Skip to main content
SpringerLink
Log in

Wolfram’s cellular automata model for unhealthy gas leakage detection

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

The Elementary Cellular Automata (ECA) introduced by Stephan Wolfram, is a powerful universal computing tool which can be explored for design solutions to a wide variety range of physical, environmental, biological as well as realtime applications. Analysis and synthesis of Null Boundary Cellular Automata (NBCA) reveals it’s suitability in environmental toxication prediction and detection. The novelty of this research work is to propose an innovative significant alternative to Artificial Intelligence-Machine learning (AI-ML) solution using cellular automata (CA) to protect our environment against contamination with unhealthy gas leakage. The design is developed around single-length cycle two attractor cellular automata (TACA). The work provides a realtime solution in a power-efficient manner having a minimum delay but with 100% efficiency.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Algorithm 1
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Not Applicable.

References

  1. Kumar MP et al (2009) Bhopal Gas Tragedy: review of clinical and experimental findings after 25 years. Int J Occupational Med Environ Health 22(3):193–202

    Google Scholar 

  2. Sharma T.P. ,Solanki A, Jain T (2023)et al. Wi-Fi based quadcopter drone with battery monitoring and optimization using crazyflie platform. Int J Inf Tecnol https://doi.org/10.1007/s41870-023-01639-3

  3. Verma P, Bakthula R (2024) Empowering fire and smoke detection in smart monitoring through deep learning fusion. Int J Inf Tecnol 16:345–352. https://doi.org/10.1007/s41870-023-01630-y

    Article  Google Scholar 

  4. Qian F, Chen L, Li J, Ding C, Chen X, Wang J (2019) Direct Prediction of the Toxic Gas Diffusion Rule in a Real Environment Based on LSTM. Int J Environ Res Publ Health 16:2133. https://doi.org/10.3390/ijerph16122133

    Article  Google Scholar 

  5. Tsoukas V, Gkogkidis A, Boumpa E, Papafotikas S, Kakarountas A (2023) A Gas leakage detection device based on the technology of TinyML. Technologies 11:45. https://doi.org/10.3390/technologies11020045

    Article  Google Scholar 

  6. Yan H, Rahayu H, Yusnita (2014) Design and Development of Gas Leakage Monitoring System using Arduino and ZigBee. 10.11591/eecsi.1.404

  7. Yadawad R, Kulkarni UP (2023) Model view controller (MVC) architecture and client-to-client file transfer protocol with binarized spiking neural network for building a smart home appliances control in IoT. Int J Inf Tecnol 15:3189–3200. https://doi.org/10.1007/s41870-023-01349-w

    Article  Google Scholar 

  8. Nahid SI, Development of a Smart Automatic Gas Leakage Detector and Alarming System, et al (2021) IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). Vancouver, BC, Canada 2021:0789–0795. https://doi.org/10.1109/IEMCON53756.2021.9623207

  9. Varma A, Prabhakar S , Jayavel K (2017) Gas Leakage Detection and Smart Alerting and prediction using IoT. In: 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), Chennai, India, pp. 327-333, https://doi.org/10.1109/ICCCT2.2017.7972304.

  10. Sarkar C, Abbasi SA (2006) Cellular automata-based forecasting of the impact of accidental fire and toxic dispersion in process industries, Journal of Hazardous Materials, Volume 137, Issue 1, Pages 8-30, ISSN 0304-3894, https://doi.org/10.1016/j.jhazmat.2006.01.081

  11. Martin O, Odlyzko AM, Wolfram S (1984) Algebraic properties of cellular automata. Commun Math Phys 93:219–258

    Article  MathSciNet  Google Scholar 

  12. Das S, Mukherjee S, Naskar M, Sikdar BK (2009) Characterization of single cycle CA and its application in pattern classification. Electron Notes Theoretical Comput Sci 52:181–203

    Article  MathSciNet  Google Scholar 

  13. Choudhury, P. P , Sahoo S, Hasssan S, Basu S, Ghosh D, Kar Debarun, Ghosh A (2009) Avijit Ghosh 8 , Amal K. Ghosh: Classification of Cellular Automata Rules Based on Their Properties, Computer Science, Mathematics,

  14. Sarkar S, Saha S, Sikdar BK (2017) Multi-bit fault tolerant design for resistive memories through dynamic partitioning. In: 2017 IEEE East-West Design & Test Symposium (EWDTS), Novi Sad, 2017, pp. 1-6, https:// doi.org /10.1109/EWDTS.2017.8110053

  15. Das B, Dalui M, Kamilya S, Das S, Biplab K (2013) Sikdar: Synthesis of Periodic Boundary CA for Efficient Data Migration in Chip-Multiprocessors. IEEE

  16. Chaudhuri PP, Chowdhury D, Nandi SR, Chatterjee S (1997) Additive Cellular Automata—Theory and Applications, (1). IEEE Computer Society Press, California, USA

    Google Scholar 

  17. Kari J (2005) Reversible cellular automata, June 2005, Lecture Notes in Computer Science (3572):2-23, https://doi.org/10.1007/11505877_5.

