Sustainable Smart Cities: Networked Digital Technologies, Cognitive Big Data Analytics, and Information Technology-driven Economy

The advancement of big data analytics is paving the way for knowledge creation based on very huge and unstructured data. Currently, information is scattered and growth tremendously, containing many information but difficult to be interpreted. Consequently, traditional approaches are no longer suitable for unstructured data but very rich in information. This situation is different from the role of previous information technology in which information is based on structured data, stored in the local storage, and in more advanced form, information can be retrieved through internet. Meanwhile, in Indonesia data are collected by many institutions with different measurement standard. The nature of the data collection is top-down, carried out by survey which is expensive yet unreliable and stored exclusively by respective institution. SIDeKa (Sistem Informasi Desa dan Kawasan/Village and Regional Information System), which are connected nationally, is proposed as a system of data collection in the village level and prepared by local people. Using SIDeKa, data reliability and readiness can be improved at the local level. The goals of the SIDeKa is not only local people have information in their hand such as poverty level, production, commodity price, the area of cultivated land, and the outbreak of diseases in their village, but also they have information from the neighboring villages or event at the national level. For government, data reliability will improve the policy effectiveness. This paper discusses the implementation and role of SIDeKa for knowledge creation in the village level, especially for the agricultural activities which has been initiated in 2015.Keywords: big data analytics; SIDeKa; unstructured data.

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Urban Planning and Smart City Decision Management Empowered by Real-Time Data Processing Using Big Data Analytics

Sensors ◽

10.3390/s18092994 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2994 ◽

Cited By ~ 28

Author(s):

Bhagya Silva ◽

Murad Khan ◽

Changsu Jung ◽

Jihun Seo ◽

Diyan Muhammad ◽

...

Keyword(s):

Big Data ◽

Data Processing ◽

Real Time ◽

Smart City ◽

Data Analytics ◽

Smart Cities ◽

Big Data Analytics ◽

Time Data ◽

Real Time Data

The Internet of Things (IoT), inspired by the tremendous growth of connected heterogeneous devices, has pioneered the notion of smart city. Various components, i.e., smart transportation, smart community, smart healthcare, smart grid, etc. which are integrated within smart city architecture aims to enrich the quality of life (QoL) of urban citizens. However, real-time processing requirements and exponential data growth withhold smart city realization. Therefore, herein we propose a Big Data analytics (BDA)-embedded experimental architecture for smart cities. Two major aspects are served by the BDA-embedded smart city. Firstly, it facilitates exploitation of urban Big Data (UBD) in planning, designing, and maintaining smart cities. Secondly, it occupies BDA to manage and process voluminous UBD to enhance the quality of urban services. Three tiers of the proposed architecture are liable for data aggregation, real-time data management, and service provisioning. Moreover, offline and online data processing tasks are further expedited by integrating data normalizing and data filtering techniques to the proposed work. By analyzing authenticated datasets, we obtained the threshold values required for urban planning and city operation management. Performance metrics in terms of online and offline data processing for the proposed dual-node Hadoop cluster is obtained using aforementioned authentic datasets. Throughput and processing time analysis performed with regard to existing works guarantee the performance superiority of the proposed work. Hence, we can claim the applicability and reliability of implementing proposed BDA-embedded smart city architecture in the real world.

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Towards a big data analytics framework for smart cities

Proceedings of the Mediterranean Symposium on Smart City Application - SCAMS '17 ◽

10.1145/3175628.3175647 ◽

2017 ◽

Cited By ~ 1

Author(s):

Hicham Abbad ◽

Radi Bouchaib

Keyword(s):

Big Data ◽

Data Analytics ◽

Smart Cities ◽

Big Data Analytics

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