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Advances in Sensing, Processing and Transmission for IoT-Oriented Sensors Networks

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

Deadline for manuscript submissions: closed (31 March 2019) | Viewed by 112373

Special Issue Editors


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Guest Editor
Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, 80125 Naples, Italy
Interests: communication systems and networks test and measurement; measurements for Internet of Things applications; compressive sampling based measurements; measurements for Industry 4.0; measurement uncertainty
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Naples Federico II, 80138 Napoli, NA, Italy
Interests: augmented reality for remote educational applications; augmented reality for remote control of instrumentation and systems; Internet of Thing-based monitoring and measurement platforms; advanced sampling strategies for embedded measurement systems; measurement methods for IoT-oriented communication protocol and systems; methods for error compensation of MEMS-based inertial measurement units
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internet of things is a continuously evolving universe in which the three fundamental components of sensing, processing, and transmission of the measurement result must be kept up to date to guarantee suitable performance in the different fields of application. Regarding the sensing devices, besides the inherent metrological characteristics of the sensitive element and/or the transducer, energy-based evaluations are of interest to ensure the prolonged battery operation of the individual nodes of the wireless network. Equally important is the processing section that includes both the local level of the sensor node and the central one of the eventual management and measurement platform. The contributions concerning new technologies based on machine and deep learning for the recognition and measurement of quantities of interest are surely relevant in this issue. The last, but not least, key aspect is related to the communication protocols, as well as the integration strategies of the wireless sensor networks (WSNs) to the underlying data collection, storage, and processing infrastructure. Several features (data-rate, coverage, energy consumption, and synchronization) have to be considered in order to identify or possibly define the most suitable protocol for the desired application. Innovative data fusion strategies can be exploited to extend the capabilities of low-cost devices in order to perform complex tasks.

This Special Issue aims to highlight the latest research results and advances on technologies for sensors and wireless networks for IoT-oriented applications. You are therefore invited to submit original papers presenting significant advances with respect to the state of the art in the following topics, which include, but are not limited to:

  • Smart sensing node for IoT applications
  • Energy harvesting and optimized power supply management for IoT applications
  • Localization, geolocalization, and tracking of sensor nodes in indoor and outdoor IoT applications
  • Optimized local and distributed sampling strategies for IoT-oriented sensor nodes
  • Advanced and optimized digital signal processing for sensors nodes of IoT platforms
  • Advanced strategies for Big data, sensor data fusion, and data analytics
  • Machine and deep learning approaches for IoT-based WSNs
  • Definition and characterization of communication protocols for IoT oriented applications
  • Performance comparison, in terms of spectral efficiency, data-rate, and energy consumption or coverage, among different communication protocols in IoT-oriented applications
  • Integrated management of multiple moving nodes
  • Deep integration of data for innovative IoT applications
Prof. Dr. Leopoldo Angrisani
Assist. Prof. Dr. Rosario Schiano Lo Moriello
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart sensing node for IoT applications
  • Energy harvesting and optimized power supply management for IoT applications
  • Localization, geolocalization, and tracking of sensor nodes in indoor and outdoor IoT applications
  • Optimized local and distributed sampling strategies for IoT-oriented sensor nodes
  • Advanced and optimized digital signal processing for sensors nodes of IoT platforms
  • Advanced strategies for Big data, sensor data fusion, and data analytics
  • Machine and deep learning approaches for IoT-based WSNs
  • Definition and characterization of communication protocols for IoT oriented applications
  • Performance comparison, in terms of spectral efficiency, data-rate, and energy consumption or coverage, among different communication protocols in IoT-oriented applications
  • Integrated management of multiple moving nodes
  • Deep integration of data for innovative IoT applications

Published Papers (19 papers)

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16 pages, 3438 KiB  
Article
An Autonomous Wireless Device for Real-Time Monitoring of Water Needs
by Juan D. Borrero and Alberto Zabalo
Sensors 2020, 20(7), 2078; https://doi.org/10.3390/s20072078 - 07 Apr 2020
Cited by 27 | Viewed by 4117
Abstract
The agri-food sector is in constantly renewing, continuously demanding new systems that facilitate farmers´ work. Efficient agricultural practices are essential to increasing farm profitability, and reducing water consumption can be achieved by real-time monitoring of water needs. However, the prices of automatic systems [...] Read more.
