Low-power Wireless Sensor Nodes Research Articles

A 42 nJ/Conversion On-Demand State-of-Charge Indicator for Miniature IoT Li-Ion Batteries

An energy-efficient state-of-charge (SOC) indication algorithm and integrated system for low-power wireless sensor nodes with the miniature Internet of Things (IoT) batteries are introduced in this paper. Based on the key findings that the miniature Li-ion batteries exhibit a fast response to the battery current transient, we propose an instantaneous linear extrapolation (ILE) algorithm and circuit system based on the ILE algorithm allowing accurate on-demand estimation of SOC. Due to the on-demand operation, an always-ON current integration is avoided, reducing power and energy consumption by several orders of magnitude. Furthermore, the proposed SOC indicator does not require a battery disconnection from the load, ensuring continuous operation of the applications. The system is implemented in a 180-nm CMOS technology. The power consumption is 42 nW and maximum SOC indication error is 1.7%. The minimum applicable battery capacity is as low as 2 μAh.

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Smart Body Monitoring system using IoT and Machine Learning

In the modern health care environment, the usage of IoT technologies brings convenience of physicians and patients, since they are applied to various medical areas. The body sensor network (BSN) technology is one of the core technologies of IoT developments in healthcare system, where a patient can be monitored using a collection of tiny-powered and lightweight wireless sensor nodes. However, the development of this new technology in healthcare applications without considering security makes patient privacy vulnerable. In this paper, at first, we highlight the major security requirements in BSN-based modern healthcare system. Subsequently, we propose a secure IoT-based healthcare system using BSN, called BSN-Care, which can efficiently accomplish those requirements. The body sensor network (BSN) technology is one of the most imperative technologies used in IoT-based modern healthcare system. It is basically a collection of low-power and lightweight wireless sensor nodes that are used to monitor the human body functions and surrounding environment. Since BSN nodes are used to collect sensitive (life-critical) information and may operate in hostile environments, accordingly, they require strict security mechanisms to prevent malicious interaction with the system.

Performance evaluation of low-power wireless sensor node with hybrid energy storage

Performance evaluation of low-power wireless sensor node with hybrid energy storage

Simple almost‐optimal Cauchy detector for low‐power sensor node LOS receiver applications

Low-cost, low-power wireless sensor nodes that operate in Cauchy noise are required for applications that are located near highly trafficked roads, highways, and bridges, where solar or other green power operation is desirable. A novel suboptimal Cauchy detector of notable simplicity, suitable for low-power sensor nodes, is proposed. The novel suboptimal detector approaches the performance of the optimal detector very closely while surpassing the performance of popular previously published suboptimal Cauchy detectors by 1–4 dB.

Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node.

Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes several simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100 dB, with the mean difference of less than 2 dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring.

An innovative piezoelectric energy harvester using clamped–clamped beam with proof mass for WSN applications

In this paper a miniature piezoelectric energy harvester (PEH) with clamped–clamped beam and mass loading at the center is introduced which has more consistency against off-axis accelerations and more efficiency in comparison to other cantilever PEH’s. The beams consist of different layers of Si, piezoelectric, and insulators based on MEMS technology that vibrates by applying an external force to the fixed frame. Due to beam vibration, variable stress is applied to the AlN piezoelectric and a potential difference is created at the output terminals. AlN is deposited on clamped–clamped beams in such a way that produce more stress points which cause more power to be generated in comparison to other cantilever beam PEH’s with about same dimensions. A partial differential equations (PDE) describing the flexural wave propagating in the multi-morph clamped–clamped beam are solved as theoretical calculations for inherent frequency estimation and is confirmed by simulation results. The obtained inherent frequency is 42 Hz which with 1 g (g = 9.81 m/s2) acceleration produces 4 V and 80 µW maximum electrical peak power that can be used in the node of low-power consumption wireless sensor node for wireless sensor network (WSN) applications.

Development of Implantable Wireless Sensor Nodes for Animal Husbandry and MedTech Innovation.