  18. Sarkar S, Ghosh M, Sikdar BK, Saha M (2020) Periodic boundary cellular automata based wear leveling for resistive memory. IAENG Int J Comput Sci 47(2):310–321

    Google Scholar 

  19. Sarkar S, Sikdar BK, Saha M (2021) Cellular automata-based multi-bit stuck-at-fault diagnosis for resistive memory, http://www.jzus.zju.edu.cn/iparticle.php?doi=10.1631/FITEE.2100255

  20. Sarkar S Multi-bit stuck-at fault recovery system with error correction pointer. Proc 3rd Int Conf on Communication and Electronics Systems, p.528-533. https://doi.org/10.1109/CESYS.2018.8723890

  21. Jacek M, Zarzycki CH, Wiesław Palczewski ŁA, Kardasz P (2018) A cellular automata-based simulation tool for real fire accident prevention, Mathematical Problems in Engineering, vol. 2018, Article ID 3058241: 12 https://doi.org/10.1155/2018/3058241

  22. Cao H, Li T, Li S et al (2017) An integrated emergency response model for toxic gas release accidents based on cellular automata. Ann Oper Res 255:617–638. https://doi.org/10.1007/s10479-016-2125-4

    Article  MathSciNet  Google Scholar 

  23. Dascalu Monica (2016) Cellular Automata Hardware Implementations-an Overview. Romanian J Inform Sci Technol 19:360–368

    Google Scholar 

  24. Sarkar S, Saha M (2023). Synthesis of elementary cellular automata for targeted cache applications. In: Singh, M., Tyagi, V., Gupta, P., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2023. Communications in Computer and Information Science, vol 1848. Springer, Cham. https://doi.org/10.1007/978-3-031-37940-6_10

  25. Sutapa S, Saha M (2021) Wolfram’s cellular automata model in health informatics. Comput Intell Healthcare Inform : 179-192. Wiley online library

  26. Ding J, Wang J, Yuan N, Pan Q (2011) The monitoring system of leakage accidents in crude oil pipeline based on ZigBee technology. In: 2011 second international conference on mechanic automation and control engineering, Inner Mongolia, China, pp. 1774-1777, https://doi.org/10.1109/MACE.2011.5987303.

  27. Kebande VR, Karie NM, Ikuesan RA (2021) Real-time monitoring as a supplementary security component of vigilantism in modern network environments. Int J Inf Tecnol 13:5–17. https://doi.org/10.1007/s41870-020-00585-8

    Article  Google Scholar 

  28. Vaidya A, Joshi SM (224) Novel phase adjournment data capturing technique for a mobile object in wireless sensor network. Int. j. inf. tecnol. 16, 993-1004 . https://doi.org/10.1007/s41870-023-01636-6

  29. Cao H, Fan T, Li S (2016). CA-based dynamic risk assessment of toxic gas leakage accidents. 36. 253-262. 10.12011/1000-6788(2016)01-0253-10

  30. Praveenchandar J, Vetrithangam, D, Kaliappan S, Karthick M, Naresh Kumar Pegada Pravin P, Patil S, Govinda Rao Syed Umar (2022) IoT-Based Harmful Toxic Gases Monitoring and Fault Detection on the Sensor Dataset Using Deep Learning Techniques, Scientific Programming, vol. 2022, Article ID 7516328, 11 pages. https://doi.org/10.1155/2022/7516328

  31. Ke Wang (2017) The simulation system of hazardous chemical gas diffusion in plant based on cellular automata. Chem Eng Trans 59:661–666

    Google Scholar 

  32. Nnokwe CC, Ubochi BC, Onwuzuruike KV (2020) Development of a Gas Leakage Detection System. J Electr Eng Electron Control Comput Sci JEEECCS 6(22):23–28

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Neotia University School of Science & Technology, Kolkata, India

    Sutapa Sarkar, Mourjya Chatterjee, Swarnava Saha & Shuvendu Chakraborty

  2. CST, Brainware University, Kolkata, India

    Sutapa Sarkar

  3. Xavier Business School, St. Xavier′s University, Kolkata, India

    Shuvendu Chakraborty

Authors
  1. Sutapa Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mourjya Chatterjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Swarnava Saha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shuvendu Chakraborty
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sutapa Sarkar.

Ethics declarations

Conflict of interest

Authors declare that they do not have any Conflict of interest with directly or indirectly related to this work submitted.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarkar, S., Chatterjee, M., Saha, S. et al. Wolfram’s cellular automata model for unhealthy gas leakage detection. Int. j. inf. tecnol. (2024). https://doi.org/10.1007/s41870-024-01904-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s41870-024-01904-z

Keywords

Search

Navigation