The agri-food sector is in constantly renewing, continuously demanding new systems that facilitate farmers´ work. Efficient agricultural practices are essential to increasing farm profitability, and reducing water consumption can be achieved by real-time monitoring of water needs. However, the prices of automatic systems for collecting data from several sources (soil and climate) are expensive and their autonomy is very low. This paper presents a low-consumption solution using the Internet of Things (IoT) based on wireless sensor networks (WSNs) and long-range wide-area network (LoRaWAN) technologies. By means of low-power wide-area network (LPWAN) communication, a farmer can monitor the state of crops in real time thanks to a large number of sensors connected wirelessly and distributed across the farm. The wireless sensor node developed, called BoXmote, exhibits very low power, since it has been optimized both in terms of hardware and software. The result is a higher degree of autonomy than commercial motes. This will allow the farmer to have access to all of the information necessary to achieve an efficient irrigation management of his crops with full autonomy. Full article
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14 pages, 837 KiB  
Article
Impacts of Imperfect Channel State Information, Transceiver Hardware, and Self-Interference Cancellation on the Performance of Full-Duplex MIMO Relay System
by Ba Cao Nguyen, Nguyen Nhu Thang, Xuan Nam Tran and Le The Dung
Sensors 2020, 20(6), 1671; https://doi.org/10.3390/s20061671 - 17 Mar 2020
Cited by 16 | Viewed by 3457
Abstract
Imperfect channel state information (I-CSI) and imperfect transceiver hardware often happen in wireless communication systems due to the time-varying and random characteristics of both wireless channels and hardware components. The impacts of I-CSI and hardware impairments (HI) reduce not only the system performance [...] Read more.
Imperfect channel state information (I-CSI) and imperfect transceiver hardware often happen in wireless communication systems due to the time-varying and random characteristics of both wireless channels and hardware components. The impacts of I-CSI and hardware impairments (HI) reduce not only the system performance but also the self-interference cancellation (SIC) capability of full-duplex (FD) devices. To investigate the system performance in realistic scenarios, in this paper, we consider the performance of an FD multiple-input multiple-output (MIMO) relay system under the effects of I-CSI, imperfect SIC (I-SIC), and imperfect transceiver hardware. We mathematically derive the exact closed-form expressions of the outage probability (OP) and ergodic capacity of the considered HI-FD-MIMO relay system over Rayleigh fading channels with the existence of I-CSI, I-SIC, and HI. Numerical results indicate that the performance in terms of OP and capacity reaches saturation faster, especially when the channel estimation error, the residual self-interference (RSI), and HI levels are remarkable. Therefore, various solutions for effectively reducing the channel estimation error, RSI, and HI levels in the HI-FD-MIMO relay system should be carried out to improve the system performance. All derived mathematical expressions are verified through Monte-Carlo simulations. Full article
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21 pages, 4091 KiB  
Article
Low-Power and Low-Cost Environmental IoT Electronic Nose Using Initial Action Period Measurements
by Carlos J. García-Orellana, Miguel Macías-Macías, Horacio M. González-Velasco, Antonio García-Manso and Ramón Gallardo-Caballero
Sensors 2019, 19(14), 3183; https://doi.org/10.3390/s19143183 - 19 Jul 2019
Cited by 18 | Viewed by 4361
Abstract
In this work, we present a complete hardware development and current consumption study of a portable electronic nose designed for the Internet-of-Things (IoT). Thanks to the technique of measuring in the initial action period, it can be reliably powered with a moderate-sized battery. [...] Read more.
