Distributed Wireless Sensor Nodes Research Articles

Self-powered wireless sensing technologies based on triboelectric nanogenerator.

With the rapid development of the Internet of Things (IoT), sustainable energy supply and wireless transmission of distributed wireless sensor nodes have become a challenge. In recent years, self-powered wireless sensing technologies (SWSTs) combining triboelectric nanogenerators (TENG) and wireless solutions have been proposed to address the issues of energy harvesting and wireless transmission. This review systematically summarizes the research advances in SWSTs based on TENG, and compares the advantages and disadvantages of different technologies. In addition, challenges and expectations for future TENG-based SWSTs are discussed as well.&#xD.

High-Performance Coaxial Counter-Rotating Triboelectric Nanogenerator with Lift-Drag Hybrid Blades for Wind Energy Harvesting.

Wind energy holds potential for in-situ powering large-scale distributed wireless sensor nodes (WSNs) in the Internet of Things (IoT) era. To achieve high performance in wind energy harvesting, a coaxial counter-rotating triboelectric nanogenerator with lift-drag hybrid blades, termed CCR-TENG, has been proposed. The CCR-TENG, which can work in non-contact and soft-contact modes, realizes low-speed wind energy harvesting through a combination of counter-clockwise rotating lift-type blades and clockwise rotating drag-type blades. Non-contact CCR-TENG realizes low-speed wind energy harvesting at wind speeds as low as 1 m/s. The output of a CCR-TENG, working in soft-contact mode, achieves 41% promotion with a maximum short-circuit current of 0.11 mA and a peak surface power density of 6.2 W/m2 with two TENGs connected in parallel. Furthermore, the power density per unit of wind speed achieves 746 mW/m3·s/m. Consequently, two fluorescent lamps were successfully illuminated and six temperature sensors were continuously lit by the CCR-TENG. The reported CCR-TENG significantly improves low-speed environmental wind energy utilization and demonstrates broad application prospects for in-situ power supply of distributed wireless transmission devices and sensors in the era of the IoT.

Boosting power output of flutter-driven triboelectric nanogenerator by flexible flagpole

One important component of Industry 4.0 is the Internet of Things (IoT) which links every “things” by distributed wireless sensor nodes (WSNs). Most sensor nodes are small in size, consume little energy and are adaptive to the environment. Small and local power generation is desirable for such WSNs, and harvesting energy from ambient wind is one of the potential methods. To harvest small-scale wind energy effectively, a promising device called flutter-driven triboelectric nanogenerator (FTENG) was lately developed, which converts kinetic energy in the self-fluttering motion of a flag to electricity. Many studies focused on material development to increase the surface charge density of the surfaces to enhance the energy output of FTENG, but few tried to enlarge the fluttering motion by considering the structural design. This study shows that by simply replacing the rigid flagpole in the FTENG with a flexible flagpole, the energy output is enhanced. The fluttering dynamics of the flags with rigid and flexible flagpoles was recorded by high-speed camera. It was found that when the flag was held by a flexible flagpole, the fluttering amplitude and the contact area between the flag and electrode plates were increased. The channel width, flag thickness, and flag length in relation to the voltage, current and power outputs were also investigated in this study. The greatest enhancement can reach 113 times when the wind velocity is 10 m/s. In a demonstration experiment, the device can light 254 LEDs and a temperature and humidity wireless sensor. In addition, the device has a stable output in a one-hour durability test. Comparing with other FTENGs from the literatures, our device has a lower critical velocity and a higher energy output. Besides, our design was integrated into other FTENG structures and got an enhancement of more than two folds in power density. This work demonstrates the use of a flexible flagpole to enhance the output performance of an FTENG by increasing the fluttering mechanical energy and increasing the contact area. Based on the performance obtained in this study, the improved FTENG has the potential to be applied in smart cities as a power source for IoT WSNs. • A high energy output flutter-driven TENG is proposed by using a flexible flagpole. • The flexible flagpole helps to amplify the fluttering motion of the flag. • The channel gap, flag thickness and length were optimized based on energy output. • The power enhancement is up to 113 times compared to normal flutter-driven TENG. • The device can light 254 LEDs or a wireless sensor via a power management module.

