Smart crowds in smart cities: real life, city scale deployments of a smartphone based participatory crowd management platform

A smart city is an environment that uses innovative technologies to make networks and services more flexible, effective, and sustainable with the use of information, digital, and telecommunication technologies, improving the city’s operations for the benefit of its citizens. Most cities incorporate data acquisition elements from their own systems or those managed by subcontracted companies that can be used to optimise their resources: energy consumption, smart meters, lighting, irrigation water consumption, traffic data, camera images, waste collection, security systems, pollution meters, climate data, etc. The city-as-a-platform concept is becoming popular and it is increasingly evident that cities must have efficient management systems capable of deploying, for instance, IoT platforms, open data, etc., and of using artificial intelligence intensively. For many cities, data collection is not a problem, but managing and analysing data with the aim of optimising resources and improving the lives of citizens is. This article presents deepint.net, a platform for capturing, integrating, analysing, and creating dashboards, alert systems, optimisation models, etc. This article shows how deepint.net has been used to estimate pedestrian traffic on the streets of Melbourne (Australia) using the XGBoost algorithm. Given the current situation, it is advisable not to transit urban roads when overcrowded, thus, the model proposed in this paper (and implemented with deepint.net) facilitates the identification of areas with less pedestrian traffic. This use case is an example of an efficient crowd management system, implemented and operated via a platform that offers many possibilities for the management of the data collected in smart territories and cities.

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Dealing with Demand in Electric Grids with an Adaptive Consumption Management Platform

Complexity ◽

10.1155/2018/4012740 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Diego M. Jiménez-Bravo ◽

Juan F. De Paz ◽

Gabriel Villarrubia ◽

Javier Bajo

Keyword(s):

Multiagent System ◽

Smart Cities ◽

Demand Management ◽

Machine Learning Techniques ◽

Electrical Network ◽

Case Based Reasoning ◽

The European Union ◽

Management Platform ◽

Reasoning System ◽

Electrical Demand

The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off.

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How does a (Smart) Age-Friendly Ecosystem Look in a Post-Pandemic Society?

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17218276 ◽

2020 ◽

Vol 17 (21) ◽

pp. 8276

Author(s):

Hannah Ramsden Marston ◽

Linda Shore ◽

P.J. White

Keyword(s):

Digital Technology ◽

Positive Impact ◽

Smart Cities ◽

Real Life ◽

Living Will ◽

Opportunities To Respond ◽

Societal Challenges ◽

Aging Populations ◽

Integral Role ◽

Agile Approach

COVID-19 has impacted not only the health of citizens, but also the various factors that make up our society, living environments, and ecosystems. This pandemic has shown that future living will need to be agile and flexible to adapt to the various changes in needs of societal populations. Digital technology has played an integral role during COVID-19, assisting various sectors of the community, and demonstrating that smart cities can provide opportunities to respond to many future societal challenges. In the decades ahead, the rise in aging populations will be one of these challenges, and one in which the needs and requirements between demographic cohorts will vary greatly. Although we need to create future smart age-friendly ecosystems to meet these needs, technology still does not feature in the WHO eight domains of an age-friendly city. This paper extends upon Marston and van Hoof’s ‘Smart Age-friendly Ecosystem’ (SAfE) framework, and explores how digital technology, design hacking, and research approaches can be used to understand a smart age-friendly ecosystem in a post-pandemic society. By exploring a series of case studies and using real-life scenarios from the standpoint of COVID-19, we propose the ‘Concept of Age-friendly Smart Ecologies (CASE)’ framework. We provide an insight into a myriad of contemporary multi-disciplinary research, which are capable to initiate discussions and bring various actors together with a positive impact on future planning and development of age-friendly ecosystems. The strengths and limitations of this framework are outlined, with advantages evident in the opportunity for towns, regions/counties, provinces, and states to take an agile approach and work together in adopting and implement improvements for the greater benefits of residents and citizens.

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An Edge Computing Based Smart Healthcare Framework for Resource Management

Sensors ◽

10.3390/s18124307 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4307 ◽

Cited By ~ 50

Author(s):

Soraia Oueida ◽

Yehia Kotb ◽

Moayad Aloqaily ◽

Yaser Jararweh ◽

Thar Baker

Keyword(s):

Resource Utilization ◽

Waiting Time ◽

Smart Cities ◽

Real Life ◽

Edge Computing ◽

Utilization Rate ◽

Resource Assignment ◽

Smart Healthcare ◽

Patient Waiting Time ◽

Patient Waiting

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time.

