IET Wireless Sensor Systems最新文献

Low-cost off-the-shelf particulate matter (PM) sensors have the potentiality to be used for evaluating the air quality in outdoor settings. Monitoring of air quality in surface coal mines is an example of such applications. In coal mines, long-term exposure to inhalation of coal dust is harmful and can lead to coal workers' pneumoconiosis, which is a potentially disabling lung disease. Therefore, continual monitoring of air quality in coal mines is a must and vital and can potentially assist in preventing such diseases. Although, using and deploying of the existing low-cost and lightweight sensors can help to improve monitoring resolution in a much cost-effective manner, there are some concerns regarding the reliability of the collected data from these sensors. Therefore, low-cost PM sensors are required to initially be compared with the standard reference instruments and then be calibrated. In this study, three different types of low-cost, light-scattering-based widely available PM sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F and Laser SEN0177) are evaluated, compared, and calibrated with the reference instruments in a controlled environment as well as in a field experiment (surface coal mine).

This paper proposes a low power application dedicated protocol stack which consists of a contention-constrained p-CSMA (CCP) protocol over the LoRa modulation technique and a consecutive successful transmission controlled transport (CSTCT) protocol. The aim of these innovative protocols is to boost the network performance in terms of throughput and energy consumption while the transmission latency is still acceptable. As a reference, firstly, p-CSMA is evaluated with the consideration of under-noise-level communication. Then, the CCP protocol is proposed with the consideration of the speciality of the carrier sensing feature provided by the LoRa modem, which differs from the traditional energy level detection carrier sensing method. The CSTCT protocol resides at the CCP MAC layer which is light-weight and devised to further improve the overall throughput. The performance of the protocol stack is evaluated in simulations using various settings with predefined parameters that are drawn from experiments. The results show that our CCP MAC protocol and CSTCT transport protocol provide 10% higher throughput compared to the classic p-CSMA when the offered load is lower than 1.3 while the energy consumption is reduced by a factor of 2 and it remains latency limited.

As unmanned aerial vehicle (UAV) emerged as a flexible acquisition system that is widely used in military and civilian fields, efficient target tracking algorithm is in urgent need for UAV-based computer vision. Although research studies have been reported on typical interferences in the tracking process such as scale change, occlusion, distortion etc., some issues still exist for the target tracking algorithm based on UAV vision. This study exploited the features hidden in different colour spaces, and proposed a multi-feature multi-filter fusion tracking method that combines the HSV (hue, saturation and value) colour space with the histogram of oriented gradient (HOG) feature. The HSV colour space is proved to be able to discriminate objects under different conditions. The HOG of each HSV channel is utilised to train Kernelised correlation filters (KCF), respectively. The final tracking result is the candidate result with the biggest peak sidelobe ratio (PSR). Computer simulations proved that the fusion strategy proposed in this study can effectively improve the tracking performance of the tracker especially when the image sequences are interfered by deformation, occlusion, low resolution, etc. The performance of the tracker is also tested on UAV.

The way nodes are arranged in a wireless network can significantly influence performance, especially information flow. The construction of disjoint virtual backbone networks (DVBNs) is one of the ways this can be accomplished. In this study, the authors first present a proposal that constructs multiple DVBNs using nodes' locations, in two phases. In the second phase of the proposal, dominator selection is initiated by the sink and then continued by each selected dominator. This occurs in rounds, with each round producing a distinct virtual backbone. The simulations show that multiple DVBNs can be produced with a good approximation ratio. Further, two optimisations are presented, one for a scanty network and the other for data dissemination. These are accomplished by changing the way in which the dominators are selected in the second phase of the algorithm. These optimisations are evaluated and a marked improvement is observed in node connectedness to the backbone and in hop count while keeping approximation ratios almost constant.