In this work, we present a complete hardware development and current consumption study of a portable electronic nose designed for the Internet-of-Things (IoT). Thanks to the technique of measuring in the initial action period, it can be reliably powered with a moderate-sized battery. The system is built around the well-known SoC (System on Chip) ESP8266EX, using low-cost electronics and standard sensors from Figaro’s TGS26xx series. This SoC, in addition to a powerful microcontroller, provides Wi-Fi connectivity, making it very suitable for IoT applications. The system also includes a precision analog-to-digital converter for the measurements and a charging module for the lithium battery. During its operation, the designed software takes measurements periodically, and keeps the microcontroller in deep-sleep state most of the time, storing several measurements before uploading them to the cloud. In the experiments and tests carried out, we have focused our work on the measurement and optimization of current consumption, with the aim of extending the battery life. The results show that taking measurements every 4 min and uploading data every five measurements, the battery of 750 mAh needs to be charged approximately once a month. Despite the fact that we have used a specific model of gas sensor, this methodology is quite generic and could be extended to other sensors with lower consumption, increasing very significantly the duration of the battery. Full article
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19 pages, 3022 KiB  
Article
An IoT Based Architecture for Enhancing the Effectiveness of Prototype Medical Instruments Applied to Neurodegenerative Disease Diagnosis
by Alessandro Depari, Dhiego Fernandes Carvalho, Paolo Bellagente, Paolo Ferrari, Emiliano Sisinni, Alessandra Flammini and Alessandro Padovani
Sensors 2019, 19(7), 1564; https://doi.org/10.3390/s19071564 - 31 Mar 2019
Cited by 14 | Viewed by 4341
Abstract
Human errors are probably the most critical cause of the large amount of medical accidents. Medical cyber-physical systems (MCPS) have been suggested as a possible approach for detecting and limiting the impact of errors and wrong procedures. However, during the initial development phase [...] Read more.
Human errors are probably the most critical cause of the large amount of medical accidents. Medical cyber-physical systems (MCPS) have been suggested as a possible approach for detecting and limiting the impact of errors and wrong procedures. However, during the initial development phase of medical instruments, regular MCPS systems are not a viable approach, because of the high costs of repeating complex validation procedures, due to modifications of the prototype instrument. In this work, a communication architecture, inspired by recent Internet of Things (IoT) advances, is proposed for connecting prototype instruments to the cloud, to allow direct and real-time interaction between developers and instrument operators. Without loss of generality, a real-world use case is addressed, dealing with the use of transcranial magnetic stimulation (TMS) for neurodegenerative disease diagnosis. The proposed infrastructure leverages on a message-oriented middleware, complemented by historical database for further data processing. Two of the most diffused protocols for cloud data exchange (MQTT and AMQP) have been investigated. The experimental setup has been focused on the real-time performance, which are the most challenging requirements. Time-related metrics confirm the feasibility of the proposed approach, resulting in an end-to-end delay on the order of few tens of milliseconds for local networks and up to few hundreds of milliseconds for geographical scale networks. Full article
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12 pages, 3530 KiB  
Article
A Novel Vehicle Detection Method Based on the Fusion of Radio Received Signal Strength and Geomagnetism
by Liangliang Lou, Jinyi Zhang, Yong Xiong and Yanliang Jin
Sensors 2019, 19(1), 58; https://doi.org/10.3390/s19010058 - 24 Dec 2018
Cited by 8 | Viewed by 5392
Abstract
A geomagnetic signal blind zone exists between the front and rear axle of high-chassis vehicle such as trucks and buses, which leads to multiple-detection problem in detecting those vehicles running at low speed on roads or error-detection problem in the case of the [...] Read more.
