Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as 'fat', 'healthy' or 'thin' to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios.
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
In this paper, we present the development and testing of an optical-based sensor for monitoring the corrosion of reinforcement rebar. The testing was carried out using an 80% etched-cladding Fibre Bragg grating sensor to monitor the production of corrosion waste in a localized region of the rebar. Progression of corrosion can be sensed by observing the reflected wavelength shift of the FBG sensor. With the presence of corrosion, the etched-FBG reflected spectrum was shifted by 1.0 nm. In addition, with an increase in fringe pattern and continuously, step-like drop in power of the Bragg reflected spectrum was also displayed.
Wireless sensor networks basically consist of low cost sensor nodes which collect data from environment and relay them to a sink, where they will be subsequently processed. Since wireless nodes are severely power-constrained, the major concern is how to conserve the nodes' energy so that network lifetime can be extended significantly. Employing one static sink can rapidly exhaust the energy of sink neighbors. Furthermore, using a non-optimal single path together with a maximum transmission power level may quickly deplete the energy of individual nodes on the route. This all results in unbalanced energy consumption through the sensor field, and hence a negative effect on the network lifetime. In this paper, we present a comprehensive taxonomy of the various mechanisms applied for increasing the network lifetime. These techniques, whether in the routing or cross-layer area, fall within the following types: multi-sink, mobile sink, multi-path, power control and bio-inspired algorithms, depending on the protocol operation. In this taxonomy, special attention has been devoted to the multi-sink, power control and bio-inspired algorithms, which have not yet received much consideration in the literature. Moreover, each class covers a variety of the state-of-the-art protocols, which should provide ideas for potential future works. Finally, we compare these mechanisms and discuss open research issues.
Recent years have witnessed a growing interest in deploying large populations of microsensors that collaborate in a distributed manner to gather and process sensory data and deliver them to a sink node through wireless communications systems. Currently, there is a lot of interest in data routing for Wireless Sensor Networks (WSNs) due to their unique challenges compared to conventional routing in wired networks. In WSNs, each data routing approach follows a specific goal (goals) according to the application. Although the general goal of every data routing approach in WSNs is to extend the network lifetime and every approach should be aware of the energy level of the nodes, data routing approaches may focus on one (or some) specific goal(s) depending on the application. Thus, existing approaches can be categorized according to their routing goals. In this paper, the main goals of data routing approaches in sensor networks are described. Then, the best known and most recent data routing approaches in WSNs are classified and studied according to their specific goals.
Parkinson's Disease (PD) is characterized as the commonest neurodegenerative illness that gradually degenerates the central nervous system. The goal of this review is to come out with a summary of the recent progress of numerous forms of sensors and systems that are related to diagnosis of PD in the past decades. The paper reviews the substantial researches on the application of technological tools (objective techniques) in the PD field applying different types of sensors proposed by previous researchers. In addition, this also includes the use of clinical tools (subjective techniques) for PD assessments, for instance, patient self-reports, patient diaries and the international gold standard reference scale, Unified Parkinson Disease Rating Scale (UPDRS). Comparative studies and critical descriptions of these approaches have been highlighted in this paper, giving an insight on the current state of the art. It is followed by explaining the merits of the multiple sensor fusion platform compared to single sensor platform for better monitoring progression of PD, and ends with thoughts about the future direction towards the need of multimodal sensor integration platform for the assessment of PD.
Resource bound security solutions have facilitated the mitigation of spatio-temporal attacks by altering protocol semantics to provide minimal security while maintaining an acceptable level of performance. The Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing protocol for Wireless Sensor Network (WSN) has been proposed to achieve a minimal selection of malicious nodes by introducing a dynamic collection window period to the protocol's semantics. However, its selection scheme suffers substantial packet losses due to the utilization of a single distance based parameter for node selection. In this paper, we propose a Fuzzy-based Geographic Forwarding protocol (FuGeF) to minimize packet loss, while maintaining performance. The FuGeF utilizes a new form of dynamism and introduces three selection parameters: remaining energy, connectivity cost, and progressive distance, as well as a Fuzzy Logic System (FLS) for node selection. These introduced mechanisms ensure the appropriate selection of a non-malicious node. Extensive simulation experiments have been conducted to evaluate the performance of the proposed FuGeF protocol as compared to DWSIGF variants. The simulation results show that the proposed FuGeF outperforms the two DWSIGF variants (DWSIGF-P and DWSIGF-R) in terms of packet delivery.
