Low-power Wireless Sensor Networks Research Articles

A miniaturized printed rectenna for wireless RF energy harvesting around 2.45 GHz

This paper presents the design of a highly compact printed rectenna for ambient RF energy harvesting around 2.45 GHz. Its antenna structure comprises a rectangular patch with two etched U-shaped slots fed by a symmetric 50 Ω coplanar line. In spite of compact size, it has been directly integrated with a rectifying circuit on the same substrate only at the expense of a 15% frequency shift. The proposed rectenna overall dimension is only 24.9 × 8.6 × 1.6 mm3, the smallest so far reported with comparable performance, which can be easily integrated with any device for energizing low-power wireless sensor networks. It was fabricated and experimentally characterized, achieving a reasonable agreement with the expected simulated results. Measured results indicate that, at the resonant frequency, the antenna part of the proposed rectenna provides a good matching level (<−25 dB) and has a 0.8 dBi peak gain as well as nearly symmetrical radiation properties (in both E- and H-planes). The measured RF-to-DC conversion efficiency (DC output voltage) of the proposed rectenna at a low incident power of −20 dBm is about 20% (97 mV) with a load resistance of 4.7 kΩ. A demonstration experiment of a LED driven by the rectenna was also presented.

A Radical Study of Energy Efficient Hierarchical Cluster-Based Routing Protocols for WSN

For many decades, researchers and vendors are continually developing and designing sensors and wireless network devices for countless applications. These low power wireless sensor network devices have designed to gather and propagate data for applications such as environment, industry, habitat, patient monitoring, and many more to excel humankind— however, these devices also inherent many challenges and drawbacks due to the default hardware design. Subsequently, to mitigate limitations and enhance the capability, authors and researchers have investigated and conferred that minor optimization in modeling or routing techniques gradually elevates the performance of WSN. One of the primary concerns which remain on top of the Domain for discussion is energy conservation in WSN devices. Our primary goal is to analyze and design a cluster-based routing protocol for WSN, An efficient way to elevate the network performance. Finally, the emanate results showcase that the performance of the proposed protocol is much more optimized and favorable when combined with soft-computing tactics when compared to the conventional paradigm.

Quasi-Adiabatic SRAM Based Silicon Physical Unclonable Function

Silicon Physical Unclonable Function (PUF) is a general hardware security primitive for security vulnerabilities. Recently, Quasi-adiabatic logic based physical unclonable function (QUALPUF) has ultra low-power dissipation; hence it is suitable to implement in low-power portable electronic devices such radio frequency identification (RFID) and wireless sensor networks (WSN), etc. In this paper, we present a design of 4-bit QUALPUF which is based on static random access memory (SRAM) for low-power portable electronic devices and then shows the post-layout simulation and measurement results. To evaluate the uniqueness and reliability, the 4-bit QUALPUF is implemented in 0.18 upmum standard CMOS process with 1.8 V supply voltage. The 4-bit QUALPUF occupies 58.7times15.7 upmu mathrm {m}^{2} of layout area. The post-layout simulation results illustrate that the uniqueness calculated from the inter-die HDs of the 4-bit QUALPUF is 47.58%, the average reliability is 95.10%, and the the energy dissipation is 29.73 fJ/cycle/bit. The functional measurement results of the fabricated chip are the same as the post-layout simulation results.

BEE-DRONES: Ultra low-power monitoring systems based on unmanned aerial vehicles and wake-up radio ground sensors

Nowadays, Unmanned Aerial Vehicles (UAVs) represent a significant aid on scenarios where fixed, ground infrastructures are temporarily or permanently not available; this is the case of large-scale applications of the Internet of Things (IoTs), e.g. smart city and agriculture 3.0, where the UAVs can be employed as mobile data mules and gather the data from Wireless Ground Sensors (WGSs). UAV-aided wireless sensor networks (WSNs) introduce considerable advantages both in terms of performance and costs since they avoid the need of error-prone multi-hop communications, and also the installation of static gateways; at the same time, they pose formidable research challenges for their implementation, like the synchronization issue between the UAV and the WGS and the path planning, which should take into account the extremely limited flight autonomy of the UAVs. In this paper, we address both the issues above by proposing BEE-DRONES, a novel framework for large-scale, ultra low-power UAV-aided WSNs. In order to mitigate the synchronization problem, we investigate the utilization of passive Wake-up Radio (WR) technology on the WGSs, and of wireless power transfer from the UAVs: by harvesting the energy from the UAV hovering over it, the WGS is activated only for the short time required to transfer the data toward the mobile sink, while it experiences zero-consumption in sleep mode. We investigate the performance of passive WR-based WGS through real measurements, under different WGS-UAV distances and antenna orientations. Then, based on such results, we formulate the joint WGS scheduling and UAV path planning problem, where the goal is to determine the optimal trajectory of the UAVs activating the WR-based WGSs while taking into account the Value of the Sensing (VoS) as well as the total lifetime of the WSN. The original problem is transformed into a multi-commodity flow problem, and both centralized and distributed heuristics over the multi-graph are proposed. Finally, we evaluate the proposed algorithms through extensive OMNeT++ simulations; the results demonstrate the gain of BEE-DRONES in terms of extended lifetime compared to traditional, non WR-based solutions (e.g. duty-cycle), and in terms of reduced data-correlation compared to non VoS-aware path planning solutions.

