scholarly journals A Parallel Meta-Heuristic Approach to Reduce Vehicle Travel Time in Smart Cities

2020 ◽  
Author(s):  
Hector Rico-Garcia ◽  
Jose-Luis Sanchez-Romero ◽  
Antonio Jimeno-Morenilla ◽  
Hector Migallon-Gomis
Keyword(s):  
Travel Time ◽  
Smart City ◽  
Smart Cities ◽  
Travelling Salesman Problem ◽  
Urban Environments ◽  
Departure Point ◽  
Classic Problem ◽  
Iot Devices ◽  
Vehicle Travel Time ◽  
Gpu Architecture

The development of the smart city concept and the inhabitants’ need to reduce travel time, as well as society’s awareness of the reduction of fuel consumption and respect for the environment, lead to a new approach to the classic problem of the Travelling Salesman Problem (TSP) applied to urban environments. This problem can be formulated as “Given a list of geographic points and the distances between each pair of points, what is the shortest possible route that visits each point and returns to the departure point?” Nowadays, with the development of IoT devices and the high sensoring capabilities, a large amount of data and measurements are available, allowing researchers to model accurately the routes to choose. In this work, the purpose is to give solution to the TSP in smart city environments using a modified version of the metaheuristic optimization algorithm TLBO (Teacher Learner Based Optimization). In addition, to improve performance, the solution is implemented using a parallel GPU architecture, specifically a CUDA implementation.

scholarly journals A Parallel Meta-Heuristic Approach to Reduce Vehicle Travel Time in Smart Cities

2021 ◽  
Vol 11 (2) ◽  
pp. 818
Author(s):  
Hector Rico-Garcia ◽  
Jose-Luis Sanchez-Romero ◽  
Antonio Jimeno-Morenilla ◽  
Hector Migallon-Gomis
Keyword(s):  
Travel Time ◽  
Smart City ◽  
Graphics Processing Unit ◽  
Smart Cities ◽  
Travelling Salesman Problem ◽  
Urban Environments ◽  
Processing Unit ◽  
Departure Point ◽  
Iot Devices ◽  
Parallel Graphics

The development of the smart city concept and inhabitants’ need to reduce travel time, in addition to society’s awareness of the importance of reducing fuel consumption and respecting the environment, have led to a new approach to the classic travelling salesman problem (TSP) applied to urban environments. This problem can be formulated as “Given a list of geographic points and the distances between each pair of points, what is the shortest possible route that visits each point and returns to the departure point?”. At present, with the development of Internet of Things (IoT) devices and increased capabilities of sensors, a large amount of data and measurements are available, allowing researchers to model accurately the routes to choose. In this work, the aim is to provide a solution to the TSP in smart city environments using a modified version of the metaheuristic optimization algorithm Teacher Learner Based Optimization (TLBO). In addition, to improve performance, the solution is implemented by means of a parallel graphics processing unit (GPU) architecture, specifically a Compute Unified Device Architecture (CUDA) implementation.

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

scholarly journals Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities

2021 ◽  
Vol 13 (9) ◽  
pp. 4716
Author(s):  
Moustafa M. Nasralla
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Virtual Reality ◽  
Time Series Analysis ◽  
Smart City ◽  
Smart Cities ◽  
Rehabilitation Services ◽  
Simulation Scenario ◽  
Common Problems ◽  
Iot Devices

To develop sustainable rehabilitation systems, these should consider common problems on IoT devices such as low battery, connection issues and hardware damages. These should be able to rapidly detect any kind of problem incorporating the capacity of warning users about failures without interrupting rehabilitation services. A novel methodology is presented to guide the design and development of sustainable rehabilitation systems focusing on communication and networking among IoT devices in rehabilitation systems with virtual smart cities by using time series analysis for identifying malfunctioning IoT devices. This work is illustrated in a realistic rehabilitation simulation scenario in a virtual smart city using machine learning on time series for identifying and anticipating failures for supporting sustainability.