A geomagnetic signal blind zone exists between the front and rear axle of high-chassis vehicle such as trucks and buses, which leads to multiple-detection problem in detecting those vehicles running at low speed on roads or error-detection problem in the case of the stopping position of the vehicle is not standard when waiting for the traffic light to change. In order to improve the detection accuracy of any type of vehicle running at any speed, a novel two-sensors data fusion vehicle detection method through combining received signal strength from radio stations with geomagnetism around vehicles is designed and verified in the paper. Experimental results show that the accuracy of our proposed method can reach 95.4% and traditional single magnetism-based detection method was only 83.4% in the detection of high-chassis vehicles. Full article
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41 pages, 12398 KiB  
Article
Adding Active Slot Joint Larger Broadcast Radius for Fast Code Dissemination in WSNs
by Wei Yang, Wei Liu, Zhiwen Zeng, Anfeng Liu, Guosheng Huang, Neal N. Xiong and Zhiping Cai
Sensors 2018, 18(11), 4055; https://doi.org/10.3390/s18114055 - 20 Nov 2018
Cited by 12 | Viewed by 3899
Abstract
By using Software Defined Network (SDN) technology, senor nodes can get updated program code which can provide new features, so it has received extensive attention. How to effectively spread code to each node fast is a challenge issue in wireless sensor networks (WSNs). [...] Read more.
By using Software Defined Network (SDN) technology, senor nodes can get updated program code which can provide new features, so it has received extensive attention. How to effectively spread code to each node fast is a challenge issue in wireless sensor networks (WSNs). In this paper, an Adding Active Slot joint Larger Broadcast Radius (AAS-LBR) scheme is proposed for fast code dissemination. The AAS-LBR scheme combines the energy of data collection and code dissemination, making full use of the remaining energy in the far-sink area to increase the active slot and the broadcast radius to speed up the code dissemination. The main contributions of the proposed AAS-LBR scheme are the following: (1) Make full use of the remaining energy of the far sink area to expand the broadcast radius, so that the node broadcasts a longer distance. The wide range of broadcasts makes the number of nodes receiving code more, which speeds up the spread of code dissemination. (2) AAS-LBR uses two improved methods to further reduce the number of broadcasts and speed up the code dissemination: (a) When constructing the broadcast backbone whose nodes dominate all nodes in network and are responsible for broadcasting code, the active slot is added to the next hop node in a pipeline style on the diffusion path, which enables the code dissemination process to continue without pause. Thus, the code can quickly spread to the entire broadcast backbone. (b) For the nodes in the non-broadcast backbone whose nodes are dominated by the broadcast backbone and only for receiving code, an active slot is added coincident with its broadcast backbone’ active slot, which can reduce the time required for code dissemination and reduce the number of broadcasts. A lot of performance analysis and simulation results show that compared to previous schemed, the AAS-LBR scheme can balance energy consumption, the transmission delay can be reduced 43.09–78.69%, the number of broadcasts can be reduced 44.51–86.18% and the energy efficiency is improved by about 24.5%. Full article
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24 pages, 3263 KiB  
Article
Performance Analysis of IoT-Based Sensor, Big Data Processing, and Machine Learning Model for Real-Time Monitoring System in Automotive Manufacturing
by Muhammad Syafrudin, Ganjar Alfian, Norma Latif Fitriyani and Jongtae Rhee
Sensors 2018, 18(9), 2946; https://doi.org/10.3390/s18092946 - 04 Sep 2018
Cited by 244 | Viewed by 31281
Abstract
With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of [...] Read more.
With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process. Full article
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12 pages, 1096 KiB  
Article
Practical Use of Robot Manipulators as Intelligent Manufacturing Systems
by Pablo J. Alhama Blanco, Fares J. Abu-Dakka and Mohamed Abderrahim
Sensors 2018, 18(9), 2877; https://doi.org/10.3390/s18092877 - 31 Aug 2018
Cited by 13 | Viewed by 4921
Abstract
This paper presents features and advanced settings for a robot manipulator controller in a fully interconnected intelligent manufacturing system. Every system is made up of different agents. As also occurs in the Internet of Things and smart cities, the big issue here is [...] Read more.