Cognitive wireless sensor networks (CWSN) are severely energy constrained and radio frequency (RF) wireless energy harvesting (RFWEH) has been shown to improve the network lifetime. In many CWSN applications, node mobility imposes challenges owing to changing network topology. Therefore, the design of a new medium access control (MAC) protocol that can handle node mobility as well as energy harvesting is required. A cluster-based multihop MAC protocol (RMAC-M) is proposed that incorporates RF energy harvesting in a mobility-aware CWSN. Our protocol selects cluster heads using an algorithm based on an R-factor parameter consisting of residual node energy, residual node data and node speed, with appropriate weights. It then transmits data packages using a multitier super cluster head routing mechanism without the need for neighbour discovery. The multitier clustering and RFWEH mechanisms boost the energy performance of the network, increasing its lifetime. On the other hand, time slots allocated for RFWEH increase delay, thereby affecting system latency. Owing to its unique nature, the proposed algorithm has no comparable protocols in the literature. For the sake of completeness, RMAC-M is compared with well-known MAC protocols such as LEACH-M and KoNMAC that do not have energy harvesting or mobility features. Simulation results show that the proposed protocol increases the lifetime of the CWSN nodes substantially, promising a self-sustainable network in terms of energy. Furthermore, despite the allocation of time slots for energy harvesting, critical network parameters such as throughput, packet loss and average delay remain within target levels.

One of the ways in which localization algorithms in wireless sensor networks (WSNs) have been categorized is whether they are range-based or range-free. Range-based algorithms use expensive hardware to measure one or more physical quantities and, in turn, use them to localize nodes with greater precision. In contrast, range-free algorithms use coarse-grained quantities like connectivity to localize nodes with limited precision. A middle way between these two approaches can be called a partial range-based approach that can utilize the existing received signal strength indicator (RSSI) readings from sensor nodes to improve the already existing coarse-grained localization methods. Another important consideration in WSNs is that a distributed localization algorithm is more computationally feasible as compared to its centralized counterpart. Keeping these two considerations in mind, a distributed localization algorithm is proposed here which falls in the aforementioned partial range-based category. The proposed algorithm called RangeLookup-MDS first creates subregions using connectivity information only. This is followed by the collection of RSSI readings from individual sensor nodes that are used to perform range lookup for inter-node distance estimates in a lookup table. After that, relative localization in every subregion is performed using multidimensional scaling, and then the relative maps are stitched together to create a consistent (but relative) coordinate system. The algorithm also has the capability to compute absolute coordinates in two-dimensional if the stitching step is executed with at least three non-collinear anchor nodes with known locations. Simulation results on uniform as well as irregular networks of various sizes show that the proposed algorithm provides improved localization accuracy and reduces localization error up to 25% in comparison to a previous partial range-based localization algorithm.

Communication protocols for the Internet of Things (IoT) have been optimised to meet the specific requirements of this fast-growing domain. They have been adapted mainly to optimise power consumption, maximise coverage area and facilitate their implementation. One of these protocols is LoRaWAN, which uses the ADR algorithm (Adaptive Data Rate) and aims to reduce power consumption by reducing data rate and transmission power. The ADR algorithm has been specifically optimised for static systems, that is, systems where devices do not move or have limited mobility. In this article, we introduce COMMA (Communication Optimisation Mechanism for Mobility Adaptation), an adaptive data rate mechanism optimised for everyday mobility of devices and people. We use COMMA in telemedicine, our area of expertise, to develop a medical remote-monitoring platform for mobile patients suffering from chronic diseases.

The authors proposed a fusion protocol using multilevel clustering (FPMC), which is completely dependent on the increased coverage and wireless sensor network (WSN) reliability-clustering framework to eliminate duplication. Therefore, a static sensor for a point of interest is allocated where possible so that the particular area can be protected. Furthermore, FPMC ensures that only one sensor node is allocated to cover a specific point of interest. The network coverage, energy usage, mean movement of WSNs nodes and sensor nodes are active in each loop due to which efficiency of the proposed protocol was assessed under various densities, and its performance was also analysed. Evaluations have shown that with restricted active nodes and sensor nodes, the FPMC can increase the networking coverage. The FPMC should be stressed as reducing the overlap level. The proposed protocol is based on the fusion protocol using multi-level clustering for improving coverage and connectivity WSNs.