In this paper, we report the development, evaluation, and application of ultra-small low-power wireless sensor nodes for advancing animal husbandry, as well as for innovation of medical technologies. A radio frequency identification (RFID) chip with hybrid interface and neglectable power consumption was introduced to enable switching of ON/OFF and measurement mode after implantation. A wireless power transmission system with a maximum efficiency of 70% and an access distance of up to 5 cm was developed to allow the sensor node to survive for a duration of several weeks from a few minutes’ remote charge. The results of field tests using laboratory mice and a cow indicated the high accuracy of the collected biological data and bio-compatibility of the package. As a result of extensive application of the above technologies, a fully solid wireless pH sensor and a surgical navigation system using artificial magnetic field and a 3D MEMS magnetic sensor are introduced in this paper, and the preliminary experimental results are presented and discussed.

Low-Frequency and Broadband Vibration Energy Harvesting Using Base-Mounted Piezoelectric Transducers.

Piezoelectric vibration energy harvesters often consist of a cantilevered beam composed of a support layer and one or two piezoelectric layers with a tip mass. While this configuration is advantageous for maximizing electromechanical coupling, the mechanical properties of the piezoelectric material can place limitations on harvester size and resonant frequency. Here, we present numerical and experimental results from a new type of piezoelectric energy harvester in which the mechanical properties and the resonant frequency of the cantilever beam resonator are effectively decoupled from the piezoelectric component. Referred to as a base-mounted piezoelectric (BMP) harvester in this paper, this new design features a piezoelectric transducer mounted beneath the base of the cantilevered beam resonator. The flexibility in the material choice for the cantilever beam resonator means that the resonant frequency and the beam dimensions are essentially free parameters. A prototype made with a 1.6 mm mm mm polyurethane beam, a PZT-5H piezoelectric transducer, and an 8.36-g tip mass is shown to produce an average power of 8.75 and at 45 Hz across a 13.0- load under harmonic base excitations of constant peak acceleration at 0.25 and 1.0-g, respectively. We also show an increase in full-width half-maximum bandwidth approximately from 1.5 to 5.6 Hz using an array of four individual BMP harvesters of similar dimensions with peak power generation of at 37.6 Hz across a 1.934- load at 0.25-g peak base excitation. Finite elements-based numerical simulations are shown to be in reasonable agreement with experimental results, indicating that the harvester behaves like a damped mass-spring system as proposed in this paper. Fabricated using casting and laser machining techniques, this harvester shows potential as a low-cost option for powering small, low-power wireless sensor nodes and other low-power devices.

Study of Piezoelectric Vibration Energy Harvester with non-linear conditioning circuit using an integrated model

ABSTRACTPiezoelectric vibration energy harvester (PVEH) consists of a cantilever bimorph with piezoelectric layers pasted on its top and bottom, which can harvest power from vibrations and feed to low power wireless sensor nodes through some power conditioning circuit. In this paper, a non-linear conditioning circuit, consisting of a full-bridge rectifier followed by a buck–boost converter, is employed to investigate the issues of electrical side of the energy harvesting system. An integrated mathematical model of complete electromechanical system has been developed. Previously, researchers have studied PVEH with sophisticated piezo-beam models but employed simplistic linear circuits, such as resistor, as electrical load. In contrast, other researchers have worked on more complex non-linear circuits but with over-simplified piezo-beam models. Such models neglect different aspects of the system which result from complex interactions of its electrical and mechanical subsystems. In this work, authors have integrated the distributed parameter-based model of piezo-beam presented in literature with a real world non-linear electrical load. Then, the developed integrated model is employed to analyse the stability of complete energy harvesting system. This work provides a more realistic and useful electromechanical model having realistic non-linear electrical load unlike the simplistic linear circuit elements employed by many researchers.

Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

A low-cost hybrid wireless sensor network (WSN) that utilizes the 917 MHz band Wireless Smart Utility Network (Wi-SUN) and a 447 MHz band narrow bandwidth communication network is implemented for electric metering and room temperature, humidity, and CO2 gas measurements. A mesh network connection that is commonly utilized for the Internet of Things (IoT) is used for the Wi-SUN under the Contiki OS, and a star connection is used for the narrow bandwidth network. Both a duty-cycling receiver algorithm and a digitally controlled temperature-compensated crystal oscillator algorithm for frequency reference are implemented at the physical layer of the receiver to accomplish low-power and low-cost wireless sensor node design. A two-level temperature-compensation approach, in which first a fixed third-order curve and then a sample-based first-order curve are applied, is proposed using a conventional AT-cut quartz crystal resonator. The developed WSN is installed in a home and provides reliable data collection with low construction complexity and power consumption.

Influence of combined fundamental potentials in a nonlinear vibration energy harvester.

Ambient mechanical vibrations have emerged as a viable energy source for low-power wireless sensor nodes aiming the upcoming era of the ‘Internet of Things’. Recently, purposefully induced dynamical nonlinearities have been exploited to widen the frequency spectrum of vibration energy harvesters. Here we investigate some critical inconsistencies between the theoretical formulation and applications of the bistable Duffing nonlinearity in vibration energy harvesting. A novel nonlinear vibration energy harvesting device with the capability to switch amidst individually tunable bistable-quadratic, monostable-quartic and bistable-quartic potentials has been designed and characterized. Our study highlights the fundamentally different large deflection behaviors of the theoretical bistable-quartic Duffing oscillator and the experimentally adapted bistable-quadratic systems, and underlines their implications in the respective spectral responses. The results suggest enhanced performance in the bistable-quartic potential in comparison to others, primarily due to lower potential barrier and higher restoring forces facilitating large amplitude inter-well motion at relatively lower accelerations.

English

English

A Configurable 12–237 kS/s 12.8 mW Sparse-Approximation Engine for Mobile Data Aggregation of Compressively Sampled Physiological Signals

Compressive sensing (CS) is a promising technology for realizing low-power and cost-effective wireless sensor nodes (WSNs) in pervasive health systems for 24/7 health monitoring. Due to the high computational complexity (CC) of the reconstruction algorithms, software solutions cannot fulfill the energy efficiency needs for real-time processing. In this paper, we present a 12—237 kS/s 12.8 mW sparse-approximation (SA) engine chip that enables the energy-efficient data aggregation of compressively sampled physiological signals on mobile platforms. The SA engine chip integrated in 40 nm CMOS can support the simultaneous reconstruction of over 200 channels of physiological signals while consuming $ of a smartphone’s power budget. Such energy-efficient reconstruction enables two-to-three times energy saving at the sensor nodes in a CS-based health monitoring system as compared to traditional Nyquist-based systems, while providing timely feedback and bringing signal intelligence closer to the user.

AlGaAs Photovoltaics for Indoor Energy Harvesting in mm-Scale Wireless Sensor Nodes

Indoor photovoltaic energy harvesting is a promising candidate to power millimeter (mm)-scale systems. The theoretical efficiency and electrical performance of photovoltaics under typical indoor lighting conditions are analyzed. Commercial crystalline Si and fabricated GaAs and Al0.2Ga0.8As photovoltaic cells were experimentally measured under simulated AM 1.5 solar irradiation and indoor illumination conditions using a white phosphor light-emitting diode to study the effects of input spectra and illuminance on performance. The Al0.2Ga0.8As cells demonstrated the highest performance with a power conversion efficiency of 21%, with open-circuit voltages >0.65 V under low lighting conditions. The GaAs and Al0.2Ga0.8As cells each provide a power density of $\sim 100$ nW/mm $^{2}$ or more at 250 lx, sufficient for the perpetual operation of present-day low-power mm-scale wireless sensor nodes.

