A Smart Data Approach for Automatic Data Analysis

Sassite, Fouad; Addou, Malika; Barramou, Fatimazahra

doi:10.1007/978-981-15-0947-6_66

Cited by 2 publications

(1 citation statement)

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“…Smart data (value-based) has been introduced, to highlight valuable data, which can be effectively used by companies and governments for effective planning, monitoring, evaluation, reporting and intelligent decision-making. Three core attributes are necessary for data to be intelligent: it has to be accurate, actionable and agile [10], [11].…”

Section: A Big Data To Smart Datamentioning

confidence: 99%

A Machine Learning and Multi-Agent Model to Automate Big Data Analytics in Smart Cities

SASSITE¹,

ADDOU²,

BARRAMOU³

2022

IJACSA

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The objective of this paper is to present an architecture to improve the process of automating big data analytics using a multi-agent system and machine learning techniques, to support the processing of real time big data streams and to enhance the process of decision-making for urban planning and management. With the rapidly evolving information technologies, and their utilization in many areas such as smart cities, social networks, urban management and planning, massive data streams are generated and need an efficient approach to deal with. The proposition in this paper adopts the concept of smart data which focuses on the value aspect from big data. The proposed architecture is composed of three layers: data acquisition and storage, data management and processing and the service layer, based on a multi-agent system to automate the big data analytics; the proposed model describe the functionalities of the system and the collaboration between agents, these autonomous entities receive data streams in real time, they perform operations of preprocessing, big data analytics and storage into a Hadoop cluster. The techniques of machine learning are also used to enhance the process of decision making, such the use of classification algorithms to predict habitat type based on the characteristics of a population to help making efficient urban planning decisions. The proposed system can serve as a platform to support data management and to conduct effective decision-making in smart cities.

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Section: A Big Data To Smart Datamentioning

confidence: 99%