In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach.
In this paper, a defected ground-structured antenna with a stub-slot configuration is proposed for future 5G wireless applications. A simple stub-slot configuration is used in the patch antenna to get the dual band frequency response in the 5G mid-band and the upper unlicensed frequency region. Further, a 2-D double period Electronic band gap (EBG) structure has been implemented as a defect in the metallic ground plane to get a wider impedance bandwidth. The size of the slots and their positions are optimized to get a considerably high impedance bandwidth of 12.49% and 4.49% at a passband frequency of 3.532 GHz and 6.835 GHz, respectively. The simulated and measured realized gain and reflection coefficients are in good agreement for both operating bandwidths. The overall antenna structure size is 33.5 mm × 33.5 mm. The antenna is fabricated and compared with experimental results. The proposed antenna shows a stable radiation pattern and high realized gain with wide impedance bandwidth using the EBG structure, which are necessary for the requirements of IoT applications offered by 5G technology.
A simple, compact sickle-shaped printed antenna with a slotted ground plane is designed and developed for broadband circularly polarized (CP) radiation. The sickle-shaped radiator with a tapered feed line and circular slotted square ground plane are utilized to realize the wideband CP radiation feature. With optimized dimensions of 0.29λ × 0.29λ × 0.012λ at 2.22 GHz frequency for the realized antenna parameters, the measured results display that the antenna has a 10 dB impedance bandwidth of 7.70 GHz (126.85%; 2.22⁻9.92 GHz) and a 3 dB axial ratio (AR) bandwidth of 2.64 GHz (73.33%; 2.28⁻4.92 GHz). The measurement agrees well with simulation, which proves an excellent circularly polarized property. For verification, the mechanism of band improvement and circular polarization are presented, and the parametric study is carried out. Since, the proposed antenna is a simple design structure with broad impedance and AR bandwidth, which is a desirable feature as a candidate for various wireless communication systems. Because of the easy printed structure and scaling the dimension with broadband CP characteristics, the realized antenna does incorporate in a number of CP wireless communication applications.
We present ARTYCUL (ARTifact popularitY for CULtural heritage), a machine learning(ML)-based framework that graphically represents the footfall around an artifact on display at a museum or a heritage site. The driving factor of this framework was the fact that the presence of security cameras has become universal, including at sites of cultural heritage. ARTYCUL used the video streams of closed-circuit televisions (CCTV) cameras installed in such premises to detect human figures, and their coordinates with respect to the camera frames were used to visualize the density of visitors around the specific display items. Such a framework that can display the popularity of artifacts would aid the curators towards a more optimal organization. Moreover, it could also help to gauge if a certain display item were neglected due to incorrect placement. While items of similar interest can be placed in vicinity of each other, an online recommendation system may also use the reputation of an artifact to catch the eye of the visitors. Artificial intelligence-based solutions are well suited for analysis of internet of things (IoT) traffic due to the inherent veracity and volatile nature of the transmissions. The work done for the development of ARTYCUL provided a deeper insight into the avenues for applications of IoT technology to the cultural heritage domain, and suitability of ML to process real-time data at a fast pace. While we also observed common issues that hinder the utilization of IoT in the cultural domain, the proposed framework was designed keeping in mind the same obstacles and a preference for backward compatibility.
Magnetoactive (MA) foam, with its tunable mechanical properties and magnetostriction, has the potential to be used for the development of soft sensor technology. However, researchers have found that its mechanical properties and magnetostriction are morphologically dependent, thereby limiting its capabilities for dexterous manipulation. Thus, in this work, MA foam was developed with additional capabilities for controlling its magnetostriction, normal force, storage modulus, shear stress and torque by manipulating the concentration of carbonyl iron particles (CIPs) and the magnetic field with regard to morphological changes. MA foams were prepared with three weight percentages of CIPs, namely, 35 wt.%, 55 wt.% and 75 wt.%, and three different modes, namely, zero shear, constant shear and various shears. The results showed that the MA foam with 75 wt.% of CIPs enhanced the normal force sensitivity and positive magnetostriction sensitivity by up to 97% and 85%, respectively. Moreover, the sensitivities of the storage modulus, torque and shear stress were 8.97 Pa/mT, 0.021 µN/mT, and 0.0096 Pa/mT, respectively. Meanwhile, the magnetic dipolar interaction between the CIPs was capable of changing the property of MA foam from a positive to a negative magnetostriction under various shear strains with a low loss of energy. Therefore, it is believed that this kind of highly sensitive MA foam can potentially be implemented in future soft sensor systems.
Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.
Smart health-care is undergoing rapid transformation from the conventional specialist and hospital-focused style to a distributed patient-focused manner. Several technological developments have encouraged this rapid revolution of health-care vertical. Currently, 4G and other communication standards are used in health-care for smart health-care services and applications. These technologies are crucial for the evolution of future smart health-care services. With the growth in the health-care industry, several applications are expected to produce a massive amount of data in different format and size. Such immense and diverse data needs special treatment concerning the end-to-end delay, bandwidth, latency and other attributes. It is difficult for current communication technologies to fulfil the requirements of highly dynamic and time-sensitive health care applications of the future. Therefore, the 5G networks are being designed and developed to tackle the diverse communication needs of health-care applications in Internet of Things (IoT). 5G assisted smart health-care networks are an amalgamation of IoT devices that require improved network performance and enhanced cellular coverage. Current connectivity solutions for IoT face challenges, such as the support for a massive number of devices, standardisation, energy-efficiency, device density, and security. In this paper, we present a comprehensive review of 5G assisted smart health-care solutions in IoT. We present a structure for smart health-care in 5G by categorizing and classifying existing literature. We also present key requirements for successful deployment of smart health-care systems for certain scenarios in 5G. Finally, we discuss several open issues and research challenges in 5G smart health-care solutions in IoT.
Seasonal crops require reliable storage conditions to protect the yield once harvested. For long term storage, controlling the moisture content level in grains is challenging because existing moisture measuring techniques are time-consuming and laborious as measurements are carried out manually. The measurements are carried out using a sample and moisture may be unevenly distributed inside the silo/bin. Numerous studies have been conducted to measure the moisture content in grains utilising dielectric properties. To the best of authors' knowledge, the utilisation of low-cost wireless technology operating in the 2.4 GHz and 915 MHz ISM bands such as Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) have not been widely investigated. This study focuses on the characterisation of 2.4 GHz Radio Frequency (RF) transceivers using ZigBee Standard and 868 to 915 MHz UHF RFID transceiver for moisture content classification and prediction using Artificial Neural Network (ANN) models. The Received Signal Strength Indicator (RSSI) from the wireless transceivers is used for moisture content prediction in rice. Four samples (2 kg of rice each) were conditioned to 10%, 15%, 20%, and 25% moisture contents. The RSSI from both systems were obtained and processed. The processed data is used as input to different ANNs models such as Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest, and Multi-layer Perceptron (MLP). The results show that the Random Forest method with one input feature (RSSI_WSN) provides the highest accuracy of 87% compared to the other four models. All models show more than 98% accuracy when two input features (RSSI_WSN and RSSI_TAG2) are used. Hence, Random Forest is a reliable model that can be used to predict the moisture content level in rice as it gives a high accuracy even when only one input feature is used.
Contemporarily, almost all the global IT giants have aimed at the smart home industry and made an active strategic business layout. As the early-stage and entry-level product of the voice-enabled smart home industry, the smart speakers have been going through rapid development and rising fierce market competition globally in recent years. China, one of the most populous and largest markets in the world, has tremendous business potential in the smart home industry. The market sales of smart speakers in China have gone through rapid growth in the past three years. However, the market penetration rate of related smart home devices and equipment still stays extremely low and far from mass adoption. Moreover, the market sales of smart speakers have also entered a significant slowdown and adjustment period since 2020. Chinese consumers have moved from early impulsive consumption to a rational consumption phase about this early-stage smart home product. Trust in the marketing field is considered an indispensable component of all business transactions, which plays a crucial role in adopting new technologies. This study explores the influencing factors of Chinese users' perceived trust in the voice-enabled smart home systems, uses structural equation modeling (SEM) to analyze the interaction mechanism between different variables, and establishes a perceived trust model through 475 valid samples. The model includes six variables: system quality, familiarity, subjective norm, technology optimism, perceived enjoyment, and perceived trust. The result shows that system quality is the essential influence factor that impacts all other variables and could significantly affect the perceived trust. Perceived enjoyment is the most direct influence variable affected by system quality, subjective norm, and technology optimism, and it positively affects the perceived trust in the end. The subjective norm is one of the most distinguishing variables for Chinese users, since China has a collectivist consumption culture. People always expect their behavior to meet social expectations and standards to avoid criticism and acquire social integration. Therefore, policy guidance, authoritative opinions, and people with important reference roles will significantly affect consumers' perceived trust and purchase intention. Familiarity and technology optimism are important influential factors that will have an indirect impact on the perceived trust. The related results of this study can help designers, practitioners, and researchers of the smart home industry produce products and services with higher perceived trust to improve consumers' adoption and acceptance so that the market penetration rate of related products and enterprises could be increased, and the maturity and development of the voice-enabled smart home industry could be promoted.