LoRa Base-Station-to-Body Communication With SIMO Front-to-Back Diversity

The LoRa standard is currently widely employed for low-power long-range wireless sensor networks at sub-GHz frequency bands. The longer wavelengths associated with sub-GHz technology provide excellent radiowave propagation characteristics, yielding a much larger coverage than the higher frequency bands. In the case of wearable sensors, the 868 MHz band can be covered by textile substrate-integrated-waveguide antennas of a convenient size. In body-centric communication systems, front-to-back (F/B) diversity is an important asset to mitigate the shadowing of the antennas by the presence of the human body. This article describes a diversity textile-antenna-based LoRa platform with integrated transceivers. Outdoor measurement campaigns are conducted to assess the performance of the wearable LoRa nodes with F/B diversity in an urban radio propagation environment at walking and cycling speeds. These experiments prove that large ranges of 1.5 km can easily and reliably be achieved for off-body LoRa communication links. The results demonstrate a significant performance improvement in terms of packet loss in NLoS situations when comparing single-receiver performance with different spatial receiver diversity applications. In addition, link budget increases up to 5.5 dB, owing to the realized diversity gain.

Quadrotor-Based Lighthouse Localization with Time-Synchronized Wireless Sensor Nodes and Bearing-Only Measurements.

Some robotic localization methods, such as ultra wideband localization and lighthouse localization, require external localization infrastructure in order to operate. However, there are situations where this localization infrastructure does not exist in the field, such as robotic exploration tasks. Deploying low power wireless sensor networks (WSNs) as localization infrastructure can potentially solve this problem. In this work, we demonstrate the use of an OpenWSN network of miniaturized low power sensor nodes as localization infrastructure. We demonstrate a quadrotor performing laser-based relative bearing measurements of stationary wireless sensor nodes with known locations and using these measurements to localize itself. These laser-based measurements require little computation on the WSN nodes, and are compatible with state-of-the-art 2 mm × 3 mm monolithic wireless system-on-chips (SoCs). These capabilities were demonstrated on a Crazyflie quadcopter using an Extended Kalman Filter and a network of motes running the OpenWSN wireless sensor network stack. The RMS error for X positioning was 0.57 m and the error for Y positioning was 0.39 m. This is the first use of an OpenWSN sensor network to support robotic localization. Furthermore, simulations show that these same measurements could be used for localizing sensor motes with unknown locations in the future.

실시간 산불 모니터링을 위한 이벤트 처리 기반 저전력 저비용 무선 센서 네트워크

In this paper, we propose an event-driven low-power low-cost wireless sensor network (WSN) for real time wildfire monitoring. The proposed system will be mainly deployed and operated in a fire alert (or monitoring) area that could be divided into several sectors, each sector consisting of a controller (AP: access point) and its controlled nodes. For the evaluation of the proposed system, we implement a test bed (TB) using Arduino Uno board that has a smoke detector and a ZigBee module. The presented sensor nodes that are operated in power saving mode (PSM) during most of idle period have a longer battery life. Once a node detects smoke sample (which is termed as sensData) that is larger than a given threshold, it will generate a transmission message, called msgSensInfo (msgSensInfo1 for node fusion or msgSensInfo2 for AP fusion), and transmit that message to the AP and then the remote server. When a sensing event or a wake-up message event occurs, the presented node system is woken up from PSM, and gives a prompt (real-time) response including sensing message msgSensInfo generation and its transmission to AP. The proposed system has a data fusion algorithm collecting and synthesizing either multiple spatial samples (in case of AP fusion) or multiple time samples (in case of node fusion) that improves the fire detection performance further. Therefore, compared to existing low-cost WSN schemes, the proposed low-cost WSN scheme would be better at the perspective of real time performance, cost-effectiveness, and life-cycle such that it would be a good candidate for wildfire prevention as well as initial fire fighting.

