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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 November 2017) | Viewed by 61952

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Prof. Dr. Min-Shiang Hwang

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Guest Editor

Department of Computer Science and Information Engineering, Asia University, Taichung 41354, Taiwan
Interests: mobile computing security; blockchain technology; cryptography; steganography; network and communication security
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Cheng-Ying Yang

E-Mail Website
Guest Editor

Department of Computer Science, University of Taipei, Taipei 10066, Taiwan
Interests: communication system; signal processing; information security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With Big Data, many applications are able to precisely predict forthcoming evidence. For example, weather predictions, traffic forecasts, the stock market, economic variations, and so on, are examples of practical applications. Useful application of Big Data benefits our conveniences in life. Among these successful applications, an important factor comes from data collection. Currently, the penetration of smartphone has been grown to a high degree; and mobile devices are ubiquitous around the world. A great deal of data can be collected with the sensors attached to these devices. The characteristics of data from mobile sensors are to provide information related to location. Practical application of this is expected to promote human living in the future.

Due to the growing usage of smartphones, a great deal of data can come from these mobile devices. This Special Issue aims at mobile sensor applications. Topics include, but not limited to, the following:

Data Access
Data Management
Data Analysis
Sensor Networks
Network Security
Transportation Protocol
Mobile Application

Prof. Dr. Min-Shiang Hwang
Prof. Dr. Cheng-Ying Yang
Guest Editors

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Keywords

Mobile Sensing Application
Open Data Security and Application
Alarm and Security Sensor Application
Data Mining Structures and Application
Mata Data Management
Social Media/Networks and Application
Dynamic Big Data Processing
Educational Application
Smart Home/City

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Published Papers (11 papers)

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Research

26 pages, 12260 KiB

Open AccessArticle

A Lightweight Continuous Authentication Protocol for the Internet of Things

by Yo-Hsuan Chuang, Nai-Wei Lo, Cheng-Ying Yang and Ssu-Wei Tang

Sensors 2018, 18(4), 1104; https://doi.org/10.3390/s18041104 - 5 Apr 2018

Cited by 65 | Viewed by 8837

Abstract

Modern societies are moving toward an information-oriented environment. To gather and utilize information around people’s modern life, tiny devices with all kinds of sensing devices and various sizes of gateways need to be deployed and connected with each other through the Internet or proxy-based wireless sensor networks (WSNs). Within this kind of Internet of Things (IoT) environment, how to authenticate each other between two communicating devices is a fundamental security issue. As a lot of IoT devices are powered by batteries and they need to transmit sensed data periodically, it is necessary for IoT devices to adopt a lightweight authentication protocol to reduce their energy consumption when a device wants to authenticate and transmit data to its targeted peer. In this paper, a lightweight continuous authentication protocol for sensing devices and gateway devices in general IoT environments is introduced. The concept of valid authentication time period is proposed to enhance robustness of authentication between IoT devices. To construct the proposed lightweight continuous authentication protocol, token technique and dynamic features of IoT devices are adopted in order to reach the design goals: the reduction of time consumption for consecutive authentications and energy saving for authenticating devices through by reducing the computation complexity during session establishment of continuous authentication. Security analysis is conducted to evaluate security strength of the proposed protocol. In addition, performance analysis has shown the proposed protocol is a strong competitor among existing protocols for device-to-device authentication in IoT environments. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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26 pages, 7170 KiB

Open AccessArticle

An Indoor Positioning-Based Mobile Payment System Using Bluetooth Low Energy Technology

by Alexander Yohan, Nai-Wei Lo and Doni Winata

Sensors 2018, 18(4), 974; https://doi.org/10.3390/s18040974 - 25 Mar 2018

Cited by 16 | Viewed by 8556

Abstract

The development of information technology has paved the way for faster and more convenient payment process flows and new methodology for the design and implementation of next generation payment systems. The growth of smartphone usage nowadays has fostered a new and popular mobile payment environment. Most of the current generation smartphones support Bluetooth Low Energy (BLE) technology to communicate with nearby BLE-enabled devices. It is plausible to construct an Over-the-Air BLE-based mobile payment system as one of the payment methods for people living in modern societies. In this paper, a secure indoor positioning-based mobile payment authentication protocol with BLE technology and the corresponding mobile payment system design are proposed. The proposed protocol consists of three phases: initialization phase, session key construction phase, and authentication phase. When a customer moves toward the POS counter area, the proposed mobile payment system will automatically detect the position of the customer to confirm whether the customer is ready for the checkout process. Once the system has identified the customer is standing within the payment-enabled area, the payment system will invoke authentication process between POS and the customer’s smartphone through BLE communication channel to generate a secure session key and establish an authenticated communication session to perform the payment transaction accordingly. A prototype is implemented to assess the performance of the proposed design for mobile payment system. In addition, security analysis is conducted to evaluate the security strength of the proposed protocol. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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20 pages, 578 KiB

