SMS: A Secure Healthcare Model for Smart Cities

Technological innovations have enabled the realization of a utopian world where all objects of everyday life, as well as humans, are interconnected to form an “Internet of Things (IoT).” These connected technologies and IoT solutions have led to the emergence of smart cities where all components are converted into a connected smart ecosystem. IoT has envisioned several areas of smart cities including the modern healthcare environment like real-time monitoring, patient information management, ambient-assisted living, ambient-intelligence, anomaly detection, and accelerated sensing. IoT has also brought a breakthrough in the medical domain by integrating stake holders, medical components, and hospitals to bring about holistic healthcare management. The healthcare domain is already witnessing promising IoT-based solutions ranging from embedded mobile applications to wearable devices and implantable gadgets. However, with all these exemplary benefits, there is a need to ensure the safety and privacy of the patient’s personal and medical data communicated to and from the connected devices and systems. For a smart city, it is pertinent to have an accessible, effective, and secure healthcare system for its inhabitants. This paper discusses the various elements of technology-enabled healthcare and presents a privacy-preserved and secure “Smart Medical System (SMS)” framework for the smart city ecosystem. For providing real-time analysis and responses, this paper proposes to use the concept of secured Mobile Edge Computing (MEC) for performing critical time-bound computations on the edge itself. In order to protect the medical and personal data of the patients and to make the data tamper-proof, the concept of blockchain has been used. Finally, this paper highlights the ways to capture and store the medical big data generated from IoT devices and sensors.

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M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

Journal of Ambient Intelligence and Smart Environments ◽

10.3233/ais-210598 ◽

2021 ◽

pp. 1-15

Author(s):

Subhranshu Sekhar Tripathy ◽

Diptendu Sinha Roy ◽

Rabindra K. Barik

Keyword(s):

Load Balancing ◽

Resource Utilization ◽

Smart City ◽

Load Transfer ◽

Smart Cities ◽

Fog Computing ◽

Round Robin ◽

Healthcare Management ◽

Optimization Strategy ◽

Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

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Environmentally-Powered WSN for Urban-Scale Mapping and Assessment of Air Quality in Qatar

University of the Future: Re-Imagining Research and Higher Education ◽

10.29117/quarfe.2020.0056 ◽

2020 ◽

Author(s):

Hasan Tariq ◽

Farid Touati

Keyword(s):

Air Quality ◽

Real Time ◽

Assisted Living ◽

Quality Index ◽

Electrochemical Sensors ◽

Ambient Assisted Living ◽

Quality Measurement ◽

Air Quality Index ◽

Cross Sensitivity ◽

Index Mapping

Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges. These challenges lead to real-time gradient anomalies that effect the accuracy and pro-longed lags in air quality index mapping campaigns for state and environmental/meteorological agencies. In this work, a gradient-aware, multi-variable air quality-sensing node is proposed with event-triggered sensing based on position, gas magnitudes, and cross-sensitivity interpolation. In this approach, temperature, humidity, pressure, geo-position, photovoltaic power, volatile organic compounds, particulate matter (2.5), ozone, Carbon mono-oxide, Nitrogen dioxide, and Sulphur dioxide are the principle variables. Results have shown that the proposed system optimized the real-time air quality monitoring for the chosen geo-spatial cluster (Qatar University).

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A Low-Dimensional Radial Silhouette-Based Feature for Fast Human Action Recognition Fusing Multiple Views

International Scholarly Research Notices ◽

10.1155/2014/547069 ◽

2014 ◽

Vol 2014 ◽

pp. 1-11 ◽

Cited By ~ 8

Author(s):

Alexandros Andre Chaaraoui ◽

Francisco Flórez-Revuelta

Keyword(s):

Real Time ◽

Action Recognition ◽

Assisted Living ◽

Learning Algorithm ◽

Ambient Assisted Living ◽

Human Action Recognition ◽

Human Action ◽

Sequence Matching ◽

Low Dimensional ◽

Video Frequency

This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.

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PC-based Intelligent Traffic Monitoring System with Real-time Analysis for Smart Cities

10.1109/comsnets53615.2022.9668589 ◽

2022 ◽

Author(s):

Chi-Yat Lau ◽

Man-Ching Yuen ◽

Ka-Ho Yueng ◽

Cheuk-Pan Fan ◽

On-Yi Ko ◽

...

Keyword(s):

Real Time ◽

Monitoring System ◽

Smart Cities ◽

Traffic Monitoring ◽

Time Analysis ◽

Real Time Analysis

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Cloud-Based Big Data Analysis Tools and Techniques Towards Sustainable Smart City Services

Advances in Computational Intelligence and Robotics - Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities ◽

10.4018/978-1-7998-7468-3.ch004 ◽

2021 ◽

pp. 63-90

Author(s):

Suresh P. ◽

Keerthika P. ◽

Sathiyamoorthi V. ◽

Logeswaran K. ◽

Manjula Devi R. ◽

...