This paper presents features and advanced settings for a robot manipulator controller in a fully interconnected intelligent manufacturing system. Every system is made up of different agents. As also occurs in the Internet of Things and smart cities, the big issue here is to ensure not only that implementation is key, but also that there is better common understanding among the main players. The commitment of all agents is still required to translate that understanding into practice in Industry 4.0. Mutual interactions such as machine-to-machine and man-to-machine are solved in real time with cyber physical capabilities. This paper explores intelligent manufacturing through the context of industrial robot manipulators within a Smart Factory. An online communication algorithm with proven intelligent manufacturing abilities is proposed to solve real-time interactions. The algorithm is developed to manage and control all robot parameters in real-time. The proposed tool in conjunction with the intelligent manufacturing core incorporates data from the robot manipulators into the industrial big data to manage the factory. The novelty is a communication tool that implements the Industry 4.0 standards to allow communications among the required entities in the complete system. It is achieved by the developed tool and implemented in a real robot and simulation Full article
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15 pages, 2515 KiB  
Article
PRG: A Distance Measurement Algorithm Based on Phase Regeneration
by Yansong Cui, Di Zhu and Yanxu Liu
Sensors 2018, 18(8), 2595; https://doi.org/10.3390/s18082595 - 08 Aug 2018
Cited by 2 | Viewed by 2976
Abstract
With the booming development of the Internet of things (IoT) industry, the demand of positioning technology in various IoT application scenarios is also greatly increased. To meet the positioning requirements of the IoT application, we propose a distance measurement method based on phase [...] Read more.
With the booming development of the Internet of things (IoT) industry, the demand of positioning technology in various IoT application scenarios is also greatly increased. To meet the positioning requirements of the IoT application, we propose a distance measurement method based on phase regeneration that can provide positioning capability for IoT applications in indoor and outdoor environments. The PRG algorithm consists of two phases: coarse ranging phase and fine ranging phase. Fingerprint positioning algorithm based on Gradient Boost Decision Tree (GBDT) is used to determine coarse distance. The host machine measures the difference between the transmitted carrier phase and the received regenerative carrier phase to fix the fine distance and then the coarse distance is used to determine the carrier phase integer ambiguity. Finally, high precision ranging is realized. Simulation results show that the PRG method can achieve range finding with decimeter level precision under the 10 MHz subcarrier frequency. Full article
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18 pages, 1625 KiB  
Article
Cognitive Interference Alignment Schemes for IoT Oriented Heterogeneous Two-Tier Networks
by Run Tian, Lin Ma, Zhe Wang and Xuezhi Tan
Sensors 2018, 18(8), 2548; https://doi.org/10.3390/s18082548 - 03 Aug 2018
Cited by 10 | Viewed by 2978
Abstract
This paper considers interference management and capacity improvement for Internet of Things (IoT) oriented two-tier networks by exploiting cognition between network tiers with interference alignment (IA). More specifically, we target our efforts on the next generation two-tier networks, where a tier of femtocell [...] Read more.
This paper considers interference management and capacity improvement for Internet of Things (IoT) oriented two-tier networks by exploiting cognition between network tiers with interference alignment (IA). More specifically, we target our efforts on the next generation two-tier networks, where a tier of femtocell serving multiple IoT devices shares the licensed spectrum with a tier of pre-existing macrocell via a cognitive radio. Aiming to manage the cross-tier interference caused by cognitive spectrum sharing as well as ensure an optimal capacity of the femtocell, two novel self-organizing cognitive IA schemes are proposed. First, we propose an interference nulling based cognitive IA scheme. In such a scheme, both co-tier and cross-tier interferences are aligned into the orthogonal subspace at each IoT receiver, which means all the interference can be perfectly eliminated without causing any performance degradation on the macrocell. However, it is known that the interference nulling based IA algorithm achieves its optimum only in high signal to noise ratio (SNR) scenarios, where the noise power is negligible. Consequently, when the imposed interference-free constraint on the femtocell can be relaxed, we also present a partial cognitive IA scheme that further enhances the network performance under a low and intermediate SNR. Additionally, the feasibility conditions and capacity analyses of the proposed schemes are provided. Both theoretical and numerical results demonstrate that the proposed cognitive IA schemes outperform the traditional orthogonal precoding methods in terms of network capacity, while preserving for macrocell users the desired quality of service. Full article
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16 pages, 3770 KiB  
Article
Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment
by Juanli Li, Jiacheng Xie, Zhaojian Yang and Junjie Li
Sensors 2018, 18(6), 1920; https://doi.org/10.3390/s18061920 - 13 Jun 2018
Cited by 25 | Viewed by 6138
Abstract
To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed [...] Read more.