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Security and Cryptographic Challenges for Authentication Based on Biometrics Data

Cryptography ◽

10.3390/cryptography2040039 ◽

2018 ◽

Vol 2 (4) ◽

pp. 39 ◽

Cited By ~ 4

Author(s):

Stefania Nita ◽

Marius Mihailescu ◽

Valentin Pau

Keyword(s):

Machine Learning ◽

Cloud Computing ◽

Smart Cities ◽

Clustering Algorithms ◽

Security Analysis ◽

Real Life ◽

Analysis Tool ◽

Biometric Analysis ◽

Wide Range ◽

Government Education

Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of the society, e.g., Smart City, Internet-of-Things (IoT), Cloud Computing, Big Data. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness, characteristic, biometrics systems will become more and more vulnerable, privacy being one of the most important challenges. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The current paper has several objectives. The main objective consists in creating a framework based on cryptographic modules which can be applied in systems with biometric authentication methods. The technologies used in creating the framework are: C#, Java, C++, Python, and Haskell. The wide range of technologies for developing the algorithms give the readers the possibility and not only, to choose the proper modules for their own research or business direction. The cryptographic modules contain algorithms based on machine learning and modern cryptographic algorithms: AES (Advanced Encryption System), SHA-256, RC4, RC5, RC6, MARS, BLOWFISH, TWOFISH, THREEFISH, RSA (Rivest-Shamir-Adleman), Elliptic Curve, and Diffie Hellman. As methods for implementing with success the cryptographic modules, we will propose a methodology which can be used as a how-to guide. The article will focus only on the first category, machine learning, and data clustering, algorithms with applicability in the cloud computing environment. For tests we have used a virtual machine (Virtual Box) with Apache Hadoop and a Biometric Analysis Tool. The weakness of the algorithms and methods implemented within the framework will be evaluated and presented in order for the reader to acknowledge the latest status of the security analysis and the vulnerabilities founded in the mentioned algorithms. Another important result of the authors consists in creating a scheme for biometric enrollment (in Results). The purpose of the scheme is to give a big overview on how to use it, step by step, in real life, and how to use the algorithms. In the end, as a conclusion, the current work paper gives a comprehensive background on the most important and challenging aspects on how to design and implement an authentication system based on biometrics characteristics.

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A Real-Life Application of a Smart User Network

Energies ◽

10.3390/en11123504 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3504 ◽

Cited By ~ 3

Author(s):

Giuseppe Barone ◽

Giovanni Brusco ◽

Alessandro Burgio ◽

Daniele Menniti ◽

Anna Pinnarelli ◽

...

Keyword(s):

Social Innovation ◽

Smart Cities ◽

Renewable Energy Sources ◽

Real Life ◽

Energy Sources ◽

Control Logic ◽

Optimal Load ◽

Smart Community ◽

Distribution Energy ◽

Transmission And Distribution

Smart Community microgrids could help to improve overall energy efficiency reducing transmission and distribution losses and allowing the implementation of optimal load control and resource dispatching. In this context, the authors have proposed the realization of DC smart microgrids. They are considered as a future prospective according to the increase of DC loads and DC output type distribution energy sources such as Photovoltaic and energy storage systems. In this paper, a DC smart microgrid, called Smart User Network, realized in a real-life application as a part of pilot site under the national research project PON04_00146 Smart cities and Communities and Social innovation named “Reti, Edifici, Strade Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia” (RES NOVAE), is illustrated. The Smart User Network, is managed by a distributed and decentralized control logic, the DC Bus Signaling, which allows the converters to operate independently of each other according to a decentralized logic. It guarantees the reliability, the continuity and the quality of supply, optimizing the use of energy produced by renewable energy sources, also in stand-alone configuration. The most significant experimental results obtained both in grid-connected and stand-alone configuration are presented and discussed.

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IntelCity, comprehensive management platform for smart cities

2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE) ◽

10.1109/vitae.2014.6934423 ◽

2014 ◽

Author(s):

N. Perez ◽

J. Poncela ◽

J. M. Moreno ◽

M. Memon

Keyword(s):

Smart Cities ◽

Comprehensive Management ◽

Management Platform

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Disruptive Technologies for Efficient and Sustainable Smart Cities

International Journal of Management, Technology, and Social Sciences ◽

10.47992/ijmts.2581.6012.0152 ◽

2021 ◽

pp. 47-64

Author(s):

Dipak S. Gade

Keyword(s):

