Proceedings of the 2025 Seminar on Modern Property Management Talent Training Enabling New Productive Forces (MPMTT 2025)

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Research on Dynamic Cost Monitoring and Linear Programming Optimization for Old Residential Area Renovation Projects Based on Internet of Things and Big Data

Authors
Shu Zong1, *, Peng Liu1, Yu Su1, Junhui Che1
1Faculty of Architectural Engineering Oxbridge College, Kunming University of Science and Technology, Kunming, 650101, Yunnan, China
*Corresponding author. Email: 928288652@qq.com
Corresponding Author
Shu Zong
Available Online 3 July 2025.
DOI
10.2991/978-94-6463-778-6_8How to use a DOI?
Keywords
Old residential area renovation; Internet of Things; Big data; Cost dynamic monitoring; Linear programming optimization
Abstract

This study focuses on the dynamic cost monitoring and linear programming optimization of old residential area renovation projects based on the Internet of Things (IoT) and big data. By deploying IoT devices in the renovation projects to collect data in real time and utilizing big data technology for storage, management, and analysis, a dynamic cost monitoring system is established. Simultaneously, a linear programming model is constructed to achieve reasonable cost allocation and optimal control, thereby enhancing the economic and social benefits of the projects. The innovation of this study lies in combining IoT, big data, and linear programming optimization methods to address the insufficient integration of intelligent renovation and cost optimization in existing research. The effectiveness of the proposed method is validated through five practical cases, and the results indicate that it can effectively reduce costs and improve resource utilization efficiency, providing support for the sustainable development of old residential area renovation projects.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 Seminar on Modern Property Management Talent Training Enabling New Productive Forces (MPMTT 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
3 July 2025
ISBN
978-94-6463-778-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-778-6_8How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shu Zong
AU  - Peng Liu
AU  - Yu Su
AU  - Junhui Che
PY  - 2025
DA  - 2025/07/03
TI  - Research on Dynamic Cost Monitoring and Linear Programming Optimization for Old Residential Area Renovation Projects Based on Internet of Things and Big Data
BT  - Proceedings of the 2025 Seminar on Modern Property Management Talent Training Enabling New Productive Forces (MPMTT 2025)
PB  - Atlantis Press
SP  - 50
EP  - 66
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-778-6_8
DO  - 10.2991/978-94-6463-778-6_8
ID  - Zong2025
ER  -