendeley Data (2025). Visit official page for more details.
Indexed by IoTDataset.com on Jan 31, 2026
Ready to Start Your Research?
Download this dataset directly from the official repository and start building your next breakthrough project.