Real-time monitoring system for drunk driver through Internet of Things - a case of Nairobi County, Kenya

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dc.contributor.authorMbugua, Joseph Muoho
dc.date.accessioned2019-10-29T14:42:52Z
dc.date.available2019-10-29T14:42:52Z
dc.date.issued2019
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.abstractOne of the major causes of traffic accidents and crashes globally is drunk driving. Though driving under influence of alcohol is illegal, drivers still find themselves doing it. This has resulted to deaths and fatalities which affect the economy negatively. Currently, different technologies have been adopted to reduce the vice without success. In Kenya, breathalyzers are being used by traffic police to monitor drunk drivers. This technology has failed due to corruption. The reason being the culprits are able to buy their way out. Technological innovation needs to be implemented in a cost effective, efficient and legal manner. This enables to combat drunken driving on the roads easily. The researcher applies the V-Model Methodology to design, implement and test of a realtime monitoring system for drunk driver through IoT. The system uses fuzzy logic based algorithm to analyze the response of MQ-3 and MQ-135 sensors. Sensor fusion is achieved through processing the analog to digital converted values of the sensor output using an algorithm to determine alcohol concentration in the breath (BAC). The analyzed result determines whether the Blood alcohol concentration (BAC) is within the legally permissible standards. Upon the detection of such a situation, an alarm is activated. Additionally, an ‘alert SMS’ indicating the drunk driver’s location as tracked by the GPS receiver on the same system and the vehicle registration number is communicated to the SACCO managers using GSM cellular network to take appropriate action of intercepting the vehicle. The tested real-time results indicated the successful implementation of the system.en_US
dc.identifier.urihttp://hdl.handle.net/11071/6712
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectReal-time monitoring systemen_US
dc.subjectDrunk driveren_US
dc.subjectInternet of Thingsen_US
dc.titleReal-time monitoring system for drunk driver through Internet of Things - a case of Nairobi County, Kenyaen_US
dc.typeThesisen_US
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MSIT Theses and Dissertations (2019)