Iot Cloud for Hydroponics System and Agriculture

Year : 2024 | Volume : | : | Page : –
By

Khadeejath Ramzila,

Mahammad Ansar,

Mohammed Afheez,

Mohammed Fazil,

Mohammed Salman,

  1. Student Department of Computer Science and Engineering, P A College of Engineering, Mangalore Karnataka India
  2. Student Department of Computer Science and Engineering, P A College of Engineering, Mangalore Karnataka India
  3. Student Department of Computer Science and Engineering, P A College of Engineering, Mangalore Karnataka India
  4. Student Department of Computer Science and Engineering, P A College of Engineering, Mangalore Karnataka India
  5. Student Department of Computer Science and Engineering, P A College of Engineering, Mangalore Karnataka India

Abstract

The integration of Internet of Things (IoT) technology into hydroponic systems has revolutionized modern agriculture, enabling more efficient resource utilization and higher crop yields. This project offers an Internet of Things cloud solution intended to handle the difficulties in hydroponic system management and monitoring. By leveraging sensors to collect essential data such as temperature, humidity, pH levels, nutrient concentration, and light intensity, this solution facilitates real-time data transmission to a cloud- based platform. The platform stores, analyses, and visualizes the data, providing farmers with actionable insights through a user-friendly web or mobile interface. Key features include automated alerts for critical parameters, which enable timely interventions to prevent crop damage, and remote management capabilities, empowering farmers to optimize crop growth and resource use. This IoT cloud solution enhances the efficiency and productivity of hydroponic farming, contributing to more sustainable agricultural practices.

Keywords: IoT, hydroponic systems, agriculture, humidity, thingspeak

How to cite this article: Khadeejath Ramzila, Mahammad Ansar, Mohammed Afheez, Mohammed Fazil, Mohammed Salman. Iot Cloud for Hydroponics System and Agriculture. Journal of Microelectronics and Solid State Devices. 2024; ():-.
How to cite this URL: Khadeejath Ramzila, Mahammad Ansar, Mohammed Afheez, Mohammed Fazil, Mohammed Salman. Iot Cloud for Hydroponics System and Agriculture. Journal of Microelectronics and Solid State Devices. 2024; ():-. Available from: https://journals.stmjournals.com/jomsd/article=2024/view=167833



References

  • Jan et al., “Hydroponics – A Review,” Int. J. Curr. Microbiol. Appl.Sci., vol. 9, no. 8, pp. 1779–1787, 2020.
  • Rayhana, G. Xiao, and Z. Liu, “Internet of Things EmpoweredSmart Greenhouse Farming,” IEEE Journal of Radio Frequency Identification, vol. 4, no. 3, pp. 195–211, 2020.
  • Andrianto, Suhardi, and A. Faizal, “Performance evaluation of low cost iot based chlorophyll meter,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 3, pp. 956–963, 2020
  • Ali, S. M. Ibrahim, and Bijay-Singh, “Wheat grain yield and nitrogen uptake prediction using at Leaf and GreenSeeker portable optical sensors at jointing growth stage,” Information Processing in Agriculture, vol. 7, no. 3, pp. 375– 383, 2020
  • Ahmad, S.E. Shariffudin, A.F. Ramli, S.M. M. Maharum et al.”Intelligent Plant Monitoring System Via IoT and Fuzzy System”, 2021 IEEE 7th International Conference on Smart Instrumentation, Measurement Applications (ICSIMA), 2021.
  • Li, Zhu, X. Chu, and H. Fu, “Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture,” Journal of Sensors, Article ID 4398061, 2020.
  • Li, Z. Ma, J. Zheng, Y. Liu, L. Zhu andZhou, “An Effective Edge-Assisted Data Collection Approach for Critical Events in the SDWSN-Based Agricultural Internet of Things,” Electronics vol. 9, ID.907, 2020.
  • K. Dwivedi, A. K. Rai and R. Kumar, “Outlier Detection in Wireless Sensor Networks using Machine Learning Techniques: A Survey,” 2020 International Conference on Electrical and Electronics Engineering (ICE3), Gorakhpur, India, 2020, pp. 316-321.
  • Munasinghe, E. W. Patton, and O. Seneviratne, “IoT Application Development Using MIT App Inventor to Collect and Analyze Sensor Data,” Proceedings – 2019 IEEE International Conference on Big Data, Big Data 2019, pp. 6157–6159, 2019.
  • Nunes ML, Pereira AC, Alves AC. Smart products development approaches for Industry 4.0. Procedia manufacturing. 2017 Jan 1;13:1215-22.

Ahead of Print Subscription Original Research
Volume
Received July 3, 2024
Accepted July 12, 2024
Published July 28, 2024

Check Our other Platform for Workshops in the field of AI, Biotechnology & Nanotechnology.
Check Out Platform for Webinars in the field of AI, Biotech. & Nanotech.