Open AccessArticle

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range

by Chenlong He, Zuren Feng and Zhigang Ren

Sensors 2018, 18(2), 446; https://doi.org/10.3390/s18020446 - 3 Feb 2018

Cited by 11 | Viewed by 4713

Abstract

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham’s Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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19 pages, 7741 KiB

Open AccessArticle

A Police and Insurance Joint Management System Based on High Precision BDS/GPS Positioning

by Wenwei Zuo, Chi Guo, Jingnan Liu, Xuan Peng and Min Yang

Sensors 2018, 18(1), 169; https://doi.org/10.3390/s18010169 - 10 Jan 2018

Cited by 15 | Viewed by 5267

Abstract

Car ownership in China reached 194 million vehicles at the end of 2016. The traffic congestion index (TCI) exceeds 2.0 during rush hour in some cities. Inefficient processing for minor traffic accidents is considered to be one of the leading causes for road traffic jams. Meanwhile, the process after an accident is quite troublesome. The main reason is that it is almost always impossible to get the complete chain of evidence when the accident happens. Accordingly, a police and insurance joint management system is developed which is based on high precision BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning to process traffic accidents. First of all, an intelligent vehicle rearview mirror terminal is developed. The terminal applies a commonly used consumer electronic device with single frequency navigation. Based on the high precision BDS/GPS positioning algorithm, its accuracy can reach sub-meter level in the urban areas. More specifically, a kernel driver is built to realize the high precision positioning algorithm in an Android HAL layer. Thus the third-party application developers can call the general location Application Programming Interface (API) of the original standard Global Navigation Satellite System (GNSS) to get high precision positioning results. Therefore, the terminal can provide lane level positioning service for car users. Next, a remote traffic accident processing platform is built to provide big data analysis and management. According to the big data analysis of information collected by BDS high precision intelligent sense service, vehicle behaviors can be obtained. The platform can also automatically match and screen the data that uploads after an accident to achieve accurate reproduction of the scene. Thus, it helps traffic police and insurance personnel to complete remote responsibility identification and survey for the accident. Thirdly, a rapid processing flow is established in this article to meet the requirements to quickly handle traffic accidents. The traffic police can remotely identify accident responsibility and the insurance personnel can remotely survey an accident. Moreover, the police and insurance joint management system has been carried out in Wuhan, Central China’s Hubei Province, and Wuxi, Eastern China’s Jiangsu Province. In a word, a system is developed to obtain and analyze multisource data including precise positioning and visual information, and a solution is proposed for efficient processing of traffic accidents. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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1696 KiB

Open AccessArticle

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

by Youngmin Kim, Ki-Seong Lee and Chan-Gun Lee

Sensors 2017, 17(12), 2906; https://doi.org/10.3390/s17122906 - 14 Dec 2017

Cited by 2 | Viewed by 3786

Abstract

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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1793 KiB

Open AccessArticle

Obstacle Detection as a Safety Alert in Augmented Reality Models by the Use of Deep Learning Techniques

by Dawid Połap, Karolina Kęsik, Kamil Książek and Marcin Woźniak

Sensors 2017, 17(12), 2803; https://doi.org/10.3390/s17122803 - 4 Dec 2017

Cited by 25 | Viewed by 5896

Abstract

Augmented reality (AR) is becoming increasingly popular due to its numerous applications. This is especially evident in games, medicine, education, and other areas that support our everyday activities. Moreover, this kind of computer system not only improves our vision and our perception of the world that surrounds us, but also adds additional elements, modifies existing ones, and gives additional guidance. In this article, we focus on interpreting a reality-based real-time environment evaluation for informing the user about impending obstacles. The proposed solution is based on a hybrid architecture that is capable of estimating as much incoming information as possible. The proposed solution has been tested and discussed with respect to the advantages and disadvantages of different possibilities using this type of vision. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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3744 KiB