The Role of AI-Based Integrated Physical Security Governance for Optimizing IoT Devices Connectivity in Smart Cities

2021 ◽  
pp. 289-309
Author(s):  
Rajan R. ◽  
Venkata Subramanian Dayanandan ◽  
Shankar P. ◽  
Ranganath Tngk
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Security Threats ◽  
Security Measures ◽  
Physical Security ◽  
Security Technology ◽  
Security Controls ◽  
World Class ◽  
Iot Devices

A smart city aims at developing an ecosystem wherein the citizens will have instant access to amenities required for a healthy and safe living. Since the mission of smart city is to develop and integrate many facilities, it is envisaged that there is a need for making the information available instantly for right use of such infrastructure. So, there exists a need to design and implement a world-class physical security measures which acts as a bellwether to protect people life from physical security threats. It is a myth that if placing adequate number of cameras alone would enhance physical security controls in smart cities. There is a need for designing and building comprehensive physical security controls, based on the principles of “layered defense-in-depth,” which integrates all aspects of physical security controls. This chapter will review presence of existing physical security technology controls for smart cities in line with the known security threats and propose the need for an AI-enabled physical security premise.

A Parallel Metaheuristic Approach to Reduce Vehicle Travel Time for Smart Cities Sustainability

2021 ◽  
pp. 37-49
Author(s):  
Hector Rico-Garcia ◽  
Jose-Luis Sanchez-Romero ◽  
Antonio Jimeno-Morenilla ◽  
Hector Migallon-Gomis
Keyword(s):  
Travel Time ◽  
Smart Cities ◽  
Vehicle Travel Time

scholarly journals Study and Research on IoT and Big Data Analysis for Smart City Development

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Haixia Yu ◽  
Ion Cosmin Mihai ◽  
Anand Srivastava
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Data Generation ◽  
City Development ◽  
Smart Meters ◽  
Smart Systems ◽  
Smart Parking ◽  
Iot Devices ◽  
Time Required

With the development of smart meters, like Internet of Things (IoT), various kinds of electronic devices are equipped with each smart city. The several aspects of smart cities are accessible and these technologies enable us to be smarter. The utilization of the smart systems is very quick and valuable source to fulfill the requirement of city development. There are interconnection between various IoT devices and huge amount of data is generated when they communicate each other over the internet. It is very challenging task to effectively integrate the IoT services and processing big data. Therefore, a system for smart city development is proposed in this paper which is based on the IoT utilizing the analytics of big data. A complete system is proposed which includes various types of IoT-based smart systems like smart home, vehicular networking, and smart parking etc., for data generation. The Hadoop ecosystem is utilized for the implementation of the proposed system. The evaluation of the system is done in terms of throughput and processing time. The proposed technique is 20% to 65% better than the existing techniques in terms of time required for processing. In terms of obtained throughput, the proposed technique outperforms the existing technique by 20% to 60%.

scholarly journals Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques

2020 ◽  
Vol 17 (24) ◽  
pp. 9347 ◽  
Author(s):  
Md Mamunur Rashid ◽  
Joarder Kamruzzaman ◽  
Mohammad Mehedi Hassan ◽  
Tasadduq Imam ◽  
Steven Gordon
Keyword(s):  
Machine Learning ◽  
Smart City ◽  
Service Providers ◽  
Detection System ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Increased Risk ◽  
Iot Devices

In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational efficiency and enhance both the service providers’ quality of services and people’s wellbeing and quality of life. With the growth of smart city networks, however, comes the increased risk of cybersecurity threats and attacks. IoT devices within a smart city network are connected to sensors linked to large cloud servers and are exposed to malicious attacks and threats. Thus, it is important to devise approaches to prevent such attacks and protect IoT devices from failure. In this paper, we explore an attack and anomaly detection technique based on machine learning algorithms (LR, SVM, DT, RF, ANN and KNN) to defend against and mitigate IoT cybersecurity threats in a smart city. Contrary to existing works that have focused on single classifiers, we also explore ensemble methods such as bagging, boosting and stacking to enhance the performance of the detection system. Additionally, we consider an integration of feature selection, cross-validation and multi-class classification for the discussed domain, which has not been well considered in the existing literature. Experimental results with the recent attack dataset demonstrate that the proposed technique can effectively identify cyberattacks and the stacking ensemble model outperforms comparable models in terms of accuracy, precision, recall and F1-Score, implying the promise of stacking in this domain.

scholarly journals Modeling of Trusted Public Emergency Services for Smart Cities Using Blockchain and IoT-based Cognitive Networks

