Journal of Medical and Biological Engineering

, Volume 39, Issue 4, pp 456–469 | Cite as

Implementation of an Environmental Quality and Harmful Gases Monitoring System in Cloud

  • Chao-Tung YangEmail author
  • Shuo-Tsung Chen
  • Chih-Hung Chang
  • Walter Den
  • Chia-Cheng Wu
Original Article


The improvement of environmental quality is aligned with the betterment of life quality. Poor air quality has a greatest impact on people health, it links to cancer, long-term harm to cardiovascular and respiratory systems. Conversely, safe air quality free of harmful gases such as formaldehyde, volatile organic compounds and carbon monoxide helps to prevent disease and other health problems. The application of information technology can greatly enhance the effectiveness of ensuring good air quality. Therefore, the implementation of environmental quality and harmful gases monitoring system is beneficial to manage indoor air quality. In this work, we built an environment quality monitoring system, which can adjust the indoor air quality and monitor the concentration of formaldehyde, volatile organic compounds and carbon monoxide. If the environment comfort value is out of the standard, the system will give notification if the concentration of harmful gases exceeds the standard, and activates air ventilation and purification devices. With these real-time data, the proposed system can help people make right and timely decisions, and act in time to maintain a healthy environment in the monitored area.


Preventive healthcare Environmental comfort index Environmental Quality Monitoring System 



This work was supported in part by the Ministry of Science and Technology, Taiwan ROC, under grants number MOST 104-2221-E-029-010-MY3, MOST 106-2621-M-029-001, and MOST 106-2221-E-126-012-MY2.

Author Contributions

C-TY designed the research plan and organized the study. S-TC and WD participated in all experiments, coordinate the data analysis and contributed to the writing of the manuscript. C-CW Completed the coding.

Compliance with Ethical Standards

Conflict of interest

We declare that we have no significant competing financial, professional or personal interests that might have influenced the performance or presentation of the work described in this manuscript.


  1. 1.
    Yan, Q.-H., Yan, Z.-P., & Tan, C.-W. (2015). Design and implementation of household gas monitoring system based on zigbee+gprs communication. In 2015 International Conference on Intelligent Transportation, Big Data and Smart City, pp. 274–277.Google Scholar
  2. 2.
    Xu, J., Tang, Y.-N., & Li, X. (2016). High performance combustible gas monitoring system. In 2016 10th International Conference on Sensing Technology (ICST), pp. 1–5.Google Scholar
  3. 3.
    Jian, F., & Wei, L. (2014). Harmful gases wireless network monitoring system design. In 2014 International Symposium on Computer, Consumer and Control, pp. 551–553.Google Scholar
  4. 4.
    Liu, J., & Huang, J. L. X. (2015). Secure sharing of personal health records in cloud computing: Ciphertext policy attribute based signcryption. Future Generation Computer Systems, 52(2015), 67–76.CrossRefGoogle Scholar
  5. 5.
    Sultan, N. (2014). Discovering the potential of cloud computing in accelerating the search for curing serious illnesses. International Journal of Information Management, 34(2014), 221–225.CrossRefGoogle Scholar
  6. 6.
    Beloglazov, A., & Abawajy, R. B. J. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5), 755–768.CrossRefGoogle Scholar
  7. 7.
    Miorandi, D., & Sicari, F. D. P. I. C. S. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497–1516.CrossRefGoogle Scholar
  8. 8.
    Du, C., & Zhu, S. (2012). Research on urban public safety emergency management early warning system based on technologies for the internet of things. Procedia Engineering, 45(2012), 748–752.CrossRefGoogle Scholar
  9. 9.
    Sun, E., & Zhang, Z. L. X. (2012). The internet of things (IoT) and cloud computing (cc) based tailings dam monitoring and pre-alarm system in mines. Safety Science, 50(4), 811–815.CrossRefGoogle Scholar
  10. 10.
    Sadeghioon, A. M., & Metje, D. C. C. A. S. N. (2014). Research on urban public safety emergency management early warning system based on technologies for the internet of things. Journal of Sensor and Actuator Networks, 3(1), 64–78.CrossRefGoogle Scholar
  11. 11.
    Kim, Y., Suh, J., Cho, J. Y., Singh, S., & Seo, J. S. (2015). Development of real-time pipeline management system for prevention of accidents. International Journal of Control and Automation, 8(1), 211–226.CrossRefGoogle Scholar
  12. 12.
    LAN/MAN Standards Committee of the IEEE Computer Society, Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs), IEEE, 2003.Google Scholar
  13. 13.
    Lönn, J., & Olsson, J. (2005). Zigbee for wireless networking. Master Thesis, Linköping University.Google Scholar
  14. 14.
    “ZigBee Specification FAQ”. Zigbee Alliance. Archived from the original on 27 June 2013. Retrieved 14 June 2013.Google Scholar
  15. 15.
    Yang, C., Huang, Q., Li, Z., Liu, K., & Hu, F. (2017). Big Data and cloud computing: Innovation opportunities and challenges. International Journal of Digital Earth, 10(1), 13–53.
  16. 16.
    MySQL Cluster Architecture Overview. (2004). A mysql® technical white paper.
  17. 17.
  18. 18.
    Health Level Seven®INTERNATIONAL.
  19. 19.
    Czajkowski, K., Foster, I., & Kesselman, C. (1999). Resource co-allocation in computational grids. In Proceedings of the Eighth IEEE International Symposium on High Performance Distributed Computing (HPDC-8 99).Google Scholar
  20. 20.
    Foster, I., Kesselman, C., & Tuecke, S. (2001). The anatomy of the grid: En-abling scalable virtual organizations. International Journal of Supercomputer Ap-plications and High Performance Computing, 15(3), 200–222.CrossRefGoogle Scholar
  21. 21.
    Yang, C.-T., Shih, W.-C., Chen, L.-T., Kuo, C.-T., Jiang, F.-C., & Leu, F.-Y. (2015). Accessing medical image file with coallocation HDFS in cloud. Future Generation Computer Systems, 43–44, 61–73.Google Scholar
  22. 22.
    Yang, C.-T., Shih, W.-C., Huang, C.-L., Jiang, F.-C., & Chu, W. C.-C. (2016). On construction of a distributed data storage system in cloud. Computing, 98(1–2), 93–118.Google Scholar
  23. 23.
    ASCII (American standard code for information interchange).
  24. 24.
    Yang, C.-T., Liao, C.-J., Liu, J.-C., Den, W., Chou, Y.-C., & Tsai, J.-J. (2014). Construction and application of an intelligent air quality monitoring system for healthcare environment. Journal of Medical Systems, 38, 15.Google Scholar
  25. 25.
    Yang, C.-T., Liu, J.-C., Chen, S.-T., & Lu, H.-W. (2017). Implementation of a big data accessing and processing platform for medical records in cloud. Journal of Medical Systems, 41, 149.Google Scholar

Copyright information

© Taiwanese Society of Biomedical Engineering 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceTunghai UniversityTaichung CityTaiwan, ROC
  2. 2.College of Future, Bachelor Program in Interdisciplinary StudiesNational Yunlin University of Science and TechnologyYunlinTaiwan, ROC
  3. 3.College of Computing and InformaticsProvidence UniversityTaichung CityTaiwan, ROC
  4. 4.Department of Environmental Science and EngineeringTunghai UniversityTaichung CityTaiwan, ROC

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