- Title
- A Model for Crime Management in Smart Cities
- Creator
- Westraadt, Lindsay
- Subject
- Smart cities
- Subject
- Computer networks -- security measures
- Date Issued
- 2019
- Date
- 2019
- Type
- Thesis
- Type
- Doctoral
- Type
- PHD
- Identifier
- http://hdl.handle.net/10948/45635
- Identifier
- vital:38922
- Description
- The main research problem addressed in this study is that South African cities are not effectively integrating and utilising available, and rapidly emerging smart city data sources for planning and management. To this end, it was proposed that a predictive model, that assimilates data from traditionally isolated management silos, could be developed for prediction and simulation at the system-of-systems level. As proof of concept, the study focused on only one aspect of smart cities, namely crime management. Subsequently, the main objective of this study was to develop and evaluate a predictive model for crime management in smart cities that effectively integrated data from traditionally isolated management silos. The Design Science Research process was followed to develop and evaluate a prototype model. The practical contributions of this study was the development of a prototype model for integrated decision-making in smart cities, and the associated guidelines for the implementation of the developed modelling approach within the South African IDP context. Theoretically, this work contributed towards the development of a modelling paradigm for effective integrated decision-making in smart cities. This work also contributed towards developing strategic-level predictive policing tools aimed at proactively meeting community needs, and contributed to the body of knowledge regarding complex systems modelling.
- Format
- 153 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | PhD - L Westraadt - 2019.pdf | 11 MB | Adobe Acrobat PDF | View Details Download |