To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. The IoT requires three basic architectural layers: a perception layer, network layer, and application layer. In the perception layer, we designed a collaborative acquisition system based on the ZigBee short distance wireless communication technology for key components of the mine hoisting equipment. Real-time data acquisition was achieved, and a network layer was created by using long-distance wireless General Packet Radio Service (GPRS) transmission. The transmission and reception platforms for remote data transmission were able to transmit data in real time. A fault diagnosis reasoning method is proposed based on the improved Dezert-Smarandache Theory (DSmT) evidence theory, and fault diagnosis reasoning is performed. Based on interactive technology, a humanized and visualized fault diagnosis platform is created in the application layer. The method is then verified. A fault diagnosis test of the mine hoisting mechanism shows that the proposed diagnosis method obtains complete diagnostic data, and the diagnosis results have high accuracy and reliability. Full article
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13 pages, 14102 KiB  
Article
A Design of Small Area, 0.95 mW, 612–1152 MHz Open Loop Injection-Locked Frequency Multiplier for IoT Sensor Applications
by SungJin Kim, Dong-Gyu Kim, Chanho Kim, Dong Soo Lee, Behnam Samadpoor Rikan, YoungGun Pu, Sang-Sun Yoo, Minjae Lee, KeumCheol Hwang, Youngoo Yang and Kang-Yoon Lee
Sensors 2018, 18(6), 1777; https://doi.org/10.3390/s18061777 - 01 Jun 2018
Cited by 3 | Viewed by 4650
Abstract
This paper presents a 612–1152 MHz Injection-Locked Frequency Multiplier (ILFM). The proposed ILFM is used to send an input signal to a receiver in only the I/Q mismatch calibration mode. Adopting a Phase-Locked Loop (PLL) to calibrate the receiver places a burden on [...] Read more.
This paper presents a 612–1152 MHz Injection-Locked Frequency Multiplier (ILFM). The proposed ILFM is used to send an input signal to a receiver in only the I/Q mismatch calibration mode. Adopting a Phase-Locked Loop (PLL) to calibrate the receiver places a burden on this system because of the additional area and power consumption that is required. Instead of the PLL, to satisfy high-frequency, low-jitter and low-area requirements, a Ring Oscillator is adopted in the system. The free-running frequency of the ILFM is automatically and digitally calibrated to reflect the frequency of the injected signal from the harmonics of the reference clock. To control the frequency of the ILFM, the load current is digitally tuned with a 6-bit digital control signal. The proposed ILFM locks to the target frequency using a digitally controlled Frequency Locked Loop (FLL). This chip is fabricated using 1-poly 6-metal 0.18 µm CMOS and has achieved the wide tuning range of 612–1152 MHz. The power consumption is 0.95 mW from a supply voltage of 1.8 V. The measured phase noise of the ILFM is −108 dBc/Hz at a 1 MHz offset. Full article
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21 pages, 8568 KiB  
Article
Development of Virtual Resource Based IoT Proxy for Bridging Heterogeneous Web Services in IoT Networks
by Wenquan Jin and DoHyeun Kim
Sensors 2018, 18(6), 1721; https://doi.org/10.3390/s18061721 - 26 May 2018
Cited by 22 | Viewed by 4888
Abstract
The Internet of Things is comprised of heterogeneous devices, applications, and platforms using multiple communication technologies to connect the Internet for providing seamless services ubiquitously. With the requirement of developing Internet of Things products, many protocols, program libraries, frameworks, and standard specifications have [...] Read more.