Застосування технологій IoT та хмарних сервісів для радіаційного моніторингу

Introduction. Cloud services are the most promising technologies for monitoring radiation pollution. They are a set of geographically distributed wireless sensor nodes designed to collect, sometimes pre-process, information about environmental parameters, as well as to transmit this information to remote users. Purpose. Development of basic methods for applying cloud services for IoT radiation and Environmental Research Technology. A comprehensive assessment of the state of the ecosystem, including its impact on humans, was carried out. At the same time, a promising direction is proposed, namely the integration of on-premises measuring devices with cloud services using M2M/IoT technology for remote measurement, the use of promising semiconductor sensors based on CdTe and CdZnTe radiation detectors, and modern microcontrollers. Methods. Use of methods Wi-Fi access point, control of the sensor network via a smartphone to transfer data parameters to the ThingSpeak cloud service. Results. When writing approaches to building cloud services, the composition of each sensor node and the task that it performs are considered, such as: the type of data collected, location, power sources, and the possibility of using certain protocols for data exchange relationships. Conclusion. The analysis of unified cloud services that include methods of designing information and measurement systems, methods of building machine-machine and human-machine interfaces, methods of designing sensor networks, methods of computer modeling of electronic circuits and systems, hardware emulation method (based on QEMU), methods of analysis, system analysis, synthesis, logical generalization of results. It includes selecting and connecting layout hardware, data module software that is developed in the ThingSpeak environment using the HTML markup language to describe the configuration web page.

A Nail-Size Piezoelectric Energy Harvesting System Integrating a MEMS Transducer and a CMOS SSHI Circuit

Piezoelectric vibration energy harvesting has drawn much interest to power distributed wireless sensor nodes for Internet of Things (IoT) applications where ambient kinetic energy is available. For certain applications, the harvesting system should be small and able to generate sufficient output power. Standard rectification topologies such as the full-bridge rectifier are typically inefficient when adapted to power conditioning from miniaturized harvesters. Therefore, active rectification circuits have been researched to improve overall power conversion efficiency, and meet both the output power and miniaturization requirements while employing a MEMS harvester. In this paper, a MEMS piezoelectric energy harvester is designed and co-integrated with an active synchronized switch harvesting on inductor (SSHI) rectification circuit designed in a CMOS process to achieve high output power for system miniaturization. The system is fully integrated on a nail-size board, which is ready to provide a stable DC power for low-power mini sensors. A MEMS energy harvester of 0.005 cm3 size, co-integrated with the CMOS conditioning circuit, outputs a peak rectified DC power of 40.6 $\mu \text{W}$ and achieves a record DC power density of 8.12 mW/cm3 when compared to state-of-the-art harvesters.

Smart Load Node for Nonsmart Load Under Smart Grid Paradigm: A New Home Energy Management System

This article presents a novel approach for efficient operation of non-smart household appliances under smart grid environment using the proposed smart load node (SLN). In real world scenario, there are so many non-smart loads currently in use and embedding appliance specific intelligence into them to make them as smart loads will be more expensive compared to the proposed SLN, which is a common solution for all types of non-smart loads. This makes the proposed low-cost SLN, which neither requires any infrastructural change in the electrical wiring of a house nor any constructional change in home appliances at the manufacturing stage and at the consumer end, as a feasible solution for intelligent operation of non-smart home appliances under smart grid environment. The SLNs, which are placed in a home like distributed wireless sensor nodes, form a home area network (HAN). The HAN includes a load management unit (LMU) which acts as master for all distributed SLNs. Wi-Fi is chosen as a medium of communication in the HAN. The LMU incorporates load management algorithm which is written in Python script.

