| Title | Smart Cities Population Classification Using Hadoop MapReduce |
|---|---|
| ID_Doc | 44242 |
| Authors | Ibrahim, IS; Rabee, F |
| Title | Smart Cities Population Classification Using Hadoop MapReduce |
| Year | 2023 |
| Published | |
| Abstract | Smart cities use various technologies and applications to improve performance of services: health, education, transportation, energy, etc., in order to achieve the required level of sustainability, and to improve their citizens' living standards. As a result, data in huge amounts are generated which are used in useful application areas. One of the modern technologies that contribute to enhancing the services of smart city is big data analysis using Hadoop MapReduce where it is a powerful computational model that is more popular among all big data tools. This paper proposes the Hadoop MapReduce-based system to deal with big data by classifying the population of the smart city according to their behaviors (the good works and bad works), where these data taken from various resources with different categories which include good, non-guilty, guilty, suspect, fugitive, criminal, incriminatory, wanted. The proposed system supports a reinhabitate system to deal with these categories to improve the behavior of people. |
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