Factors influencing continuous data collection for a public safety crowdsourcing smart city project

Abstract

More than 50 percent of the world’s population are now living in cities. The trend towards urbanisation has placed an enormous strain on the limited resources and services available to citizens in these cities. As more people live in cities, public safety issues also increase. These issues include crime, natural disasters and accidents. In order to effectively manage the limited resources as well as reduce the public safety issues in a city, the smart city approach can be implemented. A smart city makes use of technology to collect data from the citizens in order to make more efficient use of existing resources. This study focuses specifically on East London, South Africa, a developing country, and argues that currently there is no existing crowdsourcing system that can be used by the city to continuously collect public safety information from citizens for continuous data collection in order to improve public safety. The aim of the study is to develop a model that can be used by a city in a developing country to collect public safety information continuously from citizens. With the use of the interpretivist paradigm and mixed methods to gather and analyse data collected via conversational analysis, observations and questionnaire, it can be concluded that in a developing country, people are motivated to participate by three factors: intrinsic, internalised extrinsic, and extrinsic. Therefore the study further recommends that in order for the crowdsourcing system to be effective, the city must use all three factors to motivate citizens to report public safety information.