A Review on Fluid-Induced Flag Vibrations

Fluid-induced flag vibrations provide unattended, efficient, low-cost, and scalable solutions for energy harvesting to power distributed wireless sensor nodes, heat transfer enhancement in channel flow, and mixing enhancement in process industries. This review surveys three generic configurations, the inverted flag, the standard flag, and the forced flag, i.e., an inverted or standard flag located downstream of a bluff body. Their instability boundaries, vibration dynamics, and vortex dynamics are compared in a unified framework to elucidate their common and distinct features and provide insights into the design of vibrating flags for various applications. Some common features are also identified and analyzed for describing the interaction between multiple flags, three-dimensional (3D) effects, and Reynolds number effects. The suggestions are intended to guide future research directions.

Simulation and evaluation of pulse-coupled oscillators in wireless sensor networks

ABSTRACTThe clock in embedded systems usually is driven by a crystal oscillator and implemented via a counter register, such a crystal clock is non-identical and drifting due to the manufacturing tolerance and variation of working conditions. Thus, a common time among distributed wireless sensor nodes, also referred to as Time Synchronization, is required for many time-sensitive wireless applications, such as collaborative condition monitoring, coordinated control and localization. Inspired by fireflies’ behaviour, the Pulse-Coupled Oscillators (PCO) has been proposed for synchronization in complex networks. Since the concurrent transmission of PCO’s Pulses is impossible in Wireless Sensor Networks (WSNs), the desynchronization mechanism is adopted to ensure the implementation of PCO in WSNs. Moreover, due to the uncertainties in radio channels and the complexities of communication protocols and packet-exchange behaviours in wireless networks, it is challenging to have a closed-form solution to the performance of PCO synchronization in WSNs. The realistic software simulation, in particular, the discrete event simulator has been a powerful tool to exam the performance of communication protocols in various scenarios, since an order sequence of well-defined event in time is to represent the behaviour of a complex system. This paper presents the development of a pulse-coupled oscillators time synchronization simulator on the OMNeT++ platform for simulating and studying its behaviour and performance in sensor networks. A clock module with configurable phase and frequency noises, and adjustable and higher resolution is developed to mimic various crystal oscillators in embedded systems, for example, the real-time clock. The developed simulator also supports the full functions devices defined by ZigBee protocol, which allows realistic simulation of multi-hop IEEE 802.15.4 wireless networks. Finally, the intensive simulations of classical PCO with the refractory period in IEEE 802.15.4-based WSNs have been carried out to demonstrate the features and benefits of the developed simulator. It is shown that for the non-identical and time-varying PCO clocks in the WSNs, the achieved synchronization will lose gradually, and the time that maintained synchronization depends on the length of refractory period.

An Efficient Inductorless Dynamically Configured Interface Circuit for Piezoelectric Vibration Energy Harvesting

Vibration energy harvesting based on piezoelectric materials is of interest in several applications such as in powering remote distributed wireless sensor nodes for structural health monitoring. Synchronized switch harvesting on inductor and synchronous electric charge extraction circuits show good power efficiency among reported power management circuits; however, limitations exist due to inductors employed, adaption of response to varying excitation levels, and the synchronized switch damping (SSD) effect. In this paper, an inductorless dynamically configured interface circuit is proposed, which is able to configure the connection of two piezoelectric materials in parallel or in series by periodically evaluating the ambient excitation level. The proposed circuit is designed and fabricated in a 0.35 μHV CMOS process.The fabricated circuit is cointegrated with a piezoelectric bimorph energy harvester and the performance is experimentally validated. With a low power consumption (0.5 μW), the measured results show that the proposed rectifier can provide a 4.5 × boost in harvested energy compared to the conventional full-bridge rectifier without employing an inductor. It also shows a high power efficiency over a wide range of excitation levels and is less susceptible to SSD.

