Publication | Closed Access
Integrating IoT-Based Environmental Monitoring and Data Analytics for Crop-Specific Smart Agriculture Management: A Multivariate Analysis
36
Citations
10
References
2023
Year
Unknown Venue
Precision AgricultureEnvironmental MonitoringEngineeringDigital AgricultureLand UseAgricultural EconomicsAgricultural RoboticsIot-based Environmental MonitoringAgricultural CyberneticsRelative HumidityData ScienceInternet Of ThingsSoil MoisturePublic HealthAgricultural MachinerySmart AgricultureCrop MonitoringSmart Agriculture ManagementGeographyPrecision FarmingAgricultureAgricultural EngineeringAgricultural ManagementData AnalyticsMultivariate Analysis
The integration of Internet of Things (IoT) technology in smart agriculture management has emerged as a promising approach to address challenges in the agricultural sector. This abstract provides an overview of the concept of integrated IoT system solutions for smart agriculture management, highlighting its benefits and applications. The integrated IoT system combines IoT sensors, devices, and cloud-based platforms to enable real- time data collection, analysis, and decision-making in agriculture. By deploying IoT sensors across the farm, farmers can gather data on crucial environmental parameters such as soil moisture, temperature, and humidity. This data empowers farmers to make informed decisions regarding irrigation, fertilization, and pest control, leading to optimized resource utilization and improved crop yields. Automation is another key aspect of integrated IoT systems in agriculture. IoT -enabled machinery and equipment, such as tractors, drones, and sensors, can automate tasks like seeding, spraying, and harvesting. This automation reduces manual labor, minimizes errors, and increases operational efficiency. The integration of data analytics and machine learning algorithms in IoT systems enables the extraction of valuable insights from the collected data. Farmers can leverage these insights for proactive decision-making, early disease detection, and yield prediction. In this study, as per the required temperature and relative humidity, tomatoes are grown in spring-summer and pea in winter seasons. To detect the moisture content of the soil at various temperatures and relative humidity levels, soil moisture sensor is also deployed in the field. Temperature, humidity, and soil moisture all exhibit a wide range of variations. In conclusion, the integration of IoT technology in smart agriculture management through an integrated IoT system solution holds great potential for optimizing farming practices, increasing productivity, and promoting sustainable agriculture. Further research and technological advancements are needed to overcome challenges and fully realize the benefits of integrated IoT systems in agriculture.
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