Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Real Time Monitoring of Environmental Parameters Using IOT

  • 13 Accesses


A novel system to monitor environmental parameters using multilevel IOT architecture is proposed. The proposed system will monitor the changes of environmental parameters in Hyderabad region. The proposed instrumentation operates in II tier architecture in IOT. The Proposed System consists of different sensors grouped into 5 sensor nodes which are invoked by switches in the gateway or from the webpage. The sensors acquire the data and sent to a slave controller (PIC). In turn the slave controller sends the acquired data to Master controller (Raspberry pi). The Master acts as a Gateway between sensor nodes and the cloud. The data is pushed by Master onto the cloud and displayed as webpage using HTTP. The data is also received in the form of SMS through GSM. Using the proposed system few experiments were conducted on different environment and altitude. The obtained results were compared with a standard weather data. It was found that the acquired data from the system was very closer to standard weather data obtained from internet. The experiments were conducted for 15 days in June 2018 and changes in climatic conditions of Hyderabad region were studied and information was handed over to local farmers in terms of indicators which can be used as an assist to decide which crop (cotton, jowar, redgram) has to be cultivated/reaped.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17


  1. 1.

    Halder, S., &Sivakumar, G. (2017). Embedded based remote monitoring station for live streaming of temperature and humidity. In 2017 international conference electrical, electronics, communication, computer and optimization (IEEE) (pp. 284–287).

  2. 2.

    Tenzin, S., & Sriyang, S. (2017). Low cost weather station for climate-smart agriculture. In 2017 9th international conference on knowledge and smart technology (IEEE) (pp. 1–10).

  3. 3.

    Solano, G., & Lama, F. (2017). Weather station for educational purposes based on Atmeg8L. In 2017 IEEE XXIV international, electrical engineering computing (IEEE) (pp. 1–10).

  4. 4.

    Brito, R. C., & Favarim, F. (2017). Development of low cost weather station using free hardware and software. In 2017 Latin American robotics symposium (LARS) and 2017 Brazilian symposium on robotics (SBR) (IEEE) (pp. 1–10).

  5. 5.

    Kishore, R., & Mandal, S. (2016). IOT based weather station. In 2016 international conference on control, instrumentation and computational technologies (ICCICCT) (IEEE) (pp. 1–10).

  6. 6.

    Saini, H., & Thakur, A. (2016). Arduino based automatic wireless weather station with remote graphical application and alerts. In 2017 international conference on signal processing and integrated networks (IEEE) (pp. 605–609).

  7. 7.

    Kodali, R. K., & Sahu, A. (2016). An IOT based weather information prototype using WeMos. In 2016 2nd International conference on Contemporary Computing and Informatics (IEEE) (pp. 612–616).

  8. 8.

    Palle, D., Kommu, A., Kanchi, R. R. (2016). Design and development of CC3200-based cloud IOT for measuring humidity and temperature. In 2016 international conference on electrical, electronics, and optimization techniques ICEEOT (IEEE) (pp. 3116–3120).

  9. 9.

    Savic, T., & Radonjic, M. (2015). One approach to weather station design based on Raspberry Pi platform. In 2015 23rd telecommunication forum Telfor (IEEE) (pp. 623–626).

  10. 10.

    Shaout, A., Li, Y., Zhou, M., & Awad, S. (2014). Low cost embedded weather station with intelligent system. In 2014 10th international computer engineering conference (IEEE) (pp. 100–106).

  11. 11.

    Fourati, M. A., & Chebbi, W. (2014). Development of a web-based weather station for irrigation scheduling. In 2014 third international colloquium in information science and technology (IEEE) (pp. 37–42).

  12. 12.

    Mittal, Y., & Mittal, A. (2015). Correlation among environmental parameters using an online smart weather station system. In 2015 annual IEEE India conference (IEEE) (pp. 1–6).

  13. 13.

    Munandar, A., & Fakhrurroja, H. (2017). Design of real-time weather monitoring system based on mobile application using automatic weather station. In 2017 2nd international conference on aotomation, cognitive science, optics, micro electro-mechanical system and information technology (IEEE) (pp. 44–47).

  14. 14.

    Ghosh, A., & Srivastava, B. (2013). Solar powered weather station and rain detector. In 2013 Texas instruments India educators conference (IEEE) (pp. 131–134).

  15. 15.

    Ruano, A. E., & Mestre, G. (2015). A neural-network based intelligent weather station. In 2015 IEEE 9th international symposium on intelligent signal processing (WISP) proceedings (IEEE) (pp. 1–6).

  16. 16.

    Catelain, M., & Ciani, L. (2016). Measurement and characterization of air temperature sensors for weather stations. In 2016 IEEE international instrumentation and measurement technology conference proceedings (IEEE) (pp. 1–7).

  17. 17.

    Quarati, A., & Clematis, A. (2017). Integrating hetrogeneous weather-sensors data into a smart-city app. In 2017 international conference on high performance computing and simulation (IEEE) (pp. 152–159).

  18. 18.

    Malik, A. H., & Jalal, A. (2017). Smart city IOT based weather monitoring system. International Journal of Engineering Science and Computing,7(5), 12123–12128.

  19. 19.

    Susmitha, P., & Sowmyabala, G. (2014). Design and implementation of weather monitoring and controlling system. International Journal of Computer Applications,97, 19–22.

  20. 20.

    Goudal, K. C., & Preetham, V. R. (2014). Microcontroller based real time weather monitoring device with GSM. International Journal of Science, Engineering and Technology Research,3(7), 1960–1963.

  21. 21.

    Patil, K., & Mhatre, M. (2016). Weather monitoring system using microcontroller. International Journal on Recent and Innovation Trends Computing and Communication,4(1), 78–80.

  22. 22.

    Katyal, A., & Yadav, R. (2016). Wireless Arduino based weather station. International Journal of Advanced Research in Computer and Communication Engineering,5(4), 274–276.

  23. 23.

    Baste, P., & Dighe, D. D. (2017). Low cost weather monitoring station using Raspberry Pi. International Research Journal of Engineering and Technology,4(5), 3184–3189.

  24. 24.

    VivekBabu, K., & Anideep, K. (2017). Weather forecasting using Raspberry Pi with Internet of Things (IOT). ARPN Journal of Engineering and Applied Sciences,12(17), 5129–5134.

  25. 25.

    Devarakonda Uma, K., & Kumar, R. (2016). Design of weather monitoring system using Raspberry Pi and Arduino. International Journal of Advanced Technology and Innovative Research,8(24), 4633–4638.

Download references

Author information

Correspondence to Vasanth Kishorebabu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kishorebabu, V., Sravanthi, R. Real Time Monitoring of Environmental Parameters Using IOT. Wireless Pers Commun (2020). https://doi.org/10.1007/s11277-020-07074-y

Download citation


  • IOT
  • Multilevel IOT
  • Raspberry Pi-3
  • PIC microcontroller
  • Sensors
  • GSM
  • Webpage