Leveraging big data solutions and APRIORI algorithms for environmental sustainability in port cities a case study of Mombasa

Abstract

Big data has been dubbed "the next frontier for innovation, competition, and productivity," and is broadly described as "society's ability to harness information in creative ways to produce meaningful insights or commodities and services of significant value". The main research question for this study is: What are the potential contributions of spatial association mining based on the APRIORI algorithm for improving environmental sustainability in port cities in the global South? The study will employ a mixed-methods approach, which will include both qualitative and quantitative data collection and analysis techniques. Qualitative data will be collected through in-depth interviews with relevant stakeholders, such as government agencies, port authorities, and environmental organizations. Quantitative data will be collected through the analysis of satellite imagery and existing databases of environmental and shipping data. The APRIORI algorithm will be used to identify the significant associations between different environmental sustainability variables in the port cities. The expected findings from this research will provide evidence for the potential of spatial association mining based on the APRIORI algorithm for addressing environmental sustainability issues in port cities in the global South. The findings will also inform the development of more effective and efficient environmental sustainability policies and practices for these cities. This research will contribute to the field of environmental sustainability by demonstrating the potential of Big Data solutions for addressing environmental challenges in the global South. The results will provide a basis for further research on the use of data-driven approaches for environmental sustainability in other regions and sectors.