Skip to main content
SpringerLink
Log in

Research and Design of Intelligent Gas Concentration Monitoring and Alarming Instrument Based on PIC Single Chip Microcomputer

  • Conference paper
  • First Online:
Artificial Intelligence and Security (ICAIS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1253))

Included in the following conference series:

  • 1064 Accesses

Abstract

In order to automatically monitor the gas concentration in the mine in real time, ensure the safety of coal mine production and protect the life safety of employees, an intelligent gas concentration monitoring and alarm instrument based on PIC single-chip microcomputer is designed. The equipment uses LXK-3 sensor to detect the gas concentration in the mine, and transmits the collected data to the single-chip microcomputer in the form of voltage; uses the single-chip microcomputer direct drive mode to dynamically display the gas concentration, when the gas concentration exceeds the limit, timely sends out the sound light alarm signal; realizes the wireless transmission of the communication data between the upper and lower computers by using nRF2401. The equipment has the characteristics of stable control, real-time communication and strong adaptability, which is of great significance for the real-time monitoring of gas concentration in the mine.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Blanco-Novoa, O., Fernández-Caramés, T., Fraga-Lamas, P., et al.: A cost-effective IoT system for monitoring indoor radon gas concentration. Sensor 18(7), 2198–2205 (2018)

    Article  Google Scholar 

  2. Sabilla, S.I., Sarno, R., Siswantoro, J.: Estimating gas concentration using artificial neural network for electronic nose. Procedia Comput. Sci. 124, 181–188 (2017)

    Article  Google Scholar 

  3. Zhao, Q., Zhou, W., Shi, L.: The design of gas concentration detection system based on acoustic relaxation method. Procedia Comput. Sci. 131, 556–563 (2018)

    Article  Google Scholar 

  4. Balch, W.M., Bowler, B.C., Drapeau, D.T., et al.: Vertical distributions of coccolithophores, PIC, POC, biogenic silica, and chlorophyll a throughout the global ocean: vertical distributions of phytoplankton in the global ocean. Glob. Biogeochem. Cycles 32(7), 56–68 (2017)

    Google Scholar 

  5. Hou, L., Wang, D., Du, B., et al.: Gas concentration detection via multi-channeled air sampling method. Sens. Rev. 37(2), 187–195 (2017)

    Article  Google Scholar 

  6. Erhai, G.: Research on gas measurement sensor based on temperature compensation. Mech. Manag. Dev. 34(03), 129–130 (2019)

    Google Scholar 

  7. Su, J., Sheng, Z., Xie, L., Li, G., Liu, A.: Fast splitting based tag identification algorithm for anti-collision in UHF RFID system. IEEE Trans. Commun. 67(3), 2527–2538 (2019)

    Article  Google Scholar 

  8. Su, J., Sheng, Z., Leung, V.C.M., Chen, Y.: Energy efficient tag identification algorithms for RFID: survey, motivation and new design. IEEE Wirel. Commun. 26(3), 118–124 (2019)

    Article  Google Scholar 

  9. Gao, L.: Discussion on compulsory verification of non gas combustible gas alarm. Brand Stand. 06, 68–70 (2018)

    Google Scholar 

  10. Zhanfei, L., Hao, L., Weifeng, X., Shuyang, L.: Development of transformer gas fast judgment device. Ningxia Electr. Power 03, 44–47 (2018)

    Google Scholar 

  11. He, J., Chen, Y., Zou, Y.: Research on app service based on hand-held infrared gas detection. Coal Technol. 37(02), 151–153 (2018)

    Google Scholar 

  12. Shihua, T.: Design of coal mine gas detection sensor alarm based on single chip microcomputer. Sci. Technol. Innov. Appl. 36, 77–78 (2016)

    Google Scholar 

  13. Su, J., Sheng, Z., Liu, A., Han, Y., Chen, Y.: A group-based binary splitting algorithm for UHF RFID anti-collision systems. IEEE Trans. Commun. 68(2), 998–1012 (2019)

    Article  Google Scholar 

  14. Hua, F., Nannan, S., Junjie, L.: Research on double circuit gas concentration instrument based on constant temperature harmonic detection. J. Sens. Technol. 29(10), 1493–1499 (2016)

    Google Scholar 

  15. Lu, J., Zhang, L., Chen, L.: Influence of underground gas composition change on optical gas detector. J. Shanxi Datong Univ. (Nat. Sci. Ed.) 32(04), 60–64 (2016)

    Google Scholar 

  16. Xiongfei, C., Keqiang, Z., Ningfang, Z.: Dual wavelength dual optical path DFB LD gas detection technology based on PLC. J. Inner Mongolia Normal Univ. (Chin. Vers. Nat. Sci.) 43(06), 719–722 (2014)

    Google Scholar 

  17. Fumin, C.: Research on the application of ultrasonic gas flowmeter in online flow detection of coal mine gas. Low Carbon World 07, 119–120 (2014)

    Google Scholar 

  18. Qiang, L.: Infrared gas detector based on spectral difference absorption principle. Coal Mine Saf. 44(11), 111–113 (2013)

    Google Scholar 

  19. Fu, H., Shu, D., Wang, X.: Research on gas detection method based on adaptive stochastic resonance. Piezoelectric Acoustooptic, 35(04), 467–472+477 (2013)

    Google Scholar 

  20. Hua, F., Dehao, Q., Jihui, C.: Gas detection research based on laser ultrasonic surface wave detection. Sens. Microsyst. 29(07), 50–52 (2010)

    Google Scholar 

  21. Ma Yong, F., Jiang, W.Y.: New gas sensor based on integral ball algorithm. Instr. Technol. Sens. 07, 13–15 (2010)

    Google Scholar 

  22. Zhang, F.: Design of gas detector based on ADuC834 single chip computer. Ind. Instr. Autom. Device 03, 64–68 (2009)

    Google Scholar 

Download references

Acknowledgments

This work was supported by the youth backbone teachers training program of Henan colleges and universities under Grant No. 2016ggjs-287, and the project of science and technology of Henan province under Grant No. 172102210124, and the Key Scientific Research projects in Colleges and Universities in Henan Grant No. 18B460003.

Author information

Authors and Affiliations

  1. Henan Mechanical and Electrical Vocational College, Xinzheng, 451191, China

    Xiaokan Wang & Qiong Wang

Authors
  1. Xiaokan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaokan Wang .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Jinwei Wang

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, X., Wang, Q. (2020). Research and Design of Intelligent Gas Concentration Monitoring and Alarming Instrument Based on PIC Single Chip Microcomputer. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Communications in Computer and Information Science, vol 1253. Springer, Singapore. https://doi.org/10.1007/978-981-15-8086-4_45

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-8086-4_45

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8085-7

  • Online ISBN: 978-981-15-8086-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation