Low-power Wireless Sensor Networks Research Articles

An immune chaotic adaptive evolutionary algorithm for energy-efficient clustering management in LPWSN

Recently, low power wireless sensor networks (LPWSNs) have been widely used in the military and education. However, the lifetime of LPWSN is affected by the energy of the sensor, so the clustering design has received a lot of attention. In this study, the problem of designing optimal clustering for LPWSN is formulated as a cluster head selection problem, considering energy, which is an NP-hard problem. Therefore, a new structural model of the clustering design problem is constructed. This model can represent the process of sensor node clustering and information transfer. In this paper, a new immune chaotic adaptive evolutionary algorithm (ICAEA) is proposed and used in the clustering design of LPWSNs to obtain a better cluster head selection scheme. Then we design new advanced operators, such as immune operator and chaotic operator, which improve the convergence speed of the algorithm on the basis of evolutionary algorithm (EA). Moreover, ICAEA avoids local optima by introducing an adaptive operator, improves the convergence accuracy of the algorithm, and improves the performance of the optimization. Simulations are conducted to determine the performance improvements of ICAEA in terms of network lifetime and energy consumption compared to the latest clustering methods of R-LEACH, Q-LEACH, and ICCHR. The experimental results show that the proposed ICAEA algorithm outperforms RLEACH, Q-LEACH and ICCHR in terms of network lifetime under multiple identical experimental conditions. Moreover, ICAEA consumes less energy than R-LEACH, Q-LEACH and ICCHR in terms of system energy consumption.

Long-Range Low-Power Multi-Hop Wireless Sensor Network for Monitoring the Vibration Response of Long-Span Bridges.

Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations.

Reliable and Low-Power Communications System Based on IR-UWB for Offshore Wind Turbines

In this paper, we propose the design of a low-power wireless sensor network architecture that enables robust communications inside offshore wind turbines. This research work is in the scope of the WATEREYE EU Project, where we have designed a corrosion monitoring solution to work unattended. The architecture is composed of several fixed sensor nodes, one mobile sensor node, several anchors and the WATEREYE Computer (WEC). Our approach is based on Impulse Radio Ultra wideband (IR-UWB) technology offering reliable and low-power communications in these harsh environments. On top of that, we propose a double star network using two UWB channels for the following purposes: one network for communications to send the sensor data and another one for ranging estimations to calculate the indoor positioning of the mobile sensor node. The power strategies applied to our system, at Hardware (HW) and Firmware (FW) levels, are described in detail. Furthermore, we present power consumption measurements obtaining the power profiles and the autonomy of the most important components of the proposed architecture supplied by battery. On the other hand, we describe the methodology to analyze the range, reliability and continuity of the two UWB links providing the packet loss and gaps as a function of distance. The proposed communications system has been validated in three different scenarios considering two of them very hostile environments. Furthermore, one of the scenarios is a real offshore wind turbine.

Optimization and Simulation of a Dynamic Management System for Building Construction Based on Low-Power Wireless Sensor Networks

In this paper, we use a low-power wireless sensor network to conduct in-depth research and analysis on the optimization simulation of the dynamic management system of building construction and study the specific application of BIM technology in the information management of building construction sites. By analysing the classical delustering routing and combining the advantages in the delustering routing protocols, we propose a two-level Mesh wireless sensor network delustering routing protocol in terms of cluster head uniformity, energy consumption and balance, working mode, and handling of isolated nodes. The most important feature of this protocol compared to other delustering protocols is that it retains the design of flat network topology and designs three routing methods with the corresponding functions of wireless sensor networks to achieve better network performance. The supported personnel location technology and construction measures and environmental monitoring technology are introduced, the applicability of the technology in the building construction process is compared and analysed, the topology of construction measures and environmental monitoring technology is designed, and finally, the targeted development of the collection scheme for personnel, scaffolding, formwork, pits, cranes, construction hoists, and physical environment is completed. Firstly, it analyses the development status of BIM-based building construction site information management technology and application and discusses the basis of BIM technology implementation and the advantages of BIM technology application in information management. Then, this paper constructs the framework of a BIM-based building construction site information management system from three dimensions: functional, logical, and physical. To ensure the realizability and operability of the system, this paper discusses the operation mechanism of the BIM-based building construction site information management system, studies the key technology of system operation, designs the basic operation process of each application system of the system, and elaborates the organizational structure of the building construction site and the functional division of the relevant personnel.