A Self-Sustained Smart Monitoring Platform for Capacitive De-Ionization Cell in Wireless Sensor Network

Water treatment is the most concerned research area as it is closely related to the quality of human life. Capacitive de-ionization (CDI) has become a popular desalination technique for water treatment in recent years; however, transferring CDI technology to practice industrial applications face many problems due to the lack of experience and ability of monitoring on its operation status. Thus, in this article, a novel self-powered smart monitoring platform (SMP) is codesigned with a laboratory-scale CDI cell by providing regulated polarized voltage to prevent faradaic reactions and to evaluate CDI's performance using desalination metrics. The proof-of-concept SMP can acquire sensory data and wirelessly transmit information to the reader by radio-frequency identification (RFID) technique. A laboratory-scale CDI cell is fabricated in house by the cost-effective carbon electrodes with high electrochemical stability. Experiments are conducted to evaluate the function of the system on real-time monitoring of the CDI cell for their conductivity, salt absorption, and charge efficiency. The measurement results demonstrate that the proposed prototype is effective in terms of supplying, monitoring, and diagnosing the operation condition of the CDI cell. Furthermore, the proof-of-concept SMP developed for the CDI reactor can achieve up to 8.8-m communication distance, while consuming 402.6 μ W active power during operation. Therefore, it is a suitable choice for low-power and low-cost wireless sensor network.

Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging.

Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-the-art for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

Optimization and modeling of modified unslotted CSMA/CA for wireless sensor networks

IEEE 802.15.4 protocol is intended to accomplish the characteristics of low power and low rate Wireless Sensor Network. It employs carrier sense multiple access with collision avoidance (CSMA/CA) protocol to access the network using either unslotted or slotted mode. This paper concentrates on the unslotted CSMA/CA where the node tends to wait for a very limited backoff exponent value, and cannot perform clear channel assessment until backoff procedure is completed. Therefore, the collision probability and the average delay are high.To enhance the unslotted CSMA/CA performance, this paper proposes a modified unslotted CSMA/CA that divides the backoff delay into Main Backoff and Secondary Backoff. The Markov model for the modified CSMA/CA is presented to assess a single hop IEEE 802.15.4 behavior, and derive expressions for average delay, energy consumption and reliability. An optimization problem is also presented to minimize the delay while guaranteeing energy consumption and reliability constraints for the modified CSMA/CA. OPNET simulation tool is applied to compare the modified to the standard unslotted CSMA, and to validate the Markov model proposed. The results demonstrate that the modified CSMA improves the reliability, while reducing the average delay significantly.

Real-time detection of energy consumption of IoT network nodes based on artificial intelligence

Low power loss networks and wireless sensor networks are important components of the Internet of Things. With the development and popularization of artificial intelligence, the network application of wireless sensors is gradually scaled up and industrialized. Aiming at the problems of high energy consumption of the routing strategy, the algorithm protocol is easy to fall into the local optimum and the uneven energy consumption of network nodes. This paper proposes a regional energy balance routing algorithm based on intelligent chaotic ant colony. Based on the intelligent chaotic ant colony algorithm, combined with the remaining energy factors of wireless sensor network nodes, this paper propose a neighbor selection strategy. In order to enhance the ant search ability and speed up the algorithm convergence, an adaptive perturbation strategy and algorithm termination conditions are proposed respectively to find the global optimal solution and avoid falling into the local optimal solution. Simulation results show that the routing planning method in this paper has obvious advantages in terms of network energy consumption and network delay, node equilibrium energy distribution, network life cycle and other performance. Compared with similar algorithms, the average energy consumption has been saved by 7.3%.

Accurate fall detection for patients with Parkinson's disease based on a data event algorithm and wireless sensor nodes

Elderly fall detection in Parkinson’s disease (PD) and epilepsy can cause broken bones or other injuries, decreasing the quality of life and possibly resulting in death. However, such fall-detection systems suffer from certain limitations and challenges such as fall-detection accuracy. This work aims to design and implement a wearable fall-detection system (WFDS) for PD patients based on the low-power ZigBee wireless sensor network (WSN). Patient falls were accurately detected based on the data event algorithm (DEA) results of two wireless sensor nodes an accelerometer and Myoware mounted on the patient’s body. The fall direction of the PD was accurately determined based on a direction fall event (DFE) algorithm in the receiver node. The experimental results show that the WFDS achieved 100% accuracy, sensitivity, and specificity in detecting the patient’s fall. The experimental WFDS appears to outperform existing modalities in terms of fall detection sensitivity, accuracy, and specificity.

