Sustainability

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12 pages, 1293 KiB

Open AccessArticle

sEMG-Based Gesture Recognition with Convolution Neural Networks

by Zhen Ding, Chifu Yang, Zhihong Tian, Chunzhi Yi, Yunsheng Fu and Feng Jiang

Sustainability 2018, 10(6), 1865; https://doi.org/10.3390/su10061865 - 4 Jun 2018

Cited by 93 | Viewed by 6166

The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we [...] Read more.

The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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11 pages, 2370 KiB

Open AccessArticle

Sustainable Situation-Aware Recommendation Services with Collective Intelligence

by Yuchul Jung, Cinyoung Hur and Mucheol Kim

Sustainability 2018, 10(5), 1632; https://doi.org/10.3390/su10051632 - 18 May 2018

Cited by 6 | Viewed by 3631

Abstract

With the recent advances of information and communication technology, people communicate with each other through online communities or social networking services, such as PatientsLikeMe and Facebook. One of the key challenges in aspects of providing sustainable situation-aware services is how to utilize peoples’ [...] Read more.

With the recent advances of information and communication technology, people communicate with each other through online communities or social networking services, such as PatientsLikeMe and Facebook. One of the key challenges in aspects of providing sustainable situation-aware services is how to utilize peoples’ experiences shared as reusable social-intelligence. If domain-specific collective intelligence is well constructed, the knowledge usages can be extended to situation-awareness-based personal situation understanding, and sustainable recommendation services with user intent. In this paper, we introduce a sustainable situation-awareness supporting framework based on text-mining techniques and a domain-specific knowledge model, the so-called Service Quality Model for Hospitals (SQM-H). Different from obtaining sustainable contexts from heterogeneous sensors surrounding users, it aggregates SQM-H based service-specific knowledge from online health communities. Our framework includes a set of components: data aggregation, text-mining, service quality analysis, and open Application Programming Interface (APIs) for recommendation services. Those components have been designed to deal with users’ immediate request, providing service quality related information reflected in collective intelligence and analyzed information based on that along with the SQM-H. As a proof of concept, we implemented a prototype system which interacts with users through smartphone user interface. Our framework supports qualitative and quantitative information based on SQM-H and statistical analyses for the given user queries. Through the implementation and user tests, we confirmed an increased knowledge support for decision-making and an easy mashup with provided Open APIs. We believe that the suggested situation-awareness supporting framework can be applied to numerous sustainable applications related to healthcare and wellness domain areas if domain-specific knowledge models are redesigned. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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21 pages, 1854 KiB

Open AccessArticle

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

by Erfan Babaee Tirkolaee, Ali Asghar Rahmani Hosseinabadi, Mehdi Soltani, Arun Kumar Sangaiah and Jin Wang

Sustainability 2018, 10(5), 1366; https://doi.org/10.3390/su10051366 - 27 Apr 2018

Cited by 95 | Viewed by 6750

Abstract

Greenhouse gases (GHG) are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing [...] Read more.

Greenhouse gases (GHG) are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing Problem (G-CARP) with the aim of minimizing total cost including the cost of generation and emission of greenhouse gases, the cost of vehicle usage and routing cost. The cost of generation and emission of greenhouse gases is based on the calculation of the amount of carbon dioxide emitted from vehicles, which depends on such factors as the vehicle speed, weather conditions, load on the vehicle and traveled distance. The main applications of this problem are in municipalities for urban waste collection, road surface marking and so forth. Due to NP-hardness of the problem, a Hybrid Genetic Algorithm (HGA) is developed, wherein a heuristic and simulated annealing algorithm are applied to generate initial solutions and a Genetic Algorithm (GA) is then used to generate the best possible solution. The obtained numerical results indicate that the proposed algorithm could present desirable performance within a suitable computational run time. Finally, a sensitivity analysis is implemented on the maximum available time of the vehicles in order to determine the optimal policy. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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14 pages, 9184 KiB

Open AccessArticle

Augmented-Reality Visualization of Aerodynamics Simulation in Sustainable Cloud Computing

by Myungil Kim, Sukkeun Yi, Daeyong Jung, Sangjin Park and Dongwoo Seo

Sustainability 2018, 10(5), 1362; https://doi.org/10.3390/su10051362 - 27 Apr 2018

Cited by 16 | Viewed by 5840

Abstract

This paper proposes visualization based on augmented reality (AR) for aerodynamics simulation in a sustainable cloud computing environment that allows the Son of Grid Engine different types of computers to perform concurrent job requests. A simulation of an indoor air-purification system is performed [...] Read more.

This paper proposes visualization based on augmented reality (AR) for aerodynamics simulation in a sustainable cloud computing environment that allows the Son of Grid Engine different types of computers to perform concurrent job requests. A simulation of an indoor air-purification system is performed using OpenFOAM computational fluid dynamics solver in the cloud computing environment. Post-processing converts the results to a form that is suitable for AR visualization. Simulation results can be displayed on devices, such as smart phones, tablets, and Microsoft HoloLens. This AR visualization allows for users to monitor purification of indoor air in real time. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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24 pages, 4278 KiB

Open AccessArticle

Constructing Differentiated Educational Materials Using Semantic Annotation for Sustainable Education in IoT Environments

by Yongsung Kim, Jihoon Moon and Eenjun Hwang

Sustainability 2018, 10(4), 1296; https://doi.org/10.3390/su10041296 - 23 Apr 2018

Cited by 7 | Viewed by 4597

Abstract

Recently, Internet of Things (IoT) technology has become a hot trend and is used in a wide variety of fields. For instance, in education, this technology contributes to improving learning efficiency in the class by enabling learners to interact with physical devices and [...] Read more.

Recently, Internet of Things (IoT) technology has become a hot trend and is used in a wide variety of fields. For instance, in education, this technology contributes to improving learning efficiency in the class by enabling learners to interact with physical devices and providing appropriate learning content based on this interaction. Such interaction data can be collected through the physical devices to define personal data. In the meanwhile, multimedia contents in this environment usually have a wide variety of formats and standards, making it difficult for computers to understand their meaning and reuse them. This could be a serious obstacle to the effective use or sustainable management of educational contents in IoT-based educational systems. In order to solve this problem, in this paper, we propose a semantic annotation scheme for sustainable computing in the IoT environment. More specifically, we first show how to collect appropriate multimedia contents and interaction data. Next, we calculate the readability of learning materials and define the user readability level to provide appropriate contents to the learners. Finally, we describe our semantic annotation scheme and show how to annotate collected data using our scheme. We implement a prototype system and show that our scheme can achieve efficient management of various learning materials in the IoT-based educational system. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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18 pages, 11415 KiB

Open AccessArticle

Efficient Protection of Android Applications through User Authentication Using Peripheral Devices

by Jinseong Kim and Im Y. Jung

Sustainability 2018, 10(4), 1290; https://doi.org/10.3390/su10041290 - 22 Apr 2018

Cited by 1 | Viewed by 4784

Abstract

Android applications store large amounts of sensitive information that may be exposed and exploited. To prevent this security risk, some applications such as Syrup and KakaoTalk use physical device values to authenticate or encrypt application data. However, by manipulating these physical device values, [...] Read more.

Android applications store large amounts of sensitive information that may be exposed and exploited. To prevent this security risk, some applications such as Syrup and KakaoTalk use physical device values to authenticate or encrypt application data. However, by manipulating these physical device values, an attacker can circumvent the authentication by executing a Same Identifier Attack and obtain the same application privileges as the user. In our work, WhatsApp, KakaoTalk, Facebook, Amazon, and Syrup were subjected to the Same Identifier Attack, and it was found that an attacker could gain the same privileges as the user, in all five applications. To solve such a problem, we propose a technical scheme—User Authentication using Peripheral Devices. We applied the proposed scheme to a Nexus 5X smartphone running Android version 7.1 and confirmed that the average execution time was 0.005 s, which does not affect the other applications’ execution significantly. We also describe the security aspects of the proposed scheme and its compatibility with the Android platform and other applications. The proposed scheme is practical and efficient in terms of resource usage; therefore, it will be useful for Android users to improve Android application security. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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14 pages, 744 KiB

