A Zero Emission Neighbourhoods Data Management Architecture for Smart City Scenarios: Discussions toward 6Vs challenges

Mahmud

2020

Preprint

Novel coronavirus disease 2019 (COVID-19) has found as a climacteric pandemic that spreads from human-to-human through contiguity. It is not possible to control the virus properly because its vaccine has not been discovered yet. As of now, various contact tracing approaches are being taken to contain the spread of the virus by breaking its transmission chain. Recently, few technologies are being exploited for contact tracing such as geological location, Bluetooth and google maps. Governments of some countries have already launched contact tracing applications to identify the close contact people of COVID-19 positive patients.However, these methods may not be effective without a huge amount of testing facility since the tracing action starts when a COVID-19 testing result is found positive. In this paper, we have proposed a novel AI-powered data management framework for smart city named IoT-to-Edge-to-Fog-to-cloudlet-to-Cloud (IEF2C) data management framework which will be exploited to identify the COVID-19 suspected patients in smart cities and also be used to inform the surrounding people about the suspected patient. The proposed framework is isolated into five layers which have different tasks such as data collection, processing, authentication and storage. The framework will bring all the citizens under a common platform as well as will ensure the user and device mobility. It will mitigate the information gap by helping concerned authorities and users to take proper steps in such a pandemic era.

Section: Literature Reviewmentioning

confidence: 99%

IEF2C: A novel AI-powered framework for suspected COVID-19 patient detection and contact tracing in smart cities

Mahmud

2020

Preprint

2020 21st IEEE International Conference on Mobile Data Management (MDM)

“…The cost model design is based on the underlying ZEN decentralized-to-centralized ICT architecture [2,32], as shown in Fig. 3.…”

Section: Using the Maut Cost Model For Data Discovery In The Zen Centermentioning

confidence: 99%

A Cost Model for Data Discovery in Large-Scale IoT Networks of Smart Cities

Soltvedt

Sinaeepourfard

Ahlers

2020

Self Cite

A smart city with huge numbers of physical (e.g., sensors and actuators) and non-physical (e.g., external databases) data sources will continuously produce high amounts of massive city-data. Distributed data storage across the city may store the produced city-data. City managers through different update mechanisms may send the produced city-data from distributed data storage to centralized data storage (e.g., Cloud data storage). Hence, the data discovery issues are in a vital position in the smart city concepts because the produced city-data may exist in different data storage platforms from distributed to centralized data. In this paper, we will first present our proposed Distributed-to-Centralized Information and Communications Technology (D2C-ICT) architecture for the Zero Emission Neighborhoods (ZEN) center. This proposed D2C-ICT architecture can provide multiple facilities from the joined benefits of distributed and centralized technologies in smart cities. Second, we will show how the Multi-Attribute Utility Theory (MAUT) cost model can be beneficial to find the appropriate data for building city services across the different storage platforms on the city scale as well as can be applied in the ZEN center and its pilots.

2019 IEEE 5th World Forum on Internet of Things (WF-IoT)

“…This idea highlights that the data is produced from many different data sources spread across the city but data is stored and reached from a centralized platform, mostly using Cloud computing technologies [2,3]. In addition, D2C-DM architectures are suggested by a few groups in the smart cities [7][8][9][10], which, uses a distributed schema for data management, using some high level of distributed technologies and ideas such as Fog Computing [6,11] or cloudlet technologies [12]. The D2C-DM architecture has been used in both potentials of Cloud and distributed (such as Fog, cloudlet, etc.)…”

Section: Related Workmentioning

confidence: 99%

“…technologies at the same time. However, almost all of D2C-DM architectures have been proposed through Fog and Cloud technologies (F2C-DM architecture) [7][8][9][10].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

F2c2C-DM: A Fog-to-cloudlet-to-Cloud Data Management Architecture in Smart City

Sinaeepourfard

Krogstie

Petersen

et al. 2019

Self Cite

Smart city solutions make a high-level technological innovation in a city to expand their citizens' quality of life by several different technological management strategies (such as resource management and data management) among end-users, city planners, and technological devices (e.g., sensors, IoT devices, etc.). Currently, data management architectures have been offered by some researchers to organize obtained data in smart cities, including Centralized Data Management (CDM) and Distributed-to-Centralized Data Management (D2C-DM). In addition, the D2C-DM architecture can provide several advantages from the combined advantages of distributed (e.g., Fog) and centralized (e.g., Cloud) technologies, such as reducing network traffic and their latencies, upgrading the security levels and so on. In this paper, we propose several novel contributions. First, we design a D2C-DM with Fog, cloudlet, and Cloud technologies to organize huge amounts of the data production in smart city scenarios, from physical devices (including IoT and sensors devices) to non-physical devices (including third-party applications, and other databases). Second, we tailor our proposed D2C-DM architecture with the Zero Emission Neighborhoods (ZEN) scenario to manage its different data types, including context, research, and Key Performance Indicator (KPI) data. Finally, the advantages of this D2C-DM architecture are discussed.