Low-Power Low-Error Wireless Sensor Network for Health and Usage Monitoring Systems

Low-Power Low-Error Wireless Sensor Network for Health and Usage Monitoring Systems

Energy-efficient and balanced routing in low-power wireless sensor networks for data collection

Cost-based routing protocols are the main approach used in practical wireless sensor network (WSN) and Internet of Things (IoT) deployments for data collection applications with energy constraints; however, those routing protocols lead to the concentration of most of the data traffic on some specific nodes which provide the best available routes, thus significantly increasing their energy consumption. Consequently, nodes providing the best routes are potentially the first ones to deplete their batteries and stop working. In this paper, we introduce a novel routing strategy for energy efficient and balanced data collection in WSNs/IoT, which can be applied to any cost-based routing solution to exploit suboptimal network routing alternatives based on the parent set concept. While still taking advantage of the stable routing topologies built in cost-based routing protocols, our approach adds a random component into the process of packet forwarding to achieve a better network lifetime in WSNs. We evaluate the implementation of our approach against other state-of-the-art WSN routing protocols through thorough real-world testbed experiments and simulations, and demonstrate that our approach achieves a significant reduction in the energy consumption of the routing layer in the busiest nodes ranging from 11% to 59%, while maintaining over 99% reliability. Furthermore, we conduct the field deployment of our approach in a heterogeneous WSN for environmental monitoring in a forest area, report the experimental results and illustrate the effectiveness of our approach in detail. Our EER based routing protocol CTP+EER is made available as open source to the community for evaluation and adoption.

Efficient Link Scheduling Based on Estimated Number of Packets in Queue on Industrial Wireless Sensor Networks

The links of low power wireless sensor networks are error prone and the transmission on a wireless link is determined probabilistically by the packet reception rate (PRR) of the link. On the other hand, there is a very strict requirement in the end-to-end reliability and delay of sensor data in industrial wireless sensor networks (IWSNs). The existing approaches to provide the end-to-end reliability in IWSNs is retransmitting the packet when failure occurs. These approaches transmit a packet multiple times in successive time slots to provide the required reliability. These approaches, however, can increase the average delay of packets and the number of packets buffered in a queue. This paper proposes a new scheme to estimate the probabilistic amount of packets, called queue level (QL), in the buffer of each node based on the PRRs of the wireless links. This paper also proposes a QL-based centralized scheduling algorithm to assign time slots efficiently in TDMA-based IWSNs. The proposed scheduling algorithm gives higher priority to the nodes with higher QL. By assigning time slots first to the node with the highest QL, we can reduce the average end-to-end delay of packets and reduce the amount of buffered packets in the queue while satisfying the required end-to-end reliability. The performance of the proposed scheduling algorithm have been evaluated through a simulation using the Cooja simulator and compared with the existing approach. In the simulation on an sample network with the target end-to-end reliability of 99%, all of the flows were shown to guarantee the target reliability in both algorithms: on average, 99.76% in the proposed algorithm and 99.85% in the existing approach. On the other hand, the proposed algorithm showed much better performance than the existing approach in terms of the average end-to-end delay of packets (about 47% less) and the number of maximally buffered packets in the queue of each node (maximally, more than 90% less).

Alert System for Fall Detection

Abstract: Healthcare is one of the most important industries, yet new ideas must travel a long way before being fully adopted due to its complexity, scope of duty, and stringent laws. The Internet of Things (IoT) may be the key to resolving healthcare challenges. The Internet of Things (IoT) has a lot of potential in healthcare, but it's still in its early stages. With the advancement of medical IoT, new possibilities for telemedicine, remote monitoring of a patient's status, and much more will emerge. Falling is a significant health danger for the elderly. If the problem is not detected in a timely manner, it can result in the death or impairment of the elderly, lowering their quality of life. Falls are a major public health concern for the elderly around the world. When it comes to old age, we must keep an eye on our loved ones to ensure their health and safety. It is therefore critical to determine if an elderly person has fallen so that help can be provided promptly. Proposing a person fall detection system based on a wearable device for detecting the falls of people in every situation, which takes advantage of lowpower wireless sensor networks, smart devices, and analyses human body motions. The system detects movement using an accelerometer and a gyro sensor. The sensor is wired to a microprocessor, which transmits the acceleration data continuously. Fall detection and sudden movement changes in the person would be monitored by the system. The sensors are getting values from a quick movement shift with shock in the system. When a person falls and becomes unconscious, the system determines whether the person has indeed fallen. If the person has truly fallen, the system will send an alert to the caregivers and sound an alarm to alert anyone nearby. When the system detects that a person has fallen, it immediately sends an alert to the individual's care takers. It is an IoT-based fall detection system that assists people by telling their caregivers about their fall so that quick attention may be drawn to the situation and essential actions can be taken to save the person who has fallen. Keywords: Threshold Based Fall Detection, Arduino, Bi-Axial, Accelerometer, Gyroscope,