In this paper, we propose a non-localization routing protocol for underwater wireless sensor networks (UWSNs), namely, the triangle metric based multi-layered routing protocol (TM2RP). The main idea of the proposed TM2RP is to utilize supernodes along with depth information and residual energy to balance the energy consumption between sensors. Moreover, TM2RP is the first multi-layered and multi-metric pressure routing protocol that considers link quality with residual energy to improve the selection of next forwarding nodes with more reliable and energy-efficient links. The aqua-sim package based on the ns-2 simulator was used to evaluate the performance of the proposed TM2RP. The obtained results were compared to other similar methods such as depth based routing (DBR) and multi-layered routing protocol (MRP). Simulation results showed that the proposed protocol (TM2RP) obtained better outcomes in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay.
This article presents the detailed theoretical, simulation, and experimental analysis of a half-mode substrate integrated waveguide (HMSIW)-based multimode wideband filter. A third-order, semicircular HMSIW filter is developed in this paper. A semicircular HMSIW cavity resonator is adopted to achieve wide band characteristics. A U-shaped slot (acts as a λ/4 stub) in the center of a semicircular HMSIW cavity resonator and L-shaped open-circuited stubs are used to improve the out-of-band response by generating multiple transmission zeros (TZs) in the stop-band region of the filter. The TZs on either side of the passband can be controlled by adjusting dimensions of a U-shaped slot and L-shaped open-circuited stubs. The proposed filter covers a wide fractional bandwidth, has a lower insertion loss value, and has multiple TZs (which improves the selectivity). The simulated response of filter agrees well with the measured data. The proposed HMSIW bandpass filter can be integrated with any planar wideband communication system circuit, thanks to its planar structure.
The rapid growth of the Internet of Things (IoT) and the massive propagation of wireless technologies has revealed recent opportunities for development in various domains of real life, such as smart cities and E-Health applications. A slight defense against different forms of attack is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed in transmission during data packet routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. In this research, we propose a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. This mainly detects, mitigates, and isolates attacks in RPL networks. The detection is based on a comparison of the rank strategy. The mitigation uses threshold and attack status tables, and the isolation adds them to a blacklist table and alerts nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies, such as Standard RPL with Attacks, Sink-Based Intrusion Detection Systems (SBIDS), and RPL+Shield. The analysis results showed that the SRPL-RP achieved significant improvements with a Packet Delivery Ratio (PDR) of 98.48%, a control message value of 991 packets/second, and an average energy consumption of 1231.75 joules. SRPL-RP provided a better accuracy rate of 98.30% under the attacks.
The vehicular Internet of Things (IoT) comprises enabling technologies for a large number of important applications including collaborative autonomous driving and advanced transportation systems. Due to the mobility of vehicles, strict application requirements, and limited communication resources, the conventional centralized control fails to provide sufficient quality of service for connected vehicles, so a decentralized approach is required in the vicinity to satisfy the requirements of delay-sensitive and mission-critical applications. A decentralized system is also more resistant to the single point of failure problem and malicious attacks. Blockchain technology has been attracting great interest due to its capability of achieving a decentralized, transparent, and tamper-resistant system. There are many studies focusing on the use of blockchain in managing data and transactions in vehicular environments. However, the application of blockchain in vehicular environments also faces some technical challenges. In this paper, we first explain the fundamentals of blockchain and vehicular IoT. Then, we conduct a literature review on the existing research efforts of the blockchain for vehicular IoT by discussing the research problems and technical issues. After that, we point out some future research issues considering the characteristics of both blockchain and vehicular IoT.