Combination of clustering algorithms to maximize the lifespan of distributed wireless sensors

Abstract. Increasing the lifespan of a group of distributed wireless sensors is one of the major challenges in research. This is especially important for distributed wireless sensor nodes used in harsh environments since it is not feasible to replace or recharge their batteries. Thus, the popular low-energy adaptive clustering hierarchy (LEACH) algorithm uses the “computation and communication energy model” to increase the lifespan of distributed wireless sensor nodes. As an improved method, we present here that a combination of three clustering algorithms performs better than the LEACH algorithm. The clustering algorithms included in the combination are the k-means+ + , k-means, and gap statistics algorithms. These three algorithms are used selectively in the following manner: the k-means+ + algorithm initializes the center for the k-means algorithm, the k-means algorithm computes the optimal center of the clusters, and the gap statistics algorithm selects the optimal number of clusters in a distributed wireless sensor network. Our simulation shows that the approach of using a combination of clustering algorithms increases the lifespan of the wireless sensor nodes by 15 % compared with the LEACH algorithm. This paper reports the details of the clustering algorithms selected for use in the combination approach and, based on the simulation results, compares the performance of the combination approach with that of the LEACH algorithm.

Novel Architecture of Self-organized Mobile Wireless Sensor Networks

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.

A New Clustering Routing Algorithm for WSN Based on PSO

A wireless sensor network (WSN) consists of spatially distributed wireless sensor nodes. The node power constrains the development of WSN. Employing techniques of clustering can reduce energy consumption of wireless sensor nodes and prolong the network lifetime. Therefore, in the study a new clustering routing algorithm is presented. The clustering algorithm uses the double-layer sensor nodes to communicate. And in order to optimize power energy consumption for WSN node energy, PSO algorithm is employed to find cluster head in each layer. Simulation results show that the algorithm not only can equal power energy of node, but also can reduce consumption in the long distance data transmission.

Simulation of Topology Control Algorithms in Wireless Sensor Networks Using Cellular Automata

We use cellular automata for simulating a series of topology control algorithms in Wireless Sensor Networks (WSNs) using various programming environments. A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computations using only local information. WSNs are composed of a large number of distributed wireless sensor nodes operating on batteries. The objective of the topology control problem in WSNs is to select an appropriate subset of nodes able to monitor a region at a minimum energy consumption cost and, therefore, extend network lifetime. Herein, we present topology control algorithms based on the selection—in a deterministic or randomized way—of an appropriate subset of sensor nodes that must remain active. We use cellular automata for conducting simulations in order to evaluate the performance of these algorithms and investigate the effect/role of the neighbourhood selection in the efficient application of our algorithms. Furthermore, we implement our simulations in Matlab, Java and Python in order to investigate in which ways the selection of an appropriate programming environment can facilitate experimentation and can result in more efficient application of our algorithms.

Design considerations of sub-mW indoor light energy harvesting for wireless sensor systems

For most wireless sensor networks, one common and major bottleneck is the limited battery lifetime. The frequent maintenance efforts associated with battery replacement significantly increase the system operational and logistics cost. Unnoticed power failures on nodes will degrade the system reliability and may lead to system failure. In building management applications, to solve this problem, small energy sources such as indoor light energy are promising to provide long-term power to these distributed wireless sensor nodes. This article provides comprehensive design considerations for an indoor light energy harvesting system for building management applications. Photovoltaic cells characteristics, energy storage units, power management circuit design, and power consumption pattern of the target mote are presented. Maximum power point tracking circuits are proposed which significantly increase the power obtained from the solar cells. The novel fast charge circuit reduces the charging time. A prototype was then successfully built and tested in various indoor light conditions to discover the practical issues of the design. The evaluation results show that the proposed prototype increases the power harvested from the PV cells by 30% and also accelerates the charging rate by 34% in a typical indoor lighting condition. By entirely eliminating the rechargeable battery as energy storage, the proposed system would expect an operational lifetime 10--20 years instead of the current less than 6 months battery lifetime.