High-Efficiency Triple-Band RF-to-DC Rectifier Primary Design for RF Energy-Harvesting Systems

Radio Frequency (RF) energy harvesting has been emerged as a potentially reliable method to replace the costly and difficult to maintain source of low-power wireless sensor networks. A plethora of dual-band rectifier designs has been proposed in the literature operating in various frequency bands. In this paper, a triple-band RF-to-DC rectifier that operates in the frequency bands of LoRaWAN, GSM-900, and WiFi 2.4 GHz is presented. The system is composed of an impedance-matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low-power devices, and an output load. The proposed system resonates at three different frequencies of 866 MHz, 948 MHz and 2423 MHz, which fall within the aforementioned frequency bands of interest. The feasible solution of the proposed system was based on a dual-band rectifier operating in the frequency bands of LoRaWAN and GSM-900. A series of shunt stubs was utilized in the initial design to form the feasible solution of the proposed system. The proposed triple-band rectifier was optimized using a powerful optimization algorithm, i.e., the genetic algorithm. The overall system exhibited improved characteristics compared to the initial design in terms of its resonance. Numerical results demonstrated that the overall system exhibited an efficiency of 81% with 3.23 V of the output voltage, for an input power of 0 dBm and a load of 13 kOhm.

Monitoring Soil and Ambient Parameters in the IoT Precision Agriculture Scenario: An Original Modeling Approach Dedicated to Low-Cost Soil Water Content Sensors.

A low power wireless sensor network based on LoRaWAN protocol was designed with a focus on the IoT low-cost Precision Agriculture applications, such as greenhouse sensing and actuation. All subsystems used in this research are designed by using commercial components and free or open-source software libraries. The whole system was implemented to demonstrate the feasibility of a modular system built with cheap off-the-shelf components, including sensors. The experimental outputs were collected and stored in a database managed by a virtual machine running in a cloud service. The collected data can be visualized in real time by the user with a graphical interface. The reliability of the whole system was proven during a continued experiment with two natural soils, Loamy Sand and Silty Loam. Regarding soil parameters, the system performance has been compared with that of a reference sensor from Sentek. Measurements highlighted a good agreement for the temperature within the supposed accuracy of the adopted sensors and a non-constant sensitivity for the low-cost volumetric water contents (VWC) sensor. Finally, for the low-cost VWC sensor we implemented a novel procedure to optimize the parameters of the non-linear fitting equation correlating its analog voltage output with the reference VWC.

Energy Efficiency Analysis of LoRa and ZigBee Protocols in Wireless Sensor Networks

Now a days IoT technologies are emerging technology with wide range of applications. Wireless sensor networks (WSNs) are plays vital role in IoT technologies. Construction of wireless sensor node with low-power radio link and high-speed processors is an interesting contribution for wireless sensor networks and IoT applications. Most of WSNs are furnished with battery source that has limited lifetime. The maximum operations of these networks require more power utility. Nevertheless, improving network efficiency and lifetime is a curtail issue in WSNs. Designing a low powered wireless sensor networks is a major challenges in recent years, it is essential to model its efficiency and power consumption for different applications. This paper describes power consumption model based on LoRa and Zigbee protocols, allows wireless sensor nodes to monitor and measure power consumption in a cyclic sleeping scenario. Experiential results reveals that the designed LoRa wireless sensor nodes have the potential for real-world IoT application with due consideration of communicating distance, data packets, transmitting speed, and consumes low power as compared with Zigbee sensor nodes. The measured sleep intervals achieved lower power consumption in LoRa as compared with Zigbee. The uniqueness of this research work lies in the review of wireless sensor node optimization and power consumption of these two wireless sensor networks for IoT applications.

Evaluation of the Quality of Aerial Links in Low-Power Wireless Sensor Networks

A wireless sensor network (WSN) assisted by Unmanned Aerial Vehicles (UAVs) can be used to monitor various phenomena in remote, extensive, inaccessible, or dangerous places. The WSN on the ground can provide close-to-the-scene sensing, in-network data processing, and multi-hop communication. The UAVs can interface the ground network with a remote control station or facilitate fast and flexible data collection. To this end, the aerial links established between the UAVs and the WSN are critical. The reliability of the links depends on many factors, including Cross Technology Interference (CTI), the relative distance of the UAVs from the ground nodes, the drive quality of the UAVs, and noise. In this paper, we present experimental results addressing some of these issues. Our experiments consisted of eleven IEEE 802.15.4 compliant transceivers, nine of which were deployed on the ground in a grid topology with a further two being attached to a UAV. From careful examination of traces extracted from received packets we concluded that CTI is the most significant factor affecting the quality of aerial links. Our observations have application for deployment related decision-making and for the design of UAV-assisted data collection protocols.

