scholarly journals Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wahiba Ben Abdessalem Karaa ◽  
Eman Alkhammash ◽  
Thabet Slimani ◽  
Myriam Hadjouni
Keyword(s):  
Smart City ◽  
Performance Metrics ◽  
Smart Cities ◽  
National Income ◽  
Machine Learning Method ◽  
Learning Method ◽  
Social Media Mining ◽  
Smart Health ◽  
F Measure ◽  
Media Mining

The paper presents a recommendation model for developing new smart city and smart health projects. The objective is to provide recommendations to citizens about smart city and smart health startups to improve entrepreneurship and leadership. These recommendations may lead to the country’s advancement and the improvement of national income and reduce unemployment. This work focuses on designing and implementing an approach for processing and analyzing tweets inclosing data related to smart city and smart health startups and providing recommended projects as well as their required skills and competencies. This approach is based on tweets mining through a machine learning method, the Word2Vec algorithm, combined with a recommendation technique conducted via an ontology-based method. This approach allows discovering the relevant startup projects in the context of smart cities and makes links to the needed skills and competencies of users. A system was implemented to validate this approach. The attained performance metrics related to precision, recall, and F-measure are, respectively, 95%, 66%, and 79%, showing that the results are very encouraging.

scholarly journals Smart Healthcare Devices for Smart Cities: A Review

2020 ◽  
pp. 98-101
Keyword(s):  
Health Care ◽  
Health Care System ◽  
Health Care Professionals ◽  
Smart City ◽  
Health Care Services ◽  
Smart Cities ◽  
Care Services ◽  
Smart Healthcare ◽  
Smart Health ◽  
Care System

Smart City has become increasingly important worldwide since the last decade. It is the advanced system for communication among people with smart infrastructure ingrained in the smart city. In the smart city, the infrastructure will track and manage all basic facilities, health care, law implementation, water supply, traffic, and transport. Improvement in smart sensor networks, ubiquitous computing, mobile cloud computing, and intellectual services for the communication of information among the sensors, all these facilities built the base for the smart city. The smart health care system will perform an important part in transforming old cities into smart cities. Telecommunication engineering scientists have prepared smarter health services which are improving the standards of living of the society. These health care services significantly develop the quality of health care services in hospitals and also decrease the burden of health care professionals and paramedical staff. This research article presents the applications of a smart health care system which will benefit everyone in the society by providing easy telecommunication access to health care professionals and patients. This system will also track the patient's health online using wearable and implantable devices.

scholarly journals Social media mining for smart cities and smart villages research

2020 ◽  
Vol 24 (15) ◽  
pp. 10983-10987 ◽  
Author(s):  
Miltiadis D. Lytras ◽  
Anna Visvizi ◽  
Jari Jussila
Keyword(s):  
Social Media ◽  
Smart Cities ◽  
Social Media Mining ◽  
Media Mining

scholarly journals Assessing Impact, Performance and Sustainability Potential of Smart City Projects: Towards a Case Agnostic Evaluation Framework

2021 ◽  
Vol 13 (13) ◽  
pp. 7395
Author(s):  
Konstantinos Kourtzanidis ◽  
Komninos Angelakoglou ◽  
Vasilis Apostolopoulos ◽  
Paraskevi Giourka ◽  
Nikolaos Nikolopoulos
Keyword(s):  
Performance Index ◽  
Smart City ◽  
Performance Metrics ◽  
Performance Indicator ◽  
Smart Cities ◽  
Project Performance ◽  
Evaluation Framework ◽  
Spatial And Temporal Scales ◽  
Impact Performance ◽  
Target Values

We report on a novel evaluation framework to globally assess the footprint of smart cities and communities (SCC) projects, being also expandable to the case of smart grid related projects. The uniform smart city evaluation (USE) framework is constructed upon three complementary evaluation axes: the first one aims to weigh up the success of a SCC project based on performance metrics against pre-defined project-specific target values. The second axis focuses on the project’s impact towards the sustainability of a city and it is bench-marked against national and international key objectives arising from strategic plans. This bench-marking feeds the third axis which provides a more inclusive evaluation against four pre-defined and widely acclaimed sectors of interest. The steps to be followed for the uniform evaluation of each axis and corresponding index are presented in detail, including necessary key performance indicator (KPI) normalization, weighting, and aggregation methods. The resulting indices’ scores for each axis (namely project performance index, sustainability impact index, and sustainability performance index) can be post-processed with adequate data processing and visualization tools to extract important information on the extent to which the range of success of a SCC project contributes to the city sustainability progress. Illustrative examples from an on-going SCC project are provided to highlight the strengths of the approach. The proposed framework can be used to compare multiple projects within a city and sustainability and project performance in different cities, evaluate the interventions chosen per project against city needs, benchmark and design future projects (with, e.g., reverse engineering, projections), as well as evaluate various spatial and temporal scales.

