Keynote speaker II: Smart cities and social media

2015 ◽  
Author(s):  
Christian Wagner
Keyword(s):  
Social Media ◽  
Smart Cities ◽  
Keynote Speaker

Technologies Disability and Inclusion

2018 ◽  
Author(s):  
Tomas Brusell
Keyword(s):  
Social Media ◽  
Augmented Reality ◽  
Information And Communication Technologies ◽  
Future Development ◽  
Smart Cities ◽  
Communication Technologies ◽  
Modern Technology ◽  
The Social ◽  
The Disabled ◽  
Information And Communication

When modern technology permeates every corner of life, there are ignited more and more hopes among the disabled to be compensated for the loss of mobility and participation in normal life, and with Information and Communication Technologies (ICT), Exoskeleton Technologies and truly hands free technologies (HMI), it's possible for the disabled to be included in the social and pedagogic spheres, especially via computers and smartphones with social media apps and digital instruments for Augmented Reality (AR) .In this paper a nouvel HMI technology is presented with relevance for the inclusion of disabled in every day life with specific focus on the future development of "smart cities" and "smart homes".

Crowdsourcing Incident Information for Emergency Response using Open Data Sources in Smart Cities

2018 ◽  
Vol 2672 (1) ◽  
pp. 198-208 ◽  
Author(s):  
Fan Zuo ◽  
Abdullah Kurkcu ◽  
Kaan Ozbay ◽  
Jingqin Gao
Keyword(s):  
Social Media ◽  
Prior Knowledge ◽  
Emergency Response ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Smart Cities ◽  
Hurricane Sandy ◽  
Support Vector ◽  
Twitter Data ◽  
Emergency Events

Emergency events affect human security and safety as well as the integrity of the local infrastructure. Emergency response officials are required to make decisions using limited information and time. During emergency events, people post updates to social media networks, such as tweets, containing information about their status, help requests, incident reports, and other useful information. In this research project, the Latent Dirichlet Allocation (LDA) model is used to automatically classify incident-related tweets and incident types using Twitter data. Unlike the previous social media information models proposed in the related literature, the LDA is an unsupervised learning model which can be utilized directly without prior knowledge and preparation for data in order to save time during emergencies. Twitter data including messages and geolocation information during two recent events in New York City, the Chelsea explosion and Hurricane Sandy, are used as two case studies to test the accuracy of the LDA model for extracting incident-related tweets and labeling them by incident type. Results showed that the model could extract emergency events and classify them for both small and large-scale events, and the model’s hyper-parameters can be shared in a similar language environment to save model training time. Furthermore, the list of keywords generated by the model can be used as prior knowledge for emergency event classification and training of supervised classification models such as support vector machine and recurrent neural network.

scholarly journals RE-ENGINEERING OF SMART CITY'S BUSINESS PROCESSES BASED ON SOCIAL NETWORKS AND INTERNET OF THINGS

2018 ◽  
Vol 16 (3) ◽  
pp. 275
Author(s):  
Emir Ugljanin ◽  
Dragan Stojanović ◽  
Ejub Kajan ◽  
Zakaria Maamar
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Internet Of Things ◽  
Smart City ◽  
Business Processes ◽  
Smart Cities ◽  
Successful Management ◽  
Complete Integration ◽  
Social Actions

This paper reports our experience with developing a Business-2-Social (B2S) platform that provides necessary support to all this platform’s constituents, namely business processes, social media (e.g., social network), and Internet of Things (IoT). This platform is exemplified with smart cities whose successful management requires a complete integration of IoT and social media capabilities into the business processes implementing user services. To ensure a successful integration, social actions, that a smart city would allow citizens execute, are analyzed in terms of impact of these smart city’s business processes. Reactions to these actions are tracked and then analyzed to improve user services.

Implementation of Social Media Concepts for E-Government

2019 ◽  
pp. 1071-1091
Author(s):  
Raimundo Díaz-Díaz ◽  
Daniel Pérez-González
Keyword(s):  
Social Media ◽  
Citizen Participation ◽  
Smart Cities ◽  
City Council ◽  
Political Agenda ◽  
The Public ◽  
Partnership Model ◽  
The Government ◽  
Technological Platform

Some governments have proven social media's potential to generate value through co-creation and citizen participation, and municipalities are increasingly using these tools in order to become smart cities. Nevertheless, few public administrations have taken full advantage of all the possibilities offered by social media and, as a consequence, there is a shortage of case studies published on this topic. By analyzing the case study of the platform Santander City Brain, managed by the City Council of Santander (Spain), the current work contributes to broaden the knowledge on ambitious social media projects implemented by local public administrations for e-Government; therefore, this case can be useful for other public sector's initiatives. The case studied herein proves that virtual social media are effective tools for civil society, as it is able to set the political agenda and influence the framing of political discourse; however, they should not be considered as the main channel for citizen participation. Among the results obtained, the authors have found that several elements are required: the determination and involvement of the government, a designated community manager to follow up with the community of users, the secured privacy of its users, and a technological platform that is easy to use. Additionally, the Public Private Partnership model provides several advantages to the project, such as opening new sources of funding.

Visualising Data for Smart Cities

2017 ◽  
pp. 453-475
Author(s):  
Michael Batty ◽  
Andrew Hudson-Smith ◽  
Stephan Hugel ◽  
Flora Roumpani
Keyword(s):  
Social Media ◽  
Mobile Devices ◽  
Smart City ◽  
Smart Cities ◽  
Short Term ◽  
Data Infrastructures ◽  
The City

This chapter introduces a range of analytics being used to understand the smart city, which depends on data that can primarily be understood using new kinds of scientific visualisation. We focus on short term routine functions that take place in cities which are being rapidly automated through various kinds of sensors, embedded into the physical fabric of the city itself or being accessed from mobile devices. We first outline a concept of the smart city, arguing that there is a major distinction between the ways in which technologies are being used to look at the short and long terms structure of cities, and we then focus on the shorter term, first examining the immediate visualisation of data through dashboards, then examining data infrastructures such as map portals, and finally introducing new ways of visualising social media which enable us to elicit the power of the crowd in providing and supplying data. We conclude with a brief focus on how new urban analytics is emerging to make sense of these developments.

scholarly journals Social Media Analytics of the Internet of Things

2021 ◽  
Author(s):  
Jim Scheibmeir ◽  
Yashwant K. Malaiya
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Internet Of Things ◽  
Smart Cities ◽  
The Internet ◽  
Social Media Analytics ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Abstract The Internet of Things technology offers convenience and innovation in areas such as smart homes and smart cities. Internet of Things solutions require careful management of devices and the risk mitigation of potential vulnerabilities within cyber-physical systems. The Internet of Things concept, its implementations, and applications are frequently discussed on social media platforms. This article illuminates the public view of the Internet of Things through a content-based analysis of contemporary conversations occurring on the Twitter platform. Tweets can be analyzed with machine learning methods to converge the volume and variety of conversations into predictive and descriptive models. We have reviewed 684,503 tweets collected in a two-week period. Using supervised and unsupervised machine learning methods, we have identified interconnecting relationships between trending themes and the most mentioned industries. We have identified characteristics of language sentiment which can help to predict popularity within the realm of IoT conversation. We found the healthcare industry as the leading use case industry for IoT implementations. This is not surprising as the current Covid-19 pandemic is driving significant social media discussions. There was an alarming dearth of conversations towards cybersecurity. Only 12% of the tweets relating to the Internet of Things contained any mention of topics such as encryption, vulnerabilities, or risk, among other cybersecurity-related terms.

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