Open AccessArticle

Instant Social Networking with Startup Time Minimization Based on Mobile Cloud Computing

by Lien-Wu Chen, Yu-Fan Ho and Ming-Fong Tsai

Sustainability 2018, 10(4), 1195; https://doi.org/10.3390/su10041195 - 16 Apr 2018

Cited by 3 | Viewed by 3458

Abstract

Mobile communication and handheld devices are currently extremely popular, and provide people with convenient and instant platforms for social networking. However, existing social networking services cannot offer efficient human-machine interfaces or intuitive user experiences. Mobile users must manually input account information and find [...] Read more.

Mobile communication and handheld devices are currently extremely popular, and provide people with convenient and instant platforms for social networking. However, existing social networking services cannot offer efficient human-machine interfaces or intuitive user experiences. Mobile users must manually input account information and find targets from search results when attempting to add someone to their friend list on social networking sites, such as Facebook and Twitter. Additionally, mobile users may not be able to identify correct targets because some usernames are identical. Typos may occur during the input process due to unfamiliar identifiers, further increasing the total operation time. To encourage social initiation between mobile users, we design an instant social networking framework, called SocialYou, to minimize the startup time based on mobile cloud computing. SocialYou proposes an efficient architecture and innovative human-machine interfaces to alleviate the complexity and difficulty for mobile users using handheld devices. In particular, we implement an Android-based prototype to verify the feasibility and superiority of SocialYou. The experimental results show that SocialYou outperforms the existing methods and saves substantial amounts of operation time for mobile social networking. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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1878 KiB

Open AccessArticle

Energy-Aware Cluster Reconfiguration Algorithm for the Big Data Analytics Platform Spark

by Kairong Duan, Simon Fong, Wei Song, Athanasios V. Vasilakos and Raymond Wong

Sustainability 2017, 9(12), 2357; https://doi.org/10.3390/su9122357 - 18 Dec 2017

Cited by 3 | Viewed by 4008

Abstract

The development of Cloud computing and data analytics technologies has made it possible to process big data faster. Distributed computing schemes, for instance, can help to reduce the time required for data analysis and thus enhance its efficiency. However, fewer researchers have paid [...] Read more.

The development of Cloud computing and data analytics technologies has made it possible to process big data faster. Distributed computing schemes, for instance, can help to reduce the time required for data analysis and thus enhance its efficiency. However, fewer researchers have paid attention to the problem of the high-energy consumption of the cluster, placing a heavy burden on the environment, especially when the number of nodes is extremely large. As a consequence, the principle of sustainable development is violated. Considering this problem, this paper proposes an approach that can be applied to remove less-efficient nodes or to migrate over-utilized nodes of the cluster so as to adjust the load of the cluster properly and thereby achieve the goal of energy conservation. Furthermore, in order to testify the performance of the proposed methodology, we present the simulation results implemented by using CloudSim. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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2236 KiB

Open AccessArticle

Evaluating Retrieval Effectiveness by Sustainable Rank List

by Tenvir Ali, Zeeshan Jhandir, Ingyu Lee, Byung-Won On and Gyu Sang Choi

Sustainability 2017, 9(7), 1203; https://doi.org/10.3390/su9071203 - 8 Jul 2017

Cited by 1 | Viewed by 5088

Abstract

The Internet of Things (IoT) and Big Data are among the most popular emerging fields of computer science today. IoT devices are creating an enormous amount of data daily on a different scale; hence, search engines must meet the requirements of rapid ingestion [...] Read more.

