Skip to main content
SpringerLink
Log in

Implementation of Real-Time Water Quality Monitoring Based on Java and Internet of Things

  • Chapter
  • First Online:
Integrating Blockchain and Artificial Intelligence for Industry 4.0 Innovations

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

  • 221 Accesses

Abstract

Water constitutes an indispensable element that assures our existence. In fact, the main part of the human body is formed by water (more than 60%). In addition, all living beings such as plants, animals, and vegetables require water. However, in recent days, this vital resource is condemned by pollutant due to many factors. Consequently, implementation of real-time water quality index monitoring can play a significant role to manage water quality. Besides, it helps water manager to alert users if water with poor quality was sensed. In this study, our aim is to develop a new application for real-time monitoring water quality index-based programming language Java, and the new technology Internet of Things. The experimental validation demonstrates that our developed application can sense water parameters and then computes WQI. Then, users can visualize the measurement ether in graphics or in standard table.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Westall, F., & Brack, A. (2018). The importance of water for life. Space Science Reviews, 214(2), 1–23.

    Article  Google Scholar 

  2. Azrour, M., Mabrouki, J., Fattah, G., Guezzaz, A., & Aziz, F. (2022). Machine learning algorithms for efficient water quality prediction. Modeling Earth Systems and Environment, 8(2), 2793–2801.

    Article  Google Scholar 

  3. Mabrouki, J., Azrour, M., Farhaoui, Y., & El Hajjaji, S. (2019). Intelligent system for monitoring and detecting water quality. In International conference on big data and networks technologies (pp. 172–182). Springer.

    Google Scholar 

  4. Fattah, G., Mabrouki, J., Ghrissi, F., Azrour, M., & Abrouki, Y. (2022). Multi-sensor system and Internet of Things (IoT) technologies for air pollution monitoring. In Futuristic research trends and applications of Internet of Things (pp. 101–116). CRC Press.

    Chapter  Google Scholar 

  5. Guezzaz, A., Benkirane, S., Mohyeddine, M., Attou, H., & Douiba, M. (2022). A lightweight hybrid intrusion detection framework using machine learning for Edge-Based IIoT Security. International Arab Journal of Information Technology, 19(5), 822–830.

    Article  Google Scholar 

  6. Douiba, M., Benkirane, S., Guezzaz, A., & Azrour, M. (2022). An improved anomaly detection model for IoT security using decision tree and gradient boosting. The Journal of Supercomputing, 79, 3392–3411.

    Article  Google Scholar 

  7. Benkirane, S., et al. (2023). Adapted speed system in a road bend situation in VANET environment. Computers, Materials and Continua, 74(2), 3781–3794. https://doi.org/10.32604/cmc.2023.033119

    Article  Google Scholar 

  8. Kim, T., Ramos, C., & Mohammed, S. (2017). Smart city and IoT. Future Generation Computer Systems, 76, 159–162. https://doi.org/10.1016/j.future.2017.03.034

    Article  Google Scholar 

  9. Aliero, M. S., Qureshi, K. N., Pasha, M. F., & Jeon, G. (2021). Smart Home Energy Management Systems in Internet of Things networks for green cities demands and services. Environmental Technology and Innovation, 22, 101443. https://doi.org/10.1016/j.eti.2021.101443

    Article  Google Scholar 

  10. Benda, R., Fagiani, T., & Giovachini, P. (2018). La ville et l’internet des objets. Internet des Objets, 5.

    Google Scholar 

  11. Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89, 80–91. https://doi.org/10.1016/j.cities.2019.01.032

    Article  Google Scholar 

  12. Ahlgren, B., Hidell, M., & Ngai, E. C.-H. (2016). Internet of Things for smart cities: Interoperability and open data. IEEE Internet Computing, 20(6), 52–56. https://doi.org/10.1109/MIC.2016.124

    Article  Google Scholar 

  13. Azrour, M., Mabrouki, J., & Chaganti, R. (2021). New efficient and secured authentication protocol for remote healthcare systems in cloud-IoT. Security and Communication Networks, 2021, 1–12.