The Internet of Things is comprised of heterogeneous devices, applications, and platforms using multiple communication technologies to connect the Internet for providing seamless services ubiquitously. With the requirement of developing Internet of Things products, many protocols, program libraries, frameworks, and standard specifications have been proposed. Therefore, providing a consistent interface to access services from those environments is difficult. Moreover, bridging the existing web services to sensor and actuator networks is also important for providing Internet of Things services in various industry domains. In this paper, an Internet of Things proxy is proposed that is based on virtual resources to bridge heterogeneous web services from the Internet to the Internet of Things network. The proxy enables clients to have transparent access to Internet of Things devices and web services in the network. The proxy is comprised of server and client to forward messages for different communication environments using the virtual resources which include the server for the message sender and the client for the message receiver. We design the proxy for the Open Connectivity Foundation network where the virtual resources are discovered by the clients as Open Connectivity Foundation resources. The virtual resources represent the resources which expose services in the Internet by web service providers. Although the services are provided by web service providers from the Internet, the client can access services using the consistent communication protocol in the Open Connectivity Foundation network. For discovering the resources to access services, the client also uses the consistent discovery interface to discover the Open Connectivity Foundation devices and virtual resources. Full article
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20 pages, 1322 KiB  
Article
HiMeter: Telling You the Height Rather than the Altitude
by Haibo Ye, Kai Dong and Tao Gu
Sensors 2018, 18(6), 1712; https://doi.org/10.3390/s18061712 - 25 May 2018
Cited by 18 | Viewed by 4753
Abstract
The altitude of a moving user is important context information for mobile technologies and applications. However, with the increasing pervasiveness of smartphones and abundant mobile applications, developers and users have gradually discovered that the height is more useful than altitude in many situations. [...] Read more.
The altitude of a moving user is important context information for mobile technologies and applications. However, with the increasing pervasiveness of smartphones and abundant mobile applications, developers and users have gradually discovered that the height is more useful than altitude in many situations. The height is often a relative value, which is the vertical distance to the ground rather than the vertical distance to sea level, and we believe that it is useful in many applications, such as localization/navigation, sport/health and tourism/travel. In this paper, we first carried out a nation-wide online survey to confirm the desirability for the height information in mobile applications, and the result is positive. Then, we proposed HiMeter, an effective and accurate approach to calculating the height of the smartphone. HiMeter makes use of a low-power barometer on the smartphone and does not require GPS or back-server support. We concentrate on the vertical moving pattern of the user and designed several novel techniques, resulting in HiMeter not needing any reference points, and the complex process of calculating the absolute altitude can be avoided. The field studies show that HiMeter can achieve an accuracy of within 5 m in 90% of cases indoors and an accuracy of 10 m in 83% of cases outdoors. Compared to the existing works, HiMeter is more accurate and practical and is more suitable for usage in many mobile applications. Full article
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13 pages, 335 KiB  
Article
Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things
by Yanjing Sun, Yiyu Guo, Song Li, Dapeng Wu and Bin Wang
Sensors 2018, 18(5), 1572; https://doi.org/10.3390/s18051572 - 15 May 2018
Cited by 20 | Viewed by 3849
Abstract
In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, [...] Read more.
In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness. Full article
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18 pages, 1704 KiB  
Article
An INS/WiFi Indoor Localization System Based on the Weighted Least Squares
by Jian Chen, Gang Ou, Ao Peng, Lingxiang Zheng and Jianghong Shi
Sensors 2018, 18(5), 1458; https://doi.org/10.3390/s18051458 - 07 May 2018
Cited by 42 | Viewed by 5271
Abstract
For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a [...] Read more.
For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m. Full article
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17 pages, 1749 KiB  
Article
VeLoc: Finding Your Car in Indoor Parking Structures
by Ruipeng Gao, Fangpu He and Teng Li
Sensors 2018, 18(5), 1403; https://doi.org/10.3390/s18051403 - 02 May 2018
Cited by 3 | Viewed by 3864
Abstract
While WiFi-based indoor localization is attractive, there are many indoor places without WiFi coverage with a strong demand for localization capability. This paper describes a system and associated algorithms to address the indoor vehicle localization problem without the installation of additional infrastructure. In [...] Read more.