The Internet of Things (IoT) and Big Data are among the most popular emerging fields of computer science today. IoT devices are creating an enormous amount of data daily on a different scale; hence, search engines must meet the requirements of rapid ingestion and processing followed by accurate and fast extraction. Researchers and students from the field of computer science query the search engines on these topics to reveal a wealth of IoT-related information. In this study, we evaluate the relative performance of two search engines: Bing and Yandex. This work proposes an automatic scheme that populates a sustainable optimal rank list of search results with higher precision for IoT-related topics. The proposed scheme rewrites the seed query with the help of attribute terms extracted from the page corpus. Additionally, we use newness and geo-sensitivity-based boosting and dampening of web pages for the re-ranking process. To evaluate the proposed scheme, we use an evaluation matrix based on discounted cumulative gain (DCG), normalized DCG (nDCG), and mean average precision (MAP_n). The experimental results show that the proposed scheme achieves scores of MAP@5 = 0.60, DCG₅ = 4.43, and nDCG₅ = 0.95 for general queries; DCG₅ = 4.14 and nDCG₅ = 0.93 for time-stamp queries; and DCG₅ = 4.15 and nDCG₅ = 0.96 for geographical location-based queries. These outcomes validate the usefulness of the suggested system in helping a user to access IoT-related information. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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27373 KiB

Open AccessArticle

Velocity Obstacle Based 3D Collision Avoidance Scheme for Low-Cost Micro UAVs

by Myungwhan Choi, Areeya Rubenecia, Taeshik Shon and Hyo Hyun Choi

Sustainability 2017, 9(7), 1174; https://doi.org/10.3390/su9071174 - 6 Jul 2017

Cited by 19 | Viewed by 5936

Abstract

An unmanned aerial vehicle (UAV) must be able to safely reach its destination even, when it can only gather limited information about its environment. When an obstacle is detected, the UAV must be able to choose a path that will avoid collision with [...] Read more.

An unmanned aerial vehicle (UAV) must be able to safely reach its destination even, when it can only gather limited information about its environment. When an obstacle is detected, the UAV must be able to choose a path that will avoid collision with the obstacle. For the collision avoidance scheme, we apply the velocity obstacle approach since it is applicable even with the UAV’s limited sensing capability. To be able to apply the velocity obstacle approach, we need to know the parameter values of the obstacle such as its size, current velocity and current position. However, due to the UAV’s limited sensing capability, such information about the obstacle is not available. Thus, by evaluating sensor readings, we get the changes in the possible positions of the obstacle in order to generate the velocity obstacle and make the UAV choose a collision-free trajectory towards the destination. We performed simulation on different obstacle movements and the collision-free trajectory of the UAV is shown in the simulation results. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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1408 KiB

Open AccessArticle

Comparative Analysis of Intelligent Transportation Systems for Sustainable Environment in Smart Cities

by Anandkumar Balasubramaniam, Anand Paul, Won-Hwa Hong, HyunCheol Seo and Jeong Hong Kim

Sustainability 2017, 9(7), 1120; https://doi.org/10.3390/su9071120 - 28 Jun 2017

Cited by 50 | Viewed by 9769

Abstract

In recent works on the Internet of Vehicles (IoV), “intelligent” and “sustainable” have been the buzzwords in the context of transportation. Maintaining sustainability in IoV is always a challenge. Sustainability in IoV can be achieved not only by the use of pollution-free vehicular [...] Read more.

In recent works on the Internet of Vehicles (IoV), “intelligent” and “sustainable” have been the buzzwords in the context of transportation. Maintaining sustainability in IoV is always a challenge. Sustainability in IoV can be achieved not only by the use of pollution-free vehicular systems, but also by maintenance of road traffic safety or prevention of accidents or collisions. With the aim of establishing an effective sustainable transportation planning system, this study performs a short analysis of existing sustainable transportation methods in the IoV. This study also analyzes various characteristics of sustainability and the advantages and disadvantages of existing transportation systems. Toward the end, this study provides a clear suggestion for effective sustainable transportation planning aimed at the maintenance of an eco-friendly environment and road traffic safety, which, in turn, would lead to a sustainable transportation system. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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1782 KiB

Open AccessArticle

An Improved Routing Optimization Algorithm Based on Travelling Salesman Problem for Social Networks

by Naixue Xiong, Wenliang Wu and Chunxue Wu

Sustainability 2017, 9(6), 985; https://doi.org/10.3390/su9060985 - 8 Jun 2017

Cited by 10 | Viewed by 4230

Abstract

A social network is a social structure, which is organized by the relationships or interactions between individuals or groups. Humans link the physical network with social network, and the services in the social world are based on data and analysis, which directly influence [...] Read more.

