Banca de QUALIFICAÇÃO: SANDERSON SANTOS AZEVEDO DA SILVA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : SANDERSON SANTOS AZEVEDO DA SILVA
DATA : 31/05/2017
HORA: 15:00
LOCAL: Sala D1-A
TÍTULO:

DATA MINING APPLICATION MODEL FOR CONTINUOUS IMPROVEMENT OF PUBLIC SERVICE PROVISIONS IN INTELLIGENT CITIES

PALAVRAS-CHAVES:

Continuous improvement; smart cities; processes analysis; data mining; citzen sensing; spontaneous feedback.

PÁGINAS: 45
GRANDE ÁREA: Engenharias
ÁREA: Engenharia de Produção
RESUMO:

Complex systems within other systems form what we now know as cities, involving traffic system, housing, energy, etc. All these systems are somehow interconnected and thus are managed by public and private actors. Such complexity opens space for innovation, that is, creating solutions that make people's lives easier, such as public transport information systems or resources used by city governments. In this environment there is a great part of the most vibrant innovations of today; The new urban centers are becoming a platform for the innovation economy. Society is rethinking the model of today's urban centers, transforming them into intelligent cities, where one of the principles is the participative managerial connection established between citizen and ruler. However, for this to happen, it is necessary for the government to set up a structure capable of collecting, storing, processing and analyzing data entered by citizens. The general objective of this work is to offer the government a model of continuous improvement of public service delivery processes based on the information derived from the mining of collaborative monitoring data, that is, data of suggestions of improvement inserted by the citizen himself. At this point, this work finds its importance and relevance, since it will propose a model capable of better managing the suggestions of improvement of processes that impact the lives of thousands of people. To do this, the research will collect suggestions for improvement of a given process by completing an electronic questionnaire, and analyze it under the light of Data Mining tools such as classification, association, grouping and summarization of data. From there, the manager will receive more accurate information and can implement improvements in the process, which will be evaluated again by the users, closing a cycle of continuous improvement and validating the model proposed by this research. Thus, it is expected at the end of this work to offer managers of public service processes a model of continuous improvement capable of helping them to intelligently process and systematize the data coming from suggestions from citizens.

MEMBROS DA BANCA:
Interno - 1229030 - HELIO ROBERTO HEKIS
Presidente - 1142787 - JOSE ALFREDO FERREIRA COSTA
Externo ao Programa - 2378360 - MARCO ANTONIO LEANDRO CABRAL
Externo ao Programa - 1525670 - MARCOS CESAR MADRUGA ALVES PINHEIRO