Mining on Social Media

2017 ◽  
pp. 206-222 ◽  
Author(s):  
Ambati Venkata Krishna Prasad ◽  
Venkata Naresh Mandhala
Keyword(s):  
Social Media ◽  
Social Network ◽  
Sentiment Analysis ◽  
Learning Method ◽  
Bayes Classifier ◽  
Social Media Data ◽  
Social Media Mining ◽  
Analysis Technique ◽  
Media Data ◽  
Media Mining

Social media mining is the process of representing, analyzing, and extracting actionable patterns and trends from raw social media data. Social media is favored by many users since it is available to individuals without any limitations to share their opinions, educational learning experiences and concerns via their status. Twitter API, twitter4j, is processed for searching the tweets based on the geo location. Student's posts on social network offers us a stronger concern to take decisions concerning the particular education system's learning method of the system. Evaluating knowledge in social media is sort of a difficult method. Bayes classifier are enforced on deep-mined knowledge for analysis purpose to urge the deeper understanding of the information. It uses multi label classification technique as every label falls into completely different classes. Label based measures are mostly taken to research the results and comparing them with the prevailing sentiment analysis technique.

SenCity – Evaluating Users’ Experiences of Intelligent Lighting for Well-Being in Smart Cities

2018 ◽  
pp. 60-67
Author(s):  
Henrika Pihlajaniemi ◽  
Anna Luusua ◽  
Eveliina Juntunen
Keyword(s):  
Case Studies ◽  
Smart City ◽  
Smart Cities ◽  
Well Being ◽  
Evaluation Methods ◽  
Data Analyses ◽  
Sense Of Security ◽  
System Data

This paper presents the evaluation of usersХ experiences in three intelligent lighting pilots in Finland. Two of the case studies are related to the use of intelligent lighting in different kinds of traffic areas, having emphasis on aspects of visibility, traffic and movement safety, and sense of security. The last case study presents a more complex view to the experience of intelligent lighting in smart city contexts. The evaluation methods, tailored to each pilot context, include questionnaires, an urban dashboard, in-situ interviews and observations, evaluation probes, and system data analyses. The applicability of the selected and tested methods is discussed reflecting the process and achieved results.

Systematization of the smart city civil engineering infrastructure

2020 ◽  
Vol 18 (4) ◽  
pp. 765-779
Author(s):  
E.V. Popov ◽  
K.A. Semyachkov ◽  
K.V. Zhunusova
Keyword(s):  
Smart City ◽  
Process Management ◽  
Smart Cities ◽  
Digital Technologies ◽  
Urban Infrastructure ◽  
Infrastructure Development ◽  
Economic Innovation ◽  
Civil Engineering Infrastructure ◽  
Functional Transformations

Subject. This article explores the basic elements of the engineering infrastructure of smart cities. Objectives. The article aims to systematize theoretical descriptions of the engineering infrastructure of a smart city. Methods. For the study, we used a logical analysis and systematization. Results. The article highlights the main areas of infrastructure development of smart cities. Conclusions. Improving process management mechanisms, optimizing urban infrastructure, increasing the use of digital technologies, and developing socio-economic innovation improve the quality of the urban environment in a digitalized environment. And improving the efficiency of urban planning and security, studying its properties and characteristics, and forming an effective urban information system lead to its functional transformations.

YOUTH EXPECTATIONS OF SMART CITY LIVING: AN IMPORTANCE- PERFORMANCE ANALYSIS OF YOUNG RESIDENTS’ PERSPECTIVES OF CITY GOVERNMENT

2017 ◽  
Vol 14 (1) ◽  
pp. 118-128
Author(s):  
Jason Cohen ◽  
Judy Backhouse ◽  
Omar Ally
Keyword(s):  
Performance Analysis ◽  
Young People ◽  
Smart City ◽  
Smart Cities ◽  
City Government ◽  
Diagnostic Tools ◽  
City Management ◽  
Bottom Up ◽  
Starting Point ◽  
The City

Young people are important to cities, bringing skills and energy and contributing to economic activity. New technologies have led to the idea of a smart city as a framework for city management. Smart cities are developed from the top-down through government programmes, but also from the bottom-up by residents as technologies facilitate participation in developing new forms of city services. Young people are uniquely positioned to contribute to bottom-up smart city projects. Few diagnostic tools exist to guide city authorities on how to prioritise city service provision. A starting point is to understand how the youth value city services. This study surveys young people in Braamfontein, Johannesburg, and conducts an importance-performance analysis to identify which city services are well regarded and where the city should focus efforts and resources. The results show that Smart city initiatives that would most increase the satisfaction of youths in Braamfontein  include wireless connectivity, tools to track public transport  and  information  on city events. These  results  identify  city services that are valued by young people, highlighting services that young people could participate in providing. The importance-performance analysis can assist the city to direct effort and scarce resources effectively.

A Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Ligand-Target Predictions

2020 ◽  
Author(s):  
Lewis Mervin ◽  
Avid M. Afzal ◽  
Ola Engkvist ◽  
Andreas Bender
Keyword(s):  
Target Prediction ◽  
Support Vector ◽  
Machine Learning Method ◽  
Learning Method ◽  
Protein Target ◽  
Bioactivity Prediction ◽  
Vector Machines ◽  
Scaling Methods ◽  
Data Points ◽  
Compound Target

In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into reliable probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance of three such methods, namely Platt Scaling, Isotonic Regression and Venn-ABERS in calibrating prediction scores for ligand-target prediction comprising the Naïve Bayes, Support Vector Machines and Random Forest algorithms with bioactivity data available at AstraZeneca (40 million data points (compound-target pairs) across 2112 targets). Performance was assessed using Stratified Shuffle Split (SSS) and Leave 20% of Scaffolds Out (L20SO) validation.

Sign in / Sign up

Export Citation Format

Share Document