A social network is a social structure, which is organized by the relationships or interactions between individuals or groups. Humans link the physical network with social network, and the services in the social world are based on data and analysis, which directly influence decision making in the physical network. In this paper, we focus on a routing optimization algorithm, which solves a well-known and popular problem. Ant colony algorithm is proposed to solve this problem effectively, but random selection strategy of the traditional algorithm causes evolution speed to be slow. Meanwhile, positive feedback and distributed computing model make the algorithm quickly converge. Therefore, how to improve convergence speed and search ability of algorithm is the focus of the current research. The paper proposes the improved scheme. Considering the difficulty about searching for next better city, new parameters are introduced to improve probability of selection, and delay convergence speed of algorithm. To avoid the shortest path being submerged, and improve sensitive speed of finding the shortest path, it updates pheromone regulation formula. The results show that the improved algorithm can effectively improve convergence speed and search ability for achieving higher accuracy and optimal results. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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4815 KiB

Open AccessArticle

Data Compatibility to Enhance Sustainable Capabilities for Autonomous Analytics in IoT

by Kaleem Razzaq Malik, Masood Habib, Shehzad Khalid, Farhan Ullah, Muhammad Umar, Taimur Sajjad and Awais Ahmad

Sustainability 2017, 9(6), 877; https://doi.org/10.3390/su9060877 - 23 May 2017

Cited by 6 | Viewed by 5140

Abstract

The collection of raw data is based on sensors embedded in devices or the environment for real-time data extraction. Nowadays, the Internet of Things (IoT) environment is used to support autonomous data collection by reducing human involvement. It is hard to analyze such [...] Read more.

The collection of raw data is based on sensors embedded in devices or the environment for real-time data extraction. Nowadays, the Internet of Things (IoT) environment is used to support autonomous data collection by reducing human involvement. It is hard to analyze such data, especially when working with the sensors in a real-time environment. On using data analytics in IoT with the help of RDF, many issues can be resolved. Resultant data will have a better chance of quality analytics by reforming data into the semantical annotation. Industrial correspondence through data will be improved by the induction of semantics at large due to efficient data capturing, whereas one popular medium of sensors’ data storage is Relational Database (RDB). This study provides a complete automated mechanism to transform from loosely structured data stored in RDB into RDF. These data are obtained from sensors in semantically annotated RDF stores. The given study comprises methodology for improving compatibility by introducing bidirectional transformation between classical DB and RDF data stores to enhance the sustainable capabilities of IoT systems for autonomous analytics. Two case studies, one on weather and another on heart-rate measurement collections through IoT sensors, are used to show the transformation process in operation. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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4072 KiB

Open AccessArticle

A Study on User-Oriented and Intelligent Service Design in Sustainable Computing: A Case of Shipbuilding Industry Safety

by Taehee Joe and Hangbae Chang

Sustainability 2017, 9(4), 544; https://doi.org/10.3390/su9040544 - 4 Apr 2017

Cited by 11 | Viewed by 5750

Abstract

Most business services based on Ubiquitous Computing are being designed with a sole focus on the technological sector, without considering business elements. In light of this trend, this study was intended to design a user-oriented u-Business service for preventing and promptly responding to [...] Read more.

Most business services based on Ubiquitous Computing are being designed with a sole focus on the technological sector, without considering business elements. In light of this trend, this study was intended to design a user-oriented u-Business service for preventing and promptly responding to industrial disasters at shipbuilding sites using a systematic methodology. Specifically, major danger elements of disasters in need of preferential preventive and responsive measures were derived as business opportunities unfulfilled by the current process, and then a u-Business service was developed to prevent/respond to such dangers. Statistical analysis was performed on the developed services according to evaluation models, and the final u-Business service was selected based on this analysis. Resources and information systems were designed to support the chosen service. Full article

(This article belongs to the Special Issue Autonomous and Sustainable Computing for preparing the Internet of Things Environment)

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