Gathering data with packet-in-packet in wireless sensor networks

In many wireless sensor network (WSN) mission-critical applications, a collector, e.g., a drone acting as a data sink, is required to gather data from all the source nodes in the area of interest. It is, thus, an all-to-one scenario. Data from each node (e.g., local temperature or its binary status) normally only consists of several bytes. Furthermore, often, data collection is expected to be done as fast as possible, especially for mission-critical applications or applications where a battery-powered sink is used (e.g., a drone). Thus, it is preferred that there is no preparation phase for the network to schedule or establish any routes in advance. Concurrent transmission (CT), a novel communication paradigm, has been shown to effectively achieve reliable and energy-efficient flooding in low-power wireless networks. With multiple nodes exploiting a receive-and-forward scheme, this technique requires no routing and works effectively in flooding-based networks, i.e., in one-to-many scenarios. Hence, CT-based communication is a good choice for fast data collection. However, a kind of global scheduling is essential for data collection in CT-based WSNs, in order to globally schedule a node that initiates a flooding in the network. In this article, to comply with the requirements of the aforementioned data collection application, we propose Packet-in-Packet (PiP), an energy-efficient paradigm requiring no global scheduling for timely data collection in low-power WSNs. PiP builds on concurrent transmissions and uses a packet concatenation capability to gather single-hop information in a best-effort manner. PiP does not require any pre-scheduling of traffic in the network, and thereby significantly reducing collection time. We compare PiP with a number of state-of-the-art protocols by extensive experiments in two testbeds, FlockLab and Indriya, respectively. Experimental results show that PiP achieves high reliability and low latency in all the scenarios in the real-world testbeds. Specifically, when the transmission power of nodes is set to 0 dBm, PiP takes only 287 ms (at least 1.8 × faster than the state-of-the-art protocols) to complete a 26-to-one data collection in FlockLab and 965 ms (1.1 × faster than a state-of-the-art protocol LWB) to complete a 42-to-one collection in Indriya, respectively.

SCSMA: A Smart CSMA/CA Using Blind Learning for Wireless Sensor Networks

A smart carrier sense multiple access (SCSMA) using control messages is proposed for low power and low bandwidth wireless sensor networks (WSNs). In traditional WSNs, the use of media access control (MAC) messages is not recommended since data are of small size. However, if data size is increased with data aggregation or multimedia data, the control messages can be used for reliable data transmission. Thus, an efficient mechanism is needed to avoid the collision of control messages and data. SCSMA employs a blind learning algorithm with low complexity to prevent collision during channel contention and data transmission, even in the presence of hidden nodes. It is shown by simulation and analysis that SCSMA improves throughput by 29.5% to 71.6%, and reduces energy consumption by 20.5% to 36.2%, compared to the recent best approach using MAC messages. Simulation data are also verified by experimental data.

An overview of applications of renewable energy methods in the development of structural health monitoring systems

Structural health monitoring is an efficient method for monitoring and scheduling maintenance of civil engineering infrastructure when exposed to various types of loadings. Advances in innovative technologies such as low power wireless sensor networks have further improved the efficiency and versatility of SHM systems. Moreover, harvesting energy from ambient and renewable energy sources, such as solar, wind, structural thermal gradient and vibration, have addressed the issue of the limited life span of batteries powering these sensors. Over the years, the scope of different harvesting mechanisms has been extended from a sensors' power source to sensing structural anomalies. This paper reviews the scope of different energy harvesting technologies in improving the robustness and efficiency of a structural health monitoring system.

An overview of applications of renewable energy methods in the development of structural health monitoring systems

Structural health monitoring is an efficient method for monitoring and scheduling maintenance of civil engineering infrastructure when exposed to various types of loadings. Advances in innovative technologies such as low power wireless sensor networks have further improved the efficiency and versatility of SHM systems. Moreover, harvesting energy from ambient and renewable energy sources, such as solar, wind, structural thermal gradient and vibration, have addressed the issue of the limited life span of batteries powering these sensors. Over the years, the scope of different harvesting mechanisms has been extended from a sensors' power source to sensing structural anomalies. This paper reviews the scope of different energy harvesting technologies in improving the robustness and efficiency of a structural health monitoring system.

