scholarly journals Data-driven framework for energy-efficient smart cities

2020 ◽  
Vol 17 (1) ◽  
pp. 41-63 ◽  
Author(s):  
Nenad Petrovic ◽  
Djordje Kocic
Keyword(s):  
Deep Learning ◽  
Energy Distribution ◽  
Code Generation ◽  
Energy Efficient ◽  
Cost Reduction ◽  
Smart Cities ◽  
Autonomous Vehicle ◽  
Linear Optimization ◽  
Data Driven ◽  
Distribution Cost

Energy management is one of the greatest challenges in smart cities. Moreover, the presence of autonomous vehicles makes this task even more complex. In this paper, we propose a data-driven smart grid framework which aims to make smart cities energy-efficient focusing on two aspects: energy trading and autonomous vehicle charging. The framework leverages deep learning, linear optimization, semantic technology, domain-specific modelling notation, simulation and elements of relay protection. The evaluation of deep learning module together with code generation time and energy distribution cost reduction performed within the simulation environment also presented in this paper are given. According to the results, the achieved energy distribution cost reduction varies and depends from case to case.

2006: The Topology of Morals (Who Does the Algorithm Think We Are?)

2021 ◽  
Vol 15 (2) ◽  
pp. 178-196
Author(s):  
Aragorn Eloff
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Deep Learning ◽  
Smart Cities ◽  
Digital Technologies ◽  
Data Driven ◽  
Learning Networks ◽  
Modes Of Operation ◽  
The Social ◽  
Form Part

Deleuze's Postscript on the Societies of Control has been the most common entry point for interrogating the ways in which contemporary digital technologies have altered the social and the subjective from a Deleuzo-Guattarian perspective. It is, however, in A Thousand Plateaus that we find the most comprehensive set of resources for grappling with the Algocene, the contemporary digitally interconnected world of ubiquitous computing, drones, data mining, smart cities, social media, automated trading and other data-driven technologies that are heavily reliant upon algorithmic processes and deep learning networks. In this broad survey, I argue that in order to grapple with these new technological assemblages and the implications of their deployment across society, we should posit a new major stratum, the algoplastic, and, along with it, new modes of operation of order-words and the regimes of signs they form part of. I conclude by posing some of the new problems that emerge with the Algocene.

On prediction of traffic flows in smart cities: a multitask deep learning based approach

2021 ◽  
Author(s):  
Fucheng Wang ◽  
Jiajie Xu ◽  
Chengfei Liu ◽  
Rui Zhou ◽  
Pengpeng Zhao
Keyword(s):  
Deep Learning ◽  
Smart Cities ◽  
Traffic Flows
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