Using Sensor Network in Motion Detection Based on Deep Full Convolutional Network Model

Aiming at the shortcomings of traditional moving target detection methods in complex scenes such as low detection accuracy and high complexity, and not considering the overall structure information of the video frame image, this paper proposes a moving-target detection based on sensor network. First, a low-power motion detection wireless sensor network node is designed to obtain motion detection information in real time. Secondly, the background of the video scene is quickly extracted by the time domain averaging method, and the video sequence and the background image are channel-merged to construct a deep full convolutional network model. Finally, the network model is used to learn the deep features of the video scene and output the pixel-level classification results to achieve moving target detection. This method not only can adapt to complex video scenes of different sizes but also has a simple background extraction method, which effectively improves the detection speed.

Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey

Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart buildings and patient healthcare monitoring. The small size IoT nodes based on low power Bluetooth (IEEE 802.15.1) standard and wireless sensor networks (WSN) (IEEE 802.15.4) standard are generally used for transmission of data to a remote location using gateways. The WSN based IoT (WSN-IoT) design problems include network coverage and connectivity issues, energy consumption, bandwidth requirement, network lifetime maximization, communication protocols and state of the art infrastructure. In this paper, the authors propose machine learning methods as an optimization tool for regular WSN-IoT nodes deployed in smart city applications. As per the author’s knowledge, this is the first in-depth literature survey of all ML techniques in the field of low power consumption WSN-IoT for smart cities. The results of this unique survey article show that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications.

Research on Optimization of Distributed Node Location Algorithm in Wireless Sensor Networks

This paper studies the related theories of wireless sensor networks, and an improved DV-Hop algorithm is proposed, which used to estimate the distance error mainly based on the error of average per hop distance, unknown nodes and anchor nodes in traditional algorithm. Through the simulation analysis, it can be found that compared with the traditional Location algorithm of DV-Hop and other improved algorithm, the improved algorithm proposed in this paper can reduce the location error and improve the location accuracy when the proportion of the anchor nodes is moderate and the communication radius is small, and this algorithm is suitable for the low power and wide range wireless sensor network environment.

Wireless Sensor Network–Based Structural Health Monitoring of Bridges Using Advanced Signal Processing Techniques

Abstract Continuous growth in the networks of roads and bridges pose a continuously rising challenge to maintenance agencies for ensuring accident-free operations of transportation network. This challenge exacerbates in developing economies. Specifically, in port/harbor areas, the challenge increases many folds because of the corrosive environment. Assessment of aging civil infrastructure integrity is imperative to guarantee safe operations. Wireless sensor networks (WSNs) offer reliable and cost-effective automated applications for structural health monitoring (SHM) of civil infrastructure. This article presents a vibration analysis–based method for SHM of civil infrastructures using WSNs. In the proposed research work, advanced signal processing techniques are applied on actual vibration data acquired using low-power WSNs to classify healthy and degraded civil structures. The proposed scheme has successfully been implemented on a 20-year-old concrete bridge situated in the harbor area of Karachi, Pakistan. Micro electro mechanical system–based accelerometers connected to low-power–consuming wireless nodes are installed on the bridge under study. The acquired vibration data are uploaded on the cloud. Subsequent application of time-frequency energy analysis of the recorded vibration data enabled the discrimination between healthy and degraded structures. The proposed scheme can be used for civil infrastructure monitoring at remote sites using low-power WSNs with the least intervention.