Smoke modified environment for crop frost protection: a fuzzy logic approach

During cold weather conditions, there is a high possibility that many crops or planted fields will be damaged due to frost, especially during cloudless cold nights. As it is well known the soil stores energy gained from the sun during the day light time. During cloudless cold nights the soil starts to loss this stored energy, and the soil surface temperature starts to drop less than the ambient temperature. When the soil surface temperature becomes around 0 °C the planted corps starts to freeze. This frost problem can highly damage the crops, or affect the crops growth process which leads to great financial losses for the agriculture sector. In this research a new intelligent agriculture controlled environment is presented based on a fuzzy logic system for frost protection in an open field environment by using a smoke generator or burner and a set of distributed wireless sensor nodes. The presented system can also be integrated with the available cell phone network in the farmer's region, so that the farmer can easily monitor and operate more than one field at a time from his home through his cell phone. The demonstrated simulation results over an examined field, have confirmed the ability of the new system to handle the frost problem at critical situations during cold weather condition by maintaining the soil surface temperature above the freezing point and saving the field crops from being damaged.

Decentralized Inference Over Multiple-Access Channels

The problem of decentralized inference over multiple-access fading channels is considered from a joint source-channel coding perspective. In our setting, spatially distributed wireless sensor nodes collect observation data about a hidden source and communicate relevant statistics to a receiver node that generates the desired inference (estimation or detection) about unknown source parameters. We assume a homogeneous sensor signal field in which information about the source parameters is distributed in space (across sensors) and time in an independent and identically distributed (i.i.d.) manner. Our study characterizes the asymptotic performance of an identical source-channel mapping for i.i.d. sensor observation data in which the same encoder is used at all the nodes. This scheme generalizes many existing methods including uncoded transmission and type-based multiple access. Sufficient conditions are obtained under which our identical mapping approach achieves the genie-aided scaling law (in the number of nodes) associated with a noiseless channel, even when the nodes transmit with asymptotically vanishing power. Our analysis also elucidates the critical impact of channel state information on the achievable performance. In particular, it identifies scenarios in which identical mapping fails and a simple nonidentical mapping scheme is shown to improve performance. Numerical examples are provided to illustrate the theoretical principles derived in the paper.

Locating sensor nodes on construction projects

Localization of randomly distributed wireless sensor nodes is a significant and fundamental problem in a broad range of emerging civil engineering applications. Densely deployed in physical environments, they are envisioned to form ad hoc communication networks and provide sensed data without relying on a fixed communications infrastructure. To establish ad hoc communication networks among wireless sensor nodes, it is useful and sometimes necessary to determine sensors' positions in static and dynamic sensor arrays. As well, the location of sensor nodes becomes of immediate use if construction resources, such as materials and components, are to be tracked. Tracking the location of construction resources enables effortless progress monitoring and supports real-time construction state sensing. This paper compares several models for localizing RFID nodes on construction job sites. They range from those based on triangulation with reference to transmission space maps, to roving RFID reader and tag systems using multiple proximity constraints, to approaches for processing uncertainty and imprecision in proximity measurements. They are compared qualitatively on the basis of cost, flexibility, scalability, computational complexity, ability to manage uncertainty and imprecision, and ability to handle dynamic sensor arrays. Results of field experiments and simulations are also presented where applicable.

Detection, classification, and tracking of targets

Networks of small, densely distributed wireless sensor nodes are being envisioned and developed for a variety of applications involving monitoring and the physical world in a tetherless fashion. Typically, each individual node can sense in multiple modalities but has limited communication and computation capabilities. Many challenges must be overcome before the concept of sensor networks In particular, there are two critical problems underlying successful operation of sensor networks: (1) efficient methods for exchanging information between the nodes and (2) collaborative signal processing (CSP) between the nodes to gather useful information about the physical world. This article describes the key ideas behind the CSP algorithms for distributed sensor networks being developed at the University of Wisconsin (UW). We also describe the basic ideas on how the CSP algorithms interface with the networking/routing algorithms being developed at Wisconsin (UW-API). We motivate the framework via the problem of detecting and tracking a single maneuvering target. This example illustrates the essential ideas behind the integration between UW-API and UW-CSP algorithms and also highlights the key aspects of detection and localization algorithms. We then build on these ideas to present our approach to tracking multiple targets that necessarily requires classification techniques becomes a reality.