Data Analysis ◽

Smart Cities ◽

Rapid Development ◽

Real Life ◽

Research Area ◽

Future Research ◽

Research Papers ◽

Digital Twins ◽

New Findings ◽

Operations And Maintenance

Purpose: The most active and rapid development in today's world is happening in Smart cities. Smart Cities are changing very fast in every aspect, be it development, operations, and or maintenance points of view. Today's Smart Cities are aiming to be at an advanced stage of urbanization and fully exploiting digital infrastructure for rapid urban development. In order to make the cities better places to live and to offer more comfortable and enjoyable living for their residents, Smart Cities are using and employing various tools and technologies to make themselves smarter and more connected with their stakeholders using technology means. Industry 4.0, Digital Transformation, and various latest technologies such as 5G, Data Analytics, IoT, AI, and Machine Learning, Digital Twins, etc. are transforming and shaping up Smart Cities in never before style. In this paper, various such key technologies that are positively affecting Smart Cities are discussed at length. It is also highlighted in detail how these technologies are impacting Smart Cities development and operations. Finally, future research directions are also discussed in brief. Design/Methodology/Approach: Extensive exploration of available literature with research papers, conference papers, white papers, online blogs, dedicated websites, etc. on the research area and interactions with field researchers, subject matter experts, industry professionals is carried out to collect, analyse and process the collected data to find out the facts. The resulted facts and findings about the latest technologies used in Smart Cities is presented in this research paper. Findings/Result: After analysis of available literature and based on interactions with relevant stakeholders and based on own data analysis, it is identified that Smart City services are making use of various latest tools and technologies to solve their real-life challenges. Among vast list of technologies specifically IoT, Blockchain, Digital Twins, 5G, Contactless Technology, AI and ML are found the most significant and widely used technologies in Smart Cities development, operations, and maintenance activities. Originality/Value: It is found that not many research papers are available on analysis of future technologies used in Smart Cities. The data presented in this paper is genuine and original and completely based on systematic literature review, interactions with SME, Researchers and Industry experts and based on own data analysis which produced new findings. Paper Type: Technology oriented Research

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Testing Platforms as Drivers for Positive-Energy Living Laboratories

Energies ◽

10.3390/en13215621 ◽

2020 ◽

Vol 13 (21) ◽

pp. 5621

Author(s):

Silvia Soutullo ◽

Laura Aelenei ◽

Per Sieverts Nielsen ◽

Jose Antonio Ferrer ◽

Helder Gonçalves

Keyword(s):

Swot Analysis ◽

Smart Cities ◽

Real Life ◽

Positive Energy ◽

Energy Research ◽

Energy Applications ◽

Climatic Regions ◽

First Results ◽

Research Alliance

The development of city-driven urban laboratories was considered a priority by the European Commission through Action 3.2 of the Strategic Energy Technology Plan. In this context, positive-energy districts laboratories could take the role of urban drivers toward innovation and sustainability in cities. These urban labs can provide real-life facilities with innovative co-creation processes and, at the same time, provide testing, experimenting, and prototyping of innovative technologies. In this scope, the authors of this work want to share the very first results of an empirical study using the testing facilities provided by the members of the Joint Program on Smart Cities of the European Energy Research Alliance as positive-energy districts laboratories. Six climatic regions are studied as boundary conditions, covering temperate and continental climates. Four scales of action are analyzed: Building, campus, urban, and virtual, with building and campus scales being the most frequent. Most of these laboratories focus on energy applications followed by networks, storage systems, and energy loads characterization. Many of these laboratories are regulated by ICT technologies but few of them consider social aspects, lighting, waste, and water systems. A SWOT analysis is performed to highlight the critical points of the testing facilities in order to replicate optimized configurations under other conditions. This statistical study provides guidelines on integration, localization, functionality, and technology modularity aspects. The use of these guidelines will ensure optimal replications, as well as identify possibilities and opportunities to share testing facilities of/between the positive-energy district laboratories.

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An Enhanced Inverse Filtering Methodology for Drive-By Frequency Identification of Bridges Using Smartphones in Real-Life Conditions

Smart Cities ◽

10.3390/smartcities4020026 ◽

2021 ◽

Vol 4 (2) ◽

pp. 499-513

Author(s):

Nima Shirzad-Ghaleroudkhani ◽

Mustafa Gül

Keyword(s):

Surface Roughness ◽

Smart Cities ◽

Real Life ◽

Cost Effective ◽

Vehicle Speed ◽

Inverse Filtering ◽

Novel Approach ◽

Life Scale ◽

Frequency Identification ◽

Speed Effect

This paper develops an enhanced inverse filtering-based methodology for drive-by frequency identification of bridges using smartphones for real-life applications. As the vibration recorded on a vehicle is dominated by vehicle features including suspension system and speed as well as road roughness, inverse filtering aims at suppressing these effects through filtering out vehicle- and road-related features, thus mitigating a few of the significant challenges for the indirect identification of the bridge frequency. In the context of inverse filtering, a novel approach of constructing a database of vehicle vibrations for different speeds is presented to account for the vehicle speed effect on the performance of the method. In addition, an energy-based surface roughness criterion is proposed to consider surface roughness influence on the identification process. The successful performance of the methodology is investigated for different vehicle speeds and surface roughness levels. While most indirect bridge monitoring studies are investigated in numerical and laboratory conditions, this study proves the capability of the proposed methodology for two bridges in a real-life scale. Promising results collected using only a smartphone as the data acquisition device corroborate the fact that the proposed inverse filtering methodology could be employed in a crowdsourced framework for monitoring bridges at a global level in smart cities through a more cost-effective and efficient process.

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