Machine Learning Technique for Precision Agriculture Applications in 5G-Based Internet of Things

Abstract

Monitoring systems based on artificial intelligence (AI) and wireless sensors are in high demand and give exact data extraction and analysis. The main objective of this paper is to detect the most appropriate plant development parameters. This paper has the concept of reducing the hazards in agriculture and promoting intelligent farming. Advancement in agriculture is not new, but the AI-based wireless sensor will push intelligent agriculture to a new standard. The research goal of this work is to improve the prediction state using image processing-based machine learning techniques. The main objective of the paper, as described above, is to detect and control cotton leaf diseases. This paper comprises several aspects, including leaf disease detection, remote monitoring system depending on the server, moisture and temperature sensing, and soil sensing. Insects and pathogens are typically responsible for plant diseases that reduce productivity if not timely. This paper presents a method to monitor the soil quality and prevent cotton leaf diseases. The proposed system suggested uses a regression technique of artificial intelligence to identify and classify leaf diseases. The information would be delivered to farmers through the Android app after infection identification. The Android app also allows soil parameter values like moisture, humidity, and temperature to be displayed along with the chemical level in a container. The relay may be on/off to regulate the motor and chemical sprinkler system as required by using the Android app. In the proposed system, the SVM algorithm delivers the best accuracy in detecting various diseases and demonstrates its efficiency in the detection and control by the improvement of cultivation for the farmers.

Sustainability of precision agriculture as a proposal for the development of autonomous crops using IoT

“…The need for individual fields and crops is observed and analyzed through this data, specifying the distribution of resource quantities used in control systems for monitoring moisture, fertilization, and disease detection. This approach increases crop yield and profitability [14]- [18]. Several studies have proposed IoT-based monitoring systems to visualize and collect data in this area, optimizing water usage in agricultural irrigation systems [19]- [20].…”

“…Monitoring soil conditions, climatological variables, and resource management poses a significant challenge in precision agriculture. Article [14] utilizes IoT for data collection and storage through sensors installed at various points on a farm. This allows for a deep analysis of the system to create an AIbased algorithm that controls natural resource management, primarily disease detection.…”

“…Integrating Artificial Intelligence (AI) Website: www.ijeer.forexjournal.co.in Sustainability of precision agriculture as a proposal for the in precision agriculture also plays a crucial role in enabling more precise and cost-effective resource management [13]. The detection of diseases through artificial vision is one of the areas where extensive research has been conducted, allowing the evaluation of various parameters through image processing, primarily assessing the presence of insects and pathogens causing diseases in crops [14].…”

Contributions of the 5G Network with Respect to Poverty (SDG1), Systematic Literature Review

“…Precision agriculture Crop and soil monitoring for improved productivity. [135][136][137][143][144][145][146]167] Online education Access to online education in remote areas. [130,131,133] Digital banking/internet banking Access to financial and banking services in remote areas.…”

Design and Service Effect Evaluation of Agricultural Social Service Platform Based on 5G and Cloud Computing

“…It displays complex data in a graphical way that is more acceptable to humans, which is convenient for users to manage and develop data through human-computer interaction. Reference [23,24] implemented 5G and nextgeneration mobile networks to develop precision agriculture use cases. Once the requirement assessment and 5G network capabilities were analyzed, the quality indicators of 5G and relevant slice types in precision agriculture were defined.…”