Open AccessArticle

Toward a Robust Security Paradigm for Bluetooth Low Energy-Based Smart Objects in the Internet-of-Things

by Shi-Cho Cha, Kuo-Hui Yeh and Jyun-Fu Chen

Sensors 2017, 17(10), 2348; https://doi.org/10.3390/s17102348 - 14 Oct 2017

Cited by 5 | Viewed by 5500

Abstract

Bluetooth Low Energy (BLE) has emerged as one of the most promising technologies to enable the Internet-of-Things (IoT) paradigm. In BLE-based IoT applications, e.g., wearables-oriented service applications, the Bluetooth MAC addresses of devices will be swapped for device pairings. The random address technique is adopted to prevent malicious users from tracking the victim’s devices with stationary Bluetooth MAC addresses and accordingly the device privacy can be preserved. However, there exists a tradeoff between privacy and security in the random address technique. That is, when device pairing is launched and one device cannot actually identify another one with addresses, it provides an opportunity for malicious users to break the system security via impersonation attacks. Hence, using random addresses may lead to higher security risks. In this study, we point out the potential risk of using random address technique and then present critical security requirements for BLE-based IoT applications. To fulfill the claimed requirements, we present a privacy-aware mechanism, which is based on elliptic curve cryptography, for secure communication and access-control among BLE-based IoT objects. Moreover, to ensure the security of smartphone application associated with BLE-based IoT objects, we construct a Smart Contract-based Investigation Report Management framework (SCIRM) which enables smartphone application users to obtain security inspection reports of BLE-based applications of interest with smart contracts. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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6247 KiB

Open AccessArticle

Autonomous Landmark Calibration Method for Indoor Localization

by Jae-Hoon Kim and Byoung-Seop Kim

Sensors 2017, 17(9), 1952; https://doi.org/10.3390/s17091952 - 24 Aug 2017

Cited by 3 | Viewed by 4534

Abstract

Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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1549 KiB

Open AccessArticle

Localization with Graph Diffusion Property

by Pengpeng Chen, Yuqing Yin, Shouwan Gao, Qiang Niu and Jun Gu

Sensors 2017, 17(7), 1636; https://doi.org/10.3390/s17071636 - 15 Jul 2017

Cited by 1 | Viewed by 4160

Abstract

Node localization is an essential issue in wireless sensor networks (WSNs). Many range-free localization methods have been proposed to satisfy the requirement of low-system cost. However, some range-free methods only depend on network connectivity, and others only utilize the proximity information attached in neighborhood ordering. To employ the strength of the above two aspects, this paper introduces a new metric system called Combined and Weighted Diffusion Distance (CWDD). CWDD is designed to obtain the relative distance among nodes based on both graph diffusion property and neighbor information. We implement our design by embedding CWDD into two well-known localization algorithms and evaluate it by extensive simulations. Results show that our design improves the localization performance in large scale and non-uniform sensor networks, which reduces positioning errors by as much as 26%. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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441 KiB

Open AccessArticle

A New Privacy-Preserving Handover Authentication Scheme for Wireless Networks

by Changji Wang, Yuan Yuan and Jiayuan Wu

Sensors 2017, 17(6), 1446; https://doi.org/10.3390/s17061446 - 20 Jun 2017

Cited by 4 | Viewed by 4855

Abstract

Handover authentication is a critical issue in wireless networks, which is being used to ensure mobile nodes wander over multiple access points securely and seamlessly. A variety of handover authentication schemes for wireless networks have been proposed in the literature. Unfortunately, existing handover authentication schemes are vulnerable to a few security attacks, or incur high communication and computation costs. Recently, He et al. proposed a handover authentication scheme PairHand and claimed it can resist various attacks without rigorous security proofs. In this paper, we show that PairHand does not meet forward secrecy and strong anonymity. More seriously, it is vulnerable to key compromise attack, where an adversary can recover the private key of any mobile node. Then, we propose a new efficient and provably secure handover authentication scheme for wireless networks based on elliptic curve cryptography. Compared with existing schemes, our proposed scheme can resist key compromise attack, and achieves forward secrecy and strong anonymity. Moreover, it is more efficient in terms of computation and communication. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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6325 KiB

Open AccessArticle

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks

by Tengyue Zou, Zhenjia Li, Shuyuan Li and Shouying Lin

Sensors 2017, 17(5), 1028; https://doi.org/10.3390/s17051028 - 4 May 2017

Cited by 10 | Viewed by 4523

Abstract

Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones. Full article

(This article belongs to the Special Issue Mobile Sensing Applications)

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