2021 ◽  
Author(s):  
Bhawana Bhawana ◽  
Sushil Kumar
Keyword(s):  
Smart City ◽  
Queuing Theory ◽  
Smart Home ◽  
Emergency Service ◽  
Smart Cities ◽  
Distributed Storage ◽  
Cognitive Networks ◽  
Smart Healthcare ◽  
Public Emergency ◽  
Iot Devices

Abstract The Internet of Things (IoT) recently gained attention from the last few years due to various smart city applications deployment. The existing literature discusses different public emergency service (PES) aspects from smart-healthcare to smart-home automation. However, less work explores for the smart-fire-brigade system. The PESs require high computation, timely service fulfillment, service transparency, and trust, which are difficult to achieve through a centralized system. In recent years, blockchain technology has gained enormous popularity for immutable data management that ensures transparency, reliability, and data integrity using distributed storage. This paper presents a blockchain based model for secure and trusted public emergency service in IoT-enabled smart cities (BMSTP) to handle the PES requests in real-time fairly. An edge compute server (ECS) is introduced to enhance data processing speed and local data storage. Simultaneously, a queuing theory model is used to process PES requests quickly. The ECS manages an access control list (ACL) for smart-home IoT devices to protect against the illegal placement of any new IoT devices near smart-home to misguiding public emergency service departments (PESDs). Further, a reputation model is designed for PESDs to scale their service quality. We explored the BMSTP for smart-homes placed under different sub-areas of a smart-city. The experiment results show the proposed system model is efficient in scheduling the smart-home PES requests to an appropriate PESD and minimizing the delay to reaching the smart-home location.

scholarly journals Analyzing and Evaluating Smart Cities for IoT Based on Use Cases Using the Analytic Network Process

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chao Huang ◽  
Shah Nazir
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Information Leakage ◽  
Analytic Network Process ◽  
Use Cases ◽  
Security And Privacy ◽  
World Population ◽  
Network Process ◽  
Iot Devices ◽  
And Control

With the passage of time, the world population is growing. Proper utilization of resources and other devices is tremendously playing an important role to easily examine, manage, and control the resources of the Internet of Things (IoT) in the smart city. Research in the field of IoT has revolutionized the services mostly in smart cities. In the smart city, the applications of IoT are utilized without human involvement. Diverse IoT devices are connected with each other and communicate for different tasks. With the existence of a huge number of IoT devices in the forthcoming years, the chances of privacy breach and information leakage are increasing. Billions of devices connected on IoT producing huge volume of data bound to cloud for processing, management, and storage. Sending of whole data to the cloud might create risk of security and privacy. Various needs of the smart city should be considered for both urgent and effective solutions to support requirements of the growing population. On the other side of rising technology, the IoT evolution has massively produced diverse research directions for the smart city. Keeping in view the use cases of the smart city, the proposed study presents the analytic network process (ANP) for evaluating smart cities. The approach of ANP works well in the situation of complexity, and vagueness exists among the available alternatives. The experimental results of the planned approach show that the approach is effective for evaluating the smart cities for IoT based on the use cases.

EMERGING TECHNOLOGIES AND APPLICATIONS FOR SMART CITIES

2021 ◽  
Vol 15 (02) ◽  
pp. 19-24
Author(s):  
Vishv Patel ◽  
Devansh Shah ◽  
Nishant Doshi
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
Emerging Technologies ◽  
Smart Cities ◽  
The Internet ◽  
The World ◽  
Iot Devices ◽  
The City ◽  
The Internet Of Things ◽  
Day By Day

The large deployment of the Internet of Things (IoT) is empowering Smart City tasks and activities everywhere throughout the world. Items utilized in day-by-day life are outfitted with IoT devices and sensors to make them interconnected and connected with the internet. Internet of Things (IoT) is a vital piece of a smart city that tremendously impact on all the city sectors, for example, governance, healthcare, mobility, pollution, and transportation. This all connected IoT devices will make the cities smart. As different smart city activities and undertakings have been propelled in recent times, we have seen the benefits as well as the risks. This paper depicts the primary challenges and weaknesses of applying IoT innovations dependent on smart city standards. Moreover, this paper points the outline of the technologies and applications of the smart cities.

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