iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://unpaywall.org/10.1007/978-981-97-0827-7_9
A New and Efficient Dormitory Management System | SpringerLink
Skip to main content

A New and Efficient Dormitory Management System

  • Conference paper
  • First Online:
Applied Intelligence (ICAI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2015))

Included in the following conference series:

  • 286 Accesses

Abstract

Today’s information trend is unstoppable, and the manual management mode of college dormitory management cannot meet the trend of increasing demand for dormitories year by year. It not only wastes many manpower and material resources, but also is easy to appear many unnecessary low-level errors. A system about student dormitory management not only saves many unnecessary repeated working time, but also reduces the generation of various low - level errors in information management, which makes the grasp and operation of information more convenient. The system adopts B/S architecture (browser / server architecture), mainly based on the development and implementation of JAVA language. The system has 3 user roles: administrator, student, and host administrator. The functional module of the administrator includes user management, student management, dormitory management, grade management and authority management, which can realize the management of dormitory information and other information. Students’ function module includes student personal details management, online pre-selection dormitory and view of absence records, students can pre-select the dormitory, and view personal information and absence information. The dormitory manager function module includes dormitory management, pre-selection setting and absence management, dormitory details management and absence management, and pre-selection time settings. After testing, the college dormitory management system can effectively realize the above functions and is interface friendly and easy to operate.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
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

Similar content being viewed by others

References

  1. Yang, Y., Chen, S.: Design and implementation of college dormitory management system. In: 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), pp. 1–5 (2022)

    Google Scholar 

  2. Yang, C.-Y., et al.: Design of high school dormitory management system based on IoT technology. In: 2021 13th International Conference on Wireless Communications and Signal Processing (WCSP), pp. 1–5 (2021)

    Google Scholar 

  3. Peng, Z., Liu, T., Mai, L.: Design and implementation of dormitory management system based on SSM framework. In: 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS), pp. 321–325 (2020)

    Google Scholar 

  4. Yuan, L., et al.: Nonconvex penalty based low-rank representation and sparse regression for eQTL mapping. IEEE/ACM Trans. Comput. Biol. Bioinf. 14, 1154–1164 (2016)

    Article  Google Scholar 

  5. Yuan, L., et al.: ICircDA-NEAE: accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction. PLoS Comput. Biol. 19, e1011344 (2023)

    Article  Google Scholar 

  6. Zeng, X., Deng, L.: Research on college counselor training system based on computer virtual reality technology. In: 2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS), pp. 1323–1326 (2022)

    Google Scholar 

  7. Yuan, L., et al.: Integration of multi-omics data for gene regulatory network inference and application to breast cancer. IEEE/ACM Trans. Comput. Biol. Bioinf. 16, 782–791 (2018)

    Article  Google Scholar 

  8. Yuan, L., et al.: Pan-Cancer Bioinformatics Analysis of Gene UBE2C, Frontiers in genetics 2022;13

    Google Scholar 

  9. Yuan, L., et al.: Path-ATT-CNN: a novel deep neural network method for key pathway identification of lung cancer. Front. Genet. 13, 893358 (2022)

    Article  Google Scholar 

  10. Yuan, L., et al.: A novel computational framework to predict disease-related copy number variations by integrating multiple data sources. Front. Genet. 12, 696956 (2021)

    Article  Google Scholar 

  11. Yuan, L., et al.: A machine learning framework that integrates multi-omics data predicts cancer-related LncRNAs. BMC Bioinform. 22, 1–18 (2021)

    Article  Google Scholar 

  12. Li, J., et al.: Design of intelligent dormitory management system based on raspberry Pi. In: 2022 6th International Conference on Wireless Communications and Applications (ICWCAPP), pp. 205–208 (2022)

    Google Scholar 

  13. Zhang, Y.: Design of grid information platform based on new media IP information modeling algorithm. In: 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 223–226 (2022)

    Google Scholar 

  14. Wang, L.: Construction and application of college student safety management system based on 4R theory. In: 2022 International Conference on Education, Network and Information Technology (ICENIT), pp. 195–199 (2022)

    Google Scholar 

  15. Shen, Z., et al.: Prediction of Back-splicing sites for CircRNA formation based on convolutional neural networks. BMC Genomics 23, 581 (2022)

    Article  Google Scholar 

  16. Alhari, M.I., Lubis, M.: Quality of service (QoS) Wifi network study case: Telkom university dormitory hall. In: 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT), pp. 345–349 (2023)

    Google Scholar 

Download references

Acknowledgement

This work was supported by the Natural Science Foundation of Shandong Province, China (No. ZR2020QF038), the Ability Improvement Project of Science and Technology SMES in Shandong Province (No. 2023TSGC0279), the Youth Innovation Team of Colleges and Universities in Shandong Province (2023KJ329), and the Qilu University of Technology (Shandong Academy of Sciences) Talent Scientific Research Project (No. 2023RCKY128).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lin Yuan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Meng, B., Zhang, Y., Li, Z., Yu, W., Wei, H., Yuan, L. (2024). A New and Efficient Dormitory Management System. In: Huang, DS., Premaratne, P., Yuan, C. (eds) Applied Intelligence. ICAI 2023. Communications in Computer and Information Science, vol 2015. Springer, Singapore. https://doi.org/10.1007/978-981-97-0827-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-981-97-0827-7_9

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0826-0

  • Online ISBN: 978-981-97-0827-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics