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dc.contributor.authorNjeru, Salesio Kinyua
dc.date.accessioned2017-11-27T09:38:14Z
dc.date.available2017-11-27T09:38:14Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/11071/5681
dc.descriptionThesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore Universityen_US
dc.description.abstractTransport departments in many institutions suffer from logistical delays caused by lack of accurate and timely information among stakeholders. Even though vehicle fueling and maintenance may be a huge percentage of total organizations running costs, existing methods for tracking vehicle movements still depend on human skills. These traditional paper-based data collection methods in these organizations are time and labour-intensive, full of errors, and unreliable due to reluctance of the mandated personnel to monitor and record the correct information. Even though we have witnessed advances in Automated Vehicle Tracking (AVT) technologies which are technically, economically feasible and viable, organizations have faced challenges in adopting the AVT technologies. This has been because the tracking needs for these organizations are unique due to the nature of work they do. Privacy concerns of the drivers is also another reason why the available AVTs do not fit into these organizations. In order to investigate the challenges of adoption of AVT technologies and to present a solution to the task of tracking organization vehicles, this study provides a useful insight into the AVT technologies adoption barriers within the organizations.In view of these, a model for integrating the latest innovations in AVT technologies for real-time data collection in transport was proposed. A combination of Radio Frequency Identification (RFID), Global Positioning System (GPS), and Global System for Mobile Communications (GSM) technologies was proposed in this study. The RFID model for tracking vehicles will facilitate extremely low-cost infrastructure solution to uniquely locate and track vehicles and driver behaviour instantaneously. The model aims at eliminating human error associated with data collection process during tracking vehicles in organizations.en_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectGPRSen_US
dc.subjectGPSen_US
dc.subjectGSMen_US
dc.subjectRFIDen_US
dc.subjectWork Ticketen_US
dc.titleRFID based model for tracking vehiclesen_US
dc.typeThesisen_US


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