Dielectric elastomer generators that stack up

This paper reports the design, fabrication, and testing of a soft dielectric elastomer power generator with a volume of less than 1 cm3. The generator is well suited to harvest energy from ambient and from human body motion as it can harvest from low frequency (sub-Hz) motions, and is compact and lightweight. Dielectric elastomers are highly stretchable variable capacitors. Electrical energy is produced when the deformation of a stretched, charged dielectric elastomer is relaxed; like-charges are compressed together and opposite-charges are pushed apart, resulting in an increased voltage. This technology provides an opportunity to produce soft, high energy density generators with unparalleled robustness. Two major issues block this goal: current configurations require rigid frames that maintain the dielectric elastomer in a prestretched state, and high energy densities have come at the expense of short lifetime. This paper presents a self-supporting stacked generator configuration which does not require rigid frames. The generator consists of 48 generator films stacked on top of each other, resulting in a structure that fits within an 11 mm diameter footprint while containing enough active material to produce useful power. To ensure sustainable power production, we also present a mathematical model for designing the electronic control of the generator which optimizes energy production while limiting the electrical stress on the generator below failure limits. When cyclically compressed at 1.6 Hz, our generator produced 1.8 mW of power, which is sufficient for many low-power wireless sensor nodes. This performance compares favorably with similarly scaled electromagnetic, piezoelectric, and electrostatic generators. The generator’s small form factor and ability to harvest useful energy from low frequency motions such as tree swaying or shoe impact provides an opportunity to deliver power to remote wireless sensor nodes or to distributed points in the human body without the need for costly periodic battery replacement.

A wireless sensor–actuator system for hazardous gases detection and control

Wireless Sensors Networks (WSN) have recently been applied in a number of hazardous gas detection applications. The state-of-the-art works make an emphasis on sensing and delivering of alert message over the WSN to an operator. Instead, in this paper, we propose a wireless sensor–actuator system which aims at quick gas detection and immediate isolation of gas leak source. The low power wireless sensor node includes catalytic gas sensors, micro processing unit and wireless transceiver which communicates with wireless actuator using ZigBee/IEEE802.15.4 standard and BACnet protocol. Wireless actuator consists of power management circuit, micro processing unit and gas valve. The experimental results demonstrate the sensor node long lifetime while fulfilling performance requirements, quick detection of a hazardous gas and fast actuation time.

Scheduling in Sensor Grid Middleware for Telemedicine Using ABC Algorithm.

Advances in microelectromechanical systems (MEMS) and nanotechnology have enabled design of low power wireless sensor nodes capable of sensing different vital signs in our body. These nodes can communicate with each other to aggregate data and transmit vital parameters to a base station (BS). The data collected in the base station can be used to monitor health in real time. The patient wearing sensors may be mobile leading to aggregation of data from different BS for processing. Processing real time data is compute-intensive and telemedicine facilities may not have appropriate hardware to process the real time data effectively. To overcome this, sensor grid has been proposed in literature wherein sensor data is integrated to the grid for processing. This work proposes a scheduling algorithm to efficiently process telemedicine data in the grid. The proposed algorithm uses the popular swarm intelligence algorithm for scheduling to overcome the NP complete problem of grid scheduling. Results compared with other heuristic scheduling algorithms show the effectiveness of the proposed algorithm.

An electroactive polymer energy harvester for wireless sensor networks

This paper reports the design, fabrication, and testing of a soft electroactive polymer power generator that has a volume of 1cm3. The generator provides an opportunity to harvest energy from environmental sources to power wireless sensor networks because it can harvest from low frequency motions, is compact, and lightweight.Electroactive polymers are highly stretchable variable capacitors. Electrical energy is produced when the deformation of a stretched, charged electroactive polymer is relaxed; like-charges are compressed together and opposite-charges are pushed apart, resulting in an increased voltage.Although electroactive polymers have impressively displayed energy densities as high as 550 mJ/g, they have been based on films with thicknesses of tens to hundreds of micrometers, thus a generator covering a large area would be required to provide useful power. Energy harvesters covering large areas are inconvenient to deploy in a wireless sensor network with a large number of nodes, so a generator that is compact in all three dimensions is required. In this work we fabricated a generator that can fit within a 11×11×9 mm envelope by stacking 42, 11mm diameter generator films on top of each other.When compressed cyclically at a