Keyword(s):

Big Data ◽

Real Time ◽

Smart City ◽

Traffic Management ◽

Smart Cities ◽

Big Data Analytics ◽

Streaming Data ◽

City Development ◽

Time Data ◽

Public And Private

Cloud computing and big data analytics are the key parts of smart city development that can create reliable, secure, healthier, more informed communities while producing tremendous data to the public and private sectors. Since the various sectors of smart cities generate enormous amounts of streaming data from sensors and other devices, storing and analyzing this huge real-time data typically entail significant computing capacity. Most smart city solutions use a combination of core technologies such as computing, storage, databases, data warehouses, and advanced technologies such as analytics on big data, real-time streaming data, artificial intelligence, machine learning, and the internet of things (IoT). This chapter presents a theoretical and experimental perspective on the smart city services such as smart healthcare, water management, education, transportation and traffic management, and smart grid that are offered using big data management and cloud-based analytics services.

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Real-time human behaviour monitoring using hybrid ambient assisted living framework

Journal of Reliable Intelligent Environments ◽

10.1007/s40860-020-00100-7 ◽

2020 ◽

Vol 6 (2) ◽

pp. 95-106 ◽

Cited By ~ 2

Author(s):

Ashish Patel ◽

Jigarkumar Shah

Keyword(s):

Real Time ◽

Assisted Living ◽

Ambient Assisted Living ◽

Human Behaviour

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A Real-Time Demo for Acoustic Event Classification in Ambient Assisted Living Contexts

Proceedings of the 27th ACM International Conference on Multimedia ◽

10.1145/3343031.3350600 ◽

2019 ◽

Author(s):

Arunodhayan Sampath Kumar ◽

René Erler ◽

Danny Kowerko

Keyword(s):

Real Time ◽

Assisted Living ◽

Ambient Assisted Living ◽

Event Classification ◽

Acoustic Event

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A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications

Sensors ◽

10.3390/s20010170 ◽

2019 ◽

Vol 20 (1) ◽

pp. 170 ◽

Cited By ~ 6

Author(s):

Daniel G. Costa ◽

Francisco Vasques ◽

Paulo Portugal ◽

Ana Aguiar

Keyword(s):

Real Time ◽

Event Detection ◽

Smart City ◽

Smart Cities ◽

Sensor Nodes ◽

Risk Level ◽

Critical Events ◽

Emergency Situations ◽

Alerting System ◽

Emergency Systems

The development of efficient sensing technologies and the maturation of the Internet of Things (IoT) paradigm and related protocols have considerably fostered the expansion of sensor-based monitoring applications. A great number of those applications has been developed to monitor a set of information for better perception of the environment, with some of them being dedicated to identifying emergency situations. Current IoT-based emergency systems have limitations when considering the broader scope of smart cities, exploiting one or just a few monitoring variables or even allocating high computational burden to regular sensor nodes. In this context, we propose a distributed multi-tier emergency alerting system built around a number of sensor-based event detection units, providing real-time georeferenced information about the occurrence of critical events, while taking as input a configurable number of different scalar sensors and GPS data. The proposed system could then be used to detect and to deliver emergency alarms, which are computed based on the detected events, the previously known risk level of the affected areas and temporal information. Doing so, modularized and flexible perceptions of critical events are provided, according to the particularities of each considered smart city scenario. Besides implementing the proposed system in open-source electronic platforms, we also created a real-time visualization application to dynamically display emergency alarms on a map, demonstrating a feasible and useful application of the system as a supporting service. Therefore, this innovative approach and its corresponding physical implementation can bring valuable results for smart cities, potentially supporting the development of adaptive IoT-based emergency-aware applications.

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Desain Banyumas Smart City Berbasis Internet of Things (IoT) Menggunakan Fog Computing Architecture

Jurnal JEETech ◽

10.48056/jeetech.v1i1.2 ◽

2020 ◽

Vol 1 (1) ◽

pp. 7-13

Author(s):

Bayu Prastyo ◽

Faiz Syaikhoni Aziz ◽

Wahyu Pribadi ◽

A.N. Afandi

Keyword(s):

Internet Of Things ◽

Real Time ◽

Communication Technology ◽

Smart City ◽

Communication Systems ◽

Intelligent System ◽

Smart Cities ◽

Fog Computing ◽

The Internet ◽

Traffic Lights

Internet use in Banyumas Regency is now increasingly diverse according to the demands of the needs. The development of communication technology raises various aspects that also develop. For example, the use of the internet for a traffic light control system so that it can be adjusted according to the settings and can be monitored in real time. In the development of communication technology, the term Internet of Things (IoT) emerged as the concept of extending the benefits of internet communication systems to give impulses to other systems. In other words, IoT is used as a communication for remote control and monitoring by utilizing an internet connection. The Internet of Things in the era is now being developed to create an intelligent system for the purposes of controlling various public needs until the concept of the smart city emerges. Basically, smart cities utilize internet connections for many purposes such as controlling CCTV, traffic lights, controlling arm robots in the industry and storing data in hospitals. If the system is carried out directly from the device to the central server, there will be a very long queue of data while the system created requires speed and accuracy of time so that a system is needed that allows sufficient data control and processing to be carried out on network edge users. Then fog Computing is used with the hope that the smart city system can work with small latency values so that the system is more real-time in sending or receiving data.

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