    Google Scholar 

  14. Tian, S., Yang, W., Grange, J. M. L., Wang, P., Huang, W., & Ye, Z. (2019). Smart healthcare: Making medical care more intelligent. Global Health Journal, 3(3), 62–65. https://doi.org/10.1016/j.glohj.2019.07.001

    Article  Google Scholar 

  15. Mohanty, S., Mohanty, S., & Pattnaik, P. K. (2020). Smart healthcare analytics: An overview. In P. K. Pattnaik, S. Mohanty, & S. Mohanty (Eds.), Smart healthcare analytics in IoT enabled environment (pp. 1–8). Springer International Publishing. https://doi.org/10.1007/978-3-030-37551-5_1

    Chapter  Google Scholar 

  16. Mabrouki, J., et al. (2022). Smart system for monitoring and controlling of agricultural production by the IoT. In IoT and smart devices for sustainable environment (pp. 103–115). Springer.

    Chapter  Google Scholar 

  17. Azrour, M., Ouanan, M., Farhaoui, Y., & Guezzaz, A. (2018). Security analysis of Ye et al. authentication protocol for Internet of Things. In International conference on big data and smart digital environment (pp. 67–74). Springer.

    Google Scholar 

  18. Mabrouki, J., Azrour, M., & Hajjaji, S. E. (2021). Use of internet of things for monitoring and evaluating water’s quality: A comparative study. International Journal of Cloud Computing, 10(5–6), 633–644.

    Article  Google Scholar 

  19. Boutahir, M. K., Farhaoui, Y., & Azrour, M. (2022). Machine learning and deep learning applications for solar radiation predictions review: Morocco as a case of study. In S. G. Yaseen (Ed.), Digital economy, business analytics, and big data analytics applications (Vol. 1010, pp. 55–67). Springer International Publishing. https://doi.org/10.1007/978-3-031-05258-3_6

    Chapter  Google Scholar 

  20. Douiba, M., Benkirane, S., Guezzaz, A., & Azrour, M. (2022). Anomaly detection model based on gradient boosting and decision tree for IoT environments security. Journal of Reliable Intelligent Environments, 1–12. https://doi.org/10.1007/s40860-022-00184-3

  21. Boutahir, M. K., Farhaoui, Y., Azrour, M., Zeroual, I., & El Allaoui, A. (2022). Effect of feature selection on the prediction of direct normal irradiance. Big Data Mining and Analytics, 5(4), 309–317. https://doi.org/10.26599/BDMA.2022.9020003

    Article  Google Scholar 

  22. Azrour, M., Mabrouki, J., Guezzaz, A., & Kanwal, A. (2021). Internet of Things security: Challenges and key issues. Security and Communication Networks, 2021, 1–11. https://doi.org/10.1155/2021/5533843

    Article  Google Scholar 

  23. Guezzaz, A., Benkirane, S., & Azrour, M. (2022). A novel anomaly network intrusion detection system for Internet of Things security. In IoT and smart devices for sustainable environment (pp. 129–138). Springer.

    Chapter  Google Scholar 

  24. Guezzaz, A., Benkirane, S., Azrour, M., & Khurram, S. (2021). A reliable network intrusion detection approach using decision tree with enhanced data quality. Security and Communication Networks, 2021, 1–8. https://doi.org/10.1155/2021/1230593

    Article  Google Scholar 

  25. Guezzaz, A., Asimi, Y., Azrour, M., & Asimi, A. (2021). Mathematical validation of proposed machine learning classifier for heterogeneous traffic and anomaly detection. Big Data Mining and Analytics, 4(1), 18–24. https://doi.org/10.26599/BDMA.2020.9020019

    Article  Google Scholar 

  26. Mabrouki, J., Azrour, M., & El Hajjaji, S. (2021). Use of Internet of Things for monitoring and evaluation water’s quality: Comparative study. International Journal of Cloud Computing, 10, 633–644.

