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A conceptual framework for blockchain smart contract adoption to manage real estate deals in smart cities

  • S.I. : Machine Learning Applications for Security
  • Published:
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Abstract

Blockchains-based smart contracts are disrupting the smart real estate sector of the smart cities. The current study explores the literature focused on blockchain smart contracts in smart real estate and proposes a conceptual framework for its adoption in smart cities. Based on a systematic review method, the literature published between 2000 and 2020 is explored and analyzed. From the literature, ten key aspects of the blockchain smart contracts are highlighted that are grouped into six layers for adopting the smart contracts in smart real estate. The decentralized application and its interactions with Ethereum Virtual Machine (EVM) are presented to show the development of a smart contract that can be used for blockchain smart contracts in real estate. Further, a detailed design and interaction mechanism are highlighted for the real estate owners and users as parties to a smart contract. A list of functions for initiating, creating, modifying, or terminating a smart contract is presented along with a stepwise procedure for establishing and terminating smart contracts. The current study can help the users enjoy a more immersive, user-friendly, and visualized contracting process, whereas the owners, property technologies (Proptech) companies, and real estate agents can enjoy more business and sales. This can help disrupt traditional real estate and transform it into smart real estate in line with industry 4.0 requirements.

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Acknowledgements

The authors are grateful to Mr. Bilal Ayub (Ph.D. Scholar RMIT University) and Dr. Tayyab Ahmad UniMelbourne for their kind comments and advice on improving the paper while the authors were waiting for reviewers’ comments. The academic community helps add substantial value to the body of knowledge, and we are grateful to have such people around. We are also thankful to Dr. Samad Sepasgozar and Dr. Jamaluddin Thaheem for their encouragement and guidance.

Funding

The article received no funding from any private or government organization.

Author information

Authors and Affiliations

  1. PhD Scholar, School of Built Environment, University of New South Wales, Kensington 2052, Sydney, NSW, Australia

    Fahim Ullah

  2. Research Center for AI and IoT, Near East University, Nicosia, Mersin 10, Turkey

    Fadi Al-Turjman

Authors
  1. Fahim Ullah
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  2. Fadi Al-Turjman
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Correspondence to Fahim Ullah.

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Appendices

Appendix A

Authors, citations, year, and type of the retrieved articles.

Authors

Retrieved Citation

Google Scholar Citation

Publication Year

Type

Ref

Watanabe H., Fujimura S., Nakadaira A., Miyazaki Y., Akutsu A., Kishigami J

101

165

2016

Conference

[36]

Amani S., Bortin M., Bégel M., Staples M

64

125

2018

Conference

[34]

Wright C., Serguieva A

15

25

2017

Conference

[37]

Molina-Jimenez C., Sfyrakis I., Solaiman E., Ng I., Weng Wong M., Chun A., Crowcroft J

14

29

2018

Conference

[47]

Sun M., Zhang J

7

11

2020

Journal

[23]

Kolluri A., Nikolic I., Sergey I., Hobor A., Saxena P

6

32

2019

Conference

[46]

Dewan S., Singh L

2

2

2020

Journal

[19]

Falazi G., Hahn M., Breitenbucher U., Leymann F., Yussupov V

2

5

2019

Conference

[35]

Covaci A., Madeo S., Motylinski P., Vincent S

2

4

2018

Conference

[57]

Appendix B

Affiliated organizations, their locations, and citations of the retrieved articles.

Organization

Location

Documents

Citations

Nchain

London, UK

2

17

Muroran Institute of Technology, Muroran-city

Hokkaido, Japan

1

101

NTT service evolution laboratories, Yokosuka-city

Kanagawa, japan

1

101

Data61 (CSIRO), UNSW

NSW, Australia

1

64

Ens Paris-Saclay, Université Paris-Saclay

Paris, France

1

64

Codex, Stanford University

Stanford, US

1

14

Computer laboratory, University of Cambridge

Cambridge, UK

1

14

Hat community foundation

Cambridge, UK

1

14

School of Computing, Newcastle University

Newcastle, UK

1

14

Singapore Management University

Singapore

1

14

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Ullah, F., Al-Turjman, F. A conceptual framework for blockchain smart contract adoption to manage real estate deals in smart cities. Neural Comput & Applic 35, 5033–5054 (2023). https://doi.org/10.1007/s00521-021-05800-6

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