Remote Tracking Gas Molecular via the Standalone-Like Nanosensor-Based Tele-Monitoring System

HighlightsA standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way is created;Metal–organic framework-derived hollow polyhedral ZnO was successfully synthesized, allowing the created smart device to be highly selective and to sensitively track the variation of NO2 concentration;A novel photoluminescence-enhanced Li-Fi telecommunication technique is proposed, offering the created smart device with the capability of long distance wireless communication.Remote tracking the variation of air quality in an effective way will be highly helpful to decrease the health risk of human short- and long-term exposures to air pollution. However, high power consumption and poor sensing performance remain the concerned issues, thereby limiting the scale-up in deploying air quality tracking networks. Herein, we report a standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way. Brevity, the created smart device demonstrated satisfactory selectivity (against six kinds of representative exhaust gases or air pollutants), desirable response magnitude (164–100 ppm), and acceptable response/recovery rate (52.0/50.5 s), as well as linear response relationship to NO2. After aging for 2 weeks, the created device exhibited relatively stable sensing performance more than 3 months. Moreover, a photoluminescence-enhanced light fidelity (Li-Fi) telecommunication technique is proposed and the Li-Fi communication distance is significantly extended. Conclusively, our reported standalone-like smart device would sever as a powerful sensing platform to construct high-performance and low-power consumption air quality wireless sensor networks and to prevent air pollutant-induced diseases via a more effective and low-cost approach.

An Elite Adaptive Niche Evolutionary Algorithm for Duty Clustering Problem in SoWSN

The recent success of emerging low power wireless sensor networks technology has encouraged researchers to create novel duty cycle design algorithm in this area. Since “sensors are constrained in sensing capabilities”, duty cycle design plays a crucial role in maximizing the point coverage rate, while most researches for duty cycle design are related to a duty cycle design algorithm. But unfortunately, the ideal duty cycle design requires an exhaustive search over all combinations of the allowed combinations. In this letter, we present a new elite adaptive niche evolutionary algorithm (EANEA) for duty cycle design problem in Service-oriented wireless sensor networks (SoWSN). In order to extend the network life cycle, we designed an objective function for SoWSN. We also give an EANEA which, depending on a powerful niche operator, blends the merits of both elite selection and adaptive adjusting for the channel assignment problem. Simulation results show that the shown algorithm can achieve a higher point coverage rate over genetic quantum algorithm (QGA) and Shuffled Frog-Leaping Algorithm (SFLA). Moreover, the optimization employs an elite selection to initialize the parameters and avoid local optima proficiently.

Healthcare monitoring of mountaineers by low power Wireless Sensor Networks

Mountains have attracted many enthusiasts and trekkers for a long time to conquer high peaks or explore picturesque terrain. A team of mountaineers carries the necessary equipment for climbing steep slopes and steering through rugged terrain. The movements are monitored through the main control centres. The reporting mechanism is periodic on a need basis or at the end of the day’s summary reporting. The team members are travelling under the threat of avalanches and victims get buried inside the snow-mass in the event of accidents. In such accidents, 65% of fatalities happen due to asphyxia, 29% due to trauma, and balance due to hypothermia, drowning and primary cardiac arrest. Commercially available gadgets and previously developed electronic systems are designed for normal habitation. They use WiFi services to transmit health parameters on IoT platforms. Users should be conscious and self-aware to monitor and communicate health parameters, whereas the buried victims suffer from trauma and remain immobile/ unconscious. The present paper aims at addressing the healthcare issues of mountaineers while trekking in normal conditions as well as in a buried scenario without the need for WiFi connectivity. The proposed electronic system uses low power consuming chips that sustain low temperatures up to -40 °C. The system monitors oxygen level, heart rate, body temperature, etc., and disseminates the compiled data to a central control station by employing technological advancements in Wireless Sensor Networks, LoRa, and satellite modems. In the event of accidental burial of victims, the electronic system is equipped with a special feature to automatically activate Op-Mode-5 and transmit data at optimum power to the master node. The system helps in the regular assessment of the health conditions of mountaineers so that search and rescue operations can be carried out in time for saving precious lives.

Design, analysis and experimental investigation of a rotational piezoelectric energy harvester with storage system

Energy harvesting from rotational motion has drawn attention over the years to energise low-power wireless sensor networks in a rotating environment. The harvester works efficiently in a small frequency range which has to be similar to the driving frequency. Because of the constraints of size, precision, and the energy harvester’s weight, it is challenging to design it to suit micro applications. To deal with this problem, this paper proposes a rotational piezoelectric energy harvester (RPEH), which generates a voltage output from rotational motion. This design increases the gravitational force acting on the system by increasing the length of the beam, which in turn increases its vibration in a transverse direction. Euler-Bernoulli’s theory is utilized to derive the mathematical model of the RPEH under rotational motion, and harvester dynamic equations are derived using the electromechanical Lagrange equations. A prototype of RPEH is developed and the exactness of the proposed mathematical model is verified using experimental results and numerical simulation. Maximum power of 43.77 uW is produced at a rotating frequency of 21 Hz (1260 rpm) with an optimum load resistance of 1141.3 kΩ.