农业工程
农业
计算机科学
精准农业
环境科学
可持续农业
营养管理
农业生产力
MQTT公司
土壤质量
数据库
土壤水分
工程类
物联网
嵌入式系统
土壤科学
生态学
生物
作者
Md Reazul Islam,Khondokar Oliullah,Md. Mohsin Kabir,Munzirul Alom,M. F. Mridha
标识
DOI:10.1016/j.jafr.2023.100880
摘要
Agriculture plays a vital role in feeding the growing global population. But optimizing crop production and resource management remains a significant challenge for farmers. This research paper proposes an innovative ML-enabled IoT device to monitor soil nutrients and provide accurate crop recommendations. The device utilizes the FC-28 sensor, DHT11 sensor, and JXBS-3001 sensor to collect real-time data on soil composition, moisture, humidity, temperature, and for nutrient levels. The collected data is transmitted to a server using the MQTT protocol. Machine learning algorithms are employed to analyze the collected data and generate customized recommendations, including a possible high-yielding crop list, fertilizer names, and its amount based on crop requirements and soil nutrients. Furthermore, the applied fertilizers and treatments to the field during production are stored in the database. As a result, it has become possible to determine the quality of the produce at the consumer level through the mobile app. The system's effectiveness is evaluated through field experiments, comparing its performance with traditional methods. The results demonstrate the device's ability to enhance crop productivity and optimize resource utilization, promoting sustainable agricultural practices and food security. The research contributes to IoT-enabled agriculture, demonstrating the potential of ML techniques in improving soil nutrient management, facilitating informed decision-making about crop fertilizers, and assessing the quality of produced crops at the consumer level.
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