International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 05 | May 2025
p-ISSN: 2395-0072
www.irjet.net
Soil Monitoring with Crop and Fertilizer Recommendation using IOT and ML Prof. P. N. Kate Deshmukh 1, Swarali Pathak 2, Sayali Shivpuje 3, Neha Taware 4, Vaishnavi Yewale 5 1 Professor, Department of Computer Engineering, SVPM’S College of Engineering Malegaon BK, Baramati,
Maharashtra, India. 2, 3. 4, 5 Student, Department of Computer Engineering, SVPM’s College of Engineering, Malegaon BK, Maharashtra,
India. ---------------------------------------------------------------------***--------------------------------------------------------------------
Abstract - Agriculture continues to be a vital and rapidly
Agriculture today is evolving through the integration of data-driven methods and smart technology, a movement commonly known as precision farming. One of the core challenges this approach addresses is soil degradation, which often results from excessive or improper farming practices. This system focuses on maintaining soil vitality by continuously analyzing crucial soil parameters, ensuring sustainable crop production.
expanding sector of the Indian economy, with India ranking second globally in the production of several agricultural commodities. The adoption of advanced technologies like the Internet of Things (IoT) and Machine Learning (ML) has significantly improved agricultural methodologies by enabling smart soil monitoring and informed decisionmaking. This study presents a system that utilizes IoT-based sensors to measure key soil health indicators, including moisture content, pH value, temperature, and nutrient levels. The data collected from these sensors is analyzed through ML algorithms to generate accurate crop and fertilizer recommendations based on specific soil conditions. By harnessing real-time monitoring and predictive analytics, the system aims to boost crop productivity, make efficient use of resources, and encourage sustainable agricultural practices. It helps tackle issues such as soil degradation, improper fertilizer usage, and mismatched crop choices, ultimately assisting farmers in improving yield and maintaining environmental balance. Furthermore, the system incorporates a user feedback mechanism, allowing farmers to share their experiences and outcomes. This enhances the platform's adaptability and usability. Despite occasional challenges due to limited technical knowledge or access, the system empowers farmers to make smarter decisions and improve overall agricultural efficiency.
To achieve efficient farming outcomes, it is vital to evaluate fields based on specific criteria related to both crops and fertilizers. The model developed uses these inputs to recommend appropriate fertilizers that support healthy plant growth and improve yields. By implementing proper techniques and making informed decisions, farmers can produce better-quality crops with fewer resources. The use of Internet of Things (IoT) devices and machine learning (ML) algorithms has simplified the process of soil monitoring and decision-making. These technologies collect and analyze real-time data to recommend the best crop and fertilizer combinations for each unique soil profile. Soil health is often compromised due to repeated cultivation, which reduces its nutrient content and productivity. This system aims to restore and maintain soil quality by regularly checking vital indicators such as pH, temperature, moisture content, and water capacity. Doing so not only improves the soil’s lifespan but also ensures consistent and high-yielding crop growth.
Keywords - Integrated Soil Monitoring, Crop Recommendation, Fertilizer Recommendation, IOT, ML, Real-Time Data Analysis.
For maximum productivity, historical data on various crop types must be evaluated alongside current soil conditions. By analyzing parameters like soil moisture, pH levels, and nutrient availability, the system provides precise recommendations. It also identifies missing nutrients and guides farmers in enriching the soil accordingly.
1.INTRODUCTION The system designed for agricultural use has brought significant improvements in crop monitoring and fertilization. By leveraging advanced technologies, it has reduced dependency on manual labor while enhancing the overall health and productivity of crops. This system selects the most suitable crop for a given soil type using key environmental and soil metrics such as pH level, temperature, humidity, and water retention.
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Impact Factor value: 8.315
This system evaluates essential soil parameters to support effective crop cultivation and enhance the overall health of specific crops. By implementing this technology, farmers can achieve higher yields of nutrient-rich crops. It also serves as a valuable tool to connect farmers—especially those
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