IOT-Enabled Smart Plant Monitoring System with Automated Fertilization

Abstract

The increasing need for efficient and sustainable agricultural practices has led to the adoption of smart technologies in farming. This project presents an IoT-enabled Smart Plant Monitoring System with an automated fertilization mechanism to optimize plant health and growth. The system integrates sensors to monitor key environmental parameters such as soil moisture, temperature, humidity, pH level, and nutrient concentration. Thesereal-timedatapointsaretransmittedtoacloud-basedplatformforanalysisandremotemonitoring.Basedon thecollecteddata,anautomatedfertilizationsystempreciselydeliverstherequirednutrients,reducingmanualeffort and preventing excessive fertilizer use. The system utilizes wireless communication for seamless connectivity, ensuring real-time alerts and decision-making via a mobile or web-based interface. The proposed solution aims to enhancecropyield,conserveresources,andpromotesustainablefarmingbyminimizingwasteandoptimizingplant care.

Introduction

Agriculture is crucial for global food security but faces challenges such as inefficient water use, soil degradation, and improper fertilization. The integration of Internet of Things (IoT) technology with artificial intelligence (AI) offers innovative solutions by enabling real-time monitoring and automated management of farming processes.

The IoT-enabled Smart Plant Monitoring System with Automated Fertilization uses sensors to measure soil moisture, temperature, pH, nutrient levels, and environmental factors. This data is processed by a microcontroller and transmitted wirelessly to a cloud platform for analysis. Based on real-time data, the system automatically adjusts irrigation and fertilization, optimizing resource use and improving crop yields while reducing waste.

The system employs components such as soil moisture sensors, humidity sensors, light sensors, and an automated pump controlled by a relay. It also features an LCD display for local monitoring and supports remote access via mobile or web apps. Power supply is ensured through solar panels or batteries for reliable operation in remote areas.

Literature reviews highlight challenges such as sensor accuracy, connectivity issues in rural areas, power management, data security, and high deployment costs, which need addressing to improve adoption and reliability.

The implemented system demonstrated efficient water usage by irrigating only when necessary and allowed for remote monitoring. Future enhancements could include AI-driven predictive analytics, solar energy integration, and improved mobile app features to further increase sustainability and usability.

Overall, the IoT-based system offers a cost-effective, scalable, and efficient approach to precision agriculture, enhancing crop production while conserving water and fertilizers.

Conclusion

The IoT-based smart irrigation system presented in this project successfully automates plant watering using real-time sensor data. The system efficiently monitors soil moisture, temperature, humidity, and light intensity using sensors and processes the data through NodeMCU to make intelligent irrigation decisions. The integration of relay-controlled pump motors ensures that water is supplied only when needed,significantlyreducingmanualinterventionand water wastage. The LCD display provides a user- friendly interface for monitoring environmental conditions, while the cloud-based remote monitoring feature can be expanded for better accessibility. Overall, the system enhances agricultural efficiency, conserves water, and supports sustainable farming practices. The project has significant potential for further enhancements, making it a scalable and intelligent farming solution. One major improvement is the integration of AI and machine learning to analyze historical data and predict irrigation needs based on weather patterns. Additionally, incorporating cloud connectivityand mobile applications wouldenable act remotemonitoringandcontrol,improvingaccessibility for farmers. The system could also be powered using solar energy, making it more sustainable and suitable for remote agricultural areas. Furthermore, the inclusion of NPK and pH sensors would allow for automatedfertilization,enhancingsoilqualityandcrop yield. To extend its reach, LoRa or Zigbee communication modules can be integrated for long- range data transmission, making the system viable for large-scale farms. By implementing these advancements, this IoT-based smart irrigation system can evolve into a fully autonomous precision farming solution, promoting sustainable agriculture and resource efficiency.

References

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Copyright

Copyright © 2025 Rajagopalakrishnan N, Surendar V, Ramammorthi K, Muthukumar MK, Nikilshabu S, Ragu p. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.