While WiFi-based indoor localization is attractive, there are many indoor places without WiFi coverage with a strong demand for localization capability. This paper describes a system and associated algorithms to address the indoor vehicle localization problem without the installation of additional infrastructure. In this paper, we propose VeLoc, which utilizes the sensor data of smartphones in the vehicle together with the floor map of the parking structure to track the vehicle in real time. VeLoc simultaneously harnesses constraints imposed by the map and environment sensing. All these cues are codified into a novel augmented particle filtering framework to estimate the position of the vehicle. Experimental results show that VeLoc performs well when even the initial position and the initial heading direction of the vehicle are completely unknown. Full article
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20 pages, 3638 KiB  
Article
Building-in-Briefcase: A Rapidly-Deployable Environmental Sensor Suite for the Smart Building
by Kevin Weekly, Ming Jin, Han Zou, Christopher Hsu, Chris Soyza, Alexandre Bayen and Costas Spanos
Sensors 2018, 18(5), 1381; https://doi.org/10.3390/s18051381 - 29 Apr 2018
Cited by 29 | Viewed by 6582
Abstract
A building’s environment has profound influence on occupant comfort and health. Continuous monitoring of building occupancy and environment is essential to fault detection, intelligent control, and building commissioning. Though many solutions for environmental measuring based on wireless sensor networks exist, they are not [...] Read more.
A building’s environment has profound influence on occupant comfort and health. Continuous monitoring of building occupancy and environment is essential to fault detection, intelligent control, and building commissioning. Though many solutions for environmental measuring based on wireless sensor networks exist, they are not easily accessible to households and building owners who may lack time or technical expertise needed to set up a system and get quick and detailed overview of environmental conditions. Building-in-Briefcase (BiB) is a portable sensor network platform that is trivially easy to deploy in any building environment. Once the sensors are distributed, the environmental data is collected and communicated to the BiB router via the Transmission Control Protocol/Internet Protocol (TCP/IP) and WiFi technology, which then forwards the data to the central database securely over the internet through a 3G radio. The user, with minimal effort, can access the aggregated data and visualize the trends in real time on the BiB web portal. Paramount to the adoption and continued operation of an indoor sensing platform is battery lifetime. This design has achieved a multi-year lifespan by careful selection of components, an efficient binary communications protocol and data compression. Our BiB sensor is capable of collecting a rich set of environmental parameters, and is expandable to measure others, such as CO 2 . This paper describes the power characteristics of BiB sensors and their occupancy estimation and activity recognition functionality. We have demonstrated large-scale deployment of BiB throughout Singapore. Our vision is that, by monitoring thousands of buildings through BiB, it would provide ample research opportunities and opportunities to identify ways to improve the building environment and energy efficiency. Full article
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Review

Jump to: Research

14 pages, 1273 KiB  
Review
An Outlook on Physical and Virtual Sensors for a Socially Interactive Internet
by Ngombo Armando, André Rodrigues, Vasco Pereira, Jorge Sá Silva and Fernando Boavida
Sensors 2018, 18(8), 2578; https://doi.org/10.3390/s18082578 - 06 Aug 2018
Cited by 15 | Viewed by 3350
Abstract
The Internet keeps changing at a rapid pace, driven mainly by the emerging concepts and applications that make it aware of the physical world and responsive to user context. The Internet of Things (IoT) concept is quickly giving way to more advanced and [...] Read more.
The Internet keeps changing at a rapid pace, driven mainly by the emerging concepts and applications that make it aware of the physical world and responsive to user context. The Internet of Things (IoT) concept is quickly giving way to more advanced and highly interactive environments that go well beyond the mere sensing of the physical world. Today, in addition to traditional electronic devices, IoT sensing/actuating includes both software and human-based entities. This paper provides an outlook on the future of sensing/actuating approaches on the Internet at large, which we see increasingly related to all kinds of socially interactive technologies. With these objectives in mind, we propose a taxonomy to deal with the heterogeneity of sensing/actuating approaches in IoT. We also analyse the state-of-the-art of Social Sensing. Finally, we identify open issues and associated research opportunities, the main ones being the integration of all sensing approaches, the combination of social sciences, engineering, and computing as enablers of context-aware, cognitive applications and, last but not least, the unified management of large sets of very heterogeneous sensors/actuators. Full article
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