Coexistence Analysis of Multiple Asynchronous IEEE 802.15.4 TSCH-Based Networks

Low-power Wireless Sensor Networks (WSNs) play a key role in realization of the Internet-of-Things (IoT). Among others, Time Slotted Channel Hopping (TSCH) is a Medium Access Control (MAC) operational mode of the IEEE 802.15.4 standard developed for communications in short range IoT networks. TSCH provides high level reliability and predictability by its channel hopping mechanism and time division channel access nature. In many applications, a number of TSCH networks may coexist in the same neighborhood. Several vehicles close to one another, each including a TSCH network for its in-vehicle communications, serve as an example. Since such networks are running independent of one another, they are not expected to be synchronized in time, and they are not scheduled to operate in exclusive frequency channels. This may lead to inter-TSCH interferences deteriorating the reliability of the networks, which is an important requirement for many IoT applications. This paper analyzes the impact of multiple asynchronous TSCH networks on one another. An analytical model is developed that estimates the chance of such interferences, and the expectation of the number of affected TSCH channels when a number of them are in the vicinity of one another. The developed model is verified using extensive simulations and real-world experiments. Also, a scalable and fast multi-TSCH coexistence simulator is developed that is used to get insight about coexistence behaviors of any number of TSCH networks with various configurations.

A reconfigurable hardware platform for low-power wide-area wireless sensor networks

Low power, large-area wireless sensor networks (WSNs) have been experiencing rapid growth in a wide range of applications, such as environmental monitoring applications and natural disaster early warning systems. The WSN consists of numerous nodes with sensing, computation, actuation, and radio communication capabilities. Dynamically reconfigurable hardware and context-aware operation to optimize performance and functionality and to prolong the lifetime of sensor nodes are critical goals in the design of distributed sensing systems, especially for battery-based systems being deployed in complex geographic areas where are hard to approach. In recent years, Programmable System-on-Chip (PSoC) technology is emerging as an efficient solution for achieving the dynamic hardware reconfiguration of a sensor node in a single chip. That aims at optimizing the use of resources, minimizing of energy waste, and system size according to the requirements of the applications. This paper presents the implementation of a configurable hardware platform for remote sensing systems based on PSoC and LoRa technology. The proposed hardware design stands out for high performance, ultralow-power, providing long-range communication as well as reconfigurable interfaces in communicating and manipulating with various types of sensors and actuators. The experiments to evaluate the functional requirements and energy consumption of the design were investigated with positive results.

Energy-efficient MAC protocols for wireless sensor networks: a survey

Wireless sensor network (WSN) is a network of a large number of battery-powered tiny sensor nodes wirelessly connected together to facilitate a wide range of monitoring applications. As WSN nodes are energy-constrained microelectronic devices, the primary design objective of WSNs is to minimise energy consumption to prolong the network lifetime. To achieve this goal, a range of cross-layer techniques, particularly focusing on medium access control (MAC) sublayer, is proposed targeting different WSN applications. This paper aims to survey low-power WSN MAC protocols, proposed from 2000 to the present, emphasising some general aspects including the issues addressed, the solutions proposed, design principles, strengths, drawbacks and target applications. With this aim, we mainly classify the MAC protocols into three categories: contention-based protocols, time division multiple access (TDMA)-based protocols and hybrid protocols, where the first category is further subdivided into subclasses. The development trends and potential research challenges are also discussed.

Design of Tri-Band Microstrip Patch Rectenna for Radio Frequency Energy Harvesting System

This paper presents a tri-band patch antenna integrated with a rectifier circuit for radiofrequency energy harvesting systems. This rectenna is more suitable for low power wireless sensors networks with rechargeable battery supplies. The radiating part is the rectangular patch with corrugated edge tapered at one of its sides operating at tri-band in the WLAN and C band. The rectenna is integrated with a radiating patch reducing the overall size of the rectenna without compromising antenna performances. The rectenna is modeled using an Ansoft HFSS simulator and is fabricated on a low-cost FR4 substrate. The performances of the rectenna are measured in the anechoic chamber and are in good agreement with simulated results. The antenna achieves a −10 dB impedance bandwidth of 100 MHz (2.4–2.5 GHz & 5–5.1 GHz) in the WLAN band in addition to 150 MHz (4–4.15 GHz) in the C band. A DC power output of 298 mV is obtained in the operating bands.