    Article  Google Scholar 

  27. Zhang, F., Yan, X., & Li, J. (2021). Embedded web server for hospital and clinical nursing analysis of cataract anti-inflammatory drugs. Microprocessors and Microsystems, 81, 103692. https://doi.org/10.1016/j.micpro.2020.103692

    Article  Google Scholar 

  28. Shuping, X., Hongqing, Y., Fan, Y., & Yajuan, W. (2021). The design of remote control system based on the embedded web server. International Journal of Advanced Network, Monitoring and Controls, 6(1), 41–49.

    Article  Google Scholar 

  29. Dimitrievski, A., et al. (2021). Rural healthcare IoT architecture based on low-energy LoRa. International Journal of Environmental Research and Public Health, 18(14), 7660.

    Article  Google Scholar 

  30. de Albuquerque, B. H. C., Pinto, F. R., & Chagas, L. d. O. (2019). Home automation using Arduino platform on an embedded server. International Journal of Advanced Engineering Research and Science, 6(11), 158–162. https://doi.org/10.22161/ijaers.611.23

    Article  Google Scholar 

  31. Senthilkumar, R., Venkatakrishnan, P., & Balaji, N. (2020). Intelligent based novel embedded system based IoT enabled air pollution monitoring system. Microprocessors and Microsystems, 77, 103172. https://doi.org/10.1016/j.micpro.2020.103172

    Article  Google Scholar 

  32. Snoussi, A., Guerbaoui, M., Ed-dahhak, A., & Lachhab, A. (2017). Embedded web server implementation for real time greenhouse monitoring. In Proceedings of the international conference: ICOA’2017 (pp. 105–108). Éditions Universitaires Européennes.

    Google Scholar 

  33. da Silva Almeida, T., Roledo, L. B., de Carvalho, R. L., & da Silva, W. G. (2020). Embedded server to automatic control of wireless transducer network for irrigation based on Internet of Things. Revista Sítio Novo, 4(2), 6–18.

    Article  Google Scholar 

  34. Telagam, N., Kandasamy, N., Nanjundan, M., & Thotakuri, A. (2017). Smart sensor network based industrial parameters monitoring in IOT environment using virtual instrumentation server. International Journal of Online Engineering, 13(11), 111. https://doi.org/10.3991/ijoe.v13i11.7630

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IDMS Team, Department of Computer Science, Faculty of Sciences and Techniques of Errachidia, Moulay Ismail University, Meknes, Morocco

    Mourade Azrour

  2. Laboratory of Spectroscopy, Molecular Modelling, Materials, Nanomaterial, Water and Environment, CERNE2D, Mohammed V, University in Rabat, Faculty of Science, Rabat, Morocco

    Jamal Mabrouki

  3. Technology Higher School, Cadi Ayyad University, Marrakesh, Morocco

    Azidine Guezzaz & Said Benkirane

  4. LIMA Laboratory, Computer Sciences Department, National School of Applied Sciences, Ibn Zohr University, Agadir, Morocco

    Hiba Asri

Authors
  1. Mourade Azrour
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jamal Mabrouki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Azidine Guezzaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Said Benkirane
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hiba Asri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mourade Azrour .

Editor information

Editors and Affiliations

  1. School of Science, Engineering, and Technology, RMIT University, Hanoi, Vietnam

    Sam Goundar

  2. Department of Computer Science Engineering, Vels Institute of Science, Technology, and Advanced Studies (VISTAS)Pallavaram, Chennai, Tamil Nadu, India

    R. Anandan

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Azrour, M., Mabrouki, J., Guezzaz, A., Benkirane, S., Asri, H. (2024). Implementation of Real-Time Water Quality Monitoring Based on Java and Internet of Things. In: Goundar, S., Anandan, R. (eds) Integrating Blockchain and Artificial Intelligence for Industry 4.0 Innovations. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-35751-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-35751-0_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35750-3

  • Online ISBN: 978-3-031-35751-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation