The aim of this study was to propose an automatable technological framework that identifies crime and misconduct patterns and trends in the matatu industry using data mining techniques for intelligence led policing in Kenya. The objectives of the study include to propose a framework for intelligent transport management system with patterns and trends identification capabilities, enhance formulation of policy developments, implementations and government regulations for the transport sector in Kenya, design model system for testing the framework to ascertain its practicability and effectiveness and identify challenges of the transport sector in Kenya. This was an application research which made use of dummy data. The study established that it is possible to use artificial intelligence to manage the transport sector by use of a system that will not only help identify the patterns and trends of matatus' on Kenyan roads but to answer the why's associated with the trends to help come up with meaningful applicable practical solutions to enhance security and integrity in the transport sector in general. The study also unearthed challenges in relation to the implementation of the above. Combination of classification and association rules based data mining approach was utilized for this study due to its effectiveness in bringing out patterns and trends that are interlinked and related to each other.
Internet of Things' is choking the world with Zettabyte scale data rate of which traditional computing can neither store nor process. Outputs of various kinds of Research endeavors are held in different media over the years and cannot be made to "talk to each other" to exploit each other for beneficial relative information. The prime objective is to find a platform that can easily accommodate Cloud technology which can elastically handle the big data concept. In this study a private cloud is built using Ubuntu and Eucalyptus open source software on two quad processor machines with 8GB Ram. Using Apache Flume and Hadoop analytics, Big Data obtained from Research outputs is mounted on the R-Wingu framework with capacity to data mine unstructured, unrelated data and relate the components intelligently and may be leased as Database as a Service(DaaS). Once disparate data streams are accessible in real time, in one place and a consistent fashion, data suddenly becomes much more powerful and decisions become that much more impactful. Surveys are conducted across research communities with an aim of isolating research Gaps through various statistical tools. Sample results are discussed alongside previous studies' outputs. Research Gaps filled are compared by poll results conducted with exiting outcomes. Establishments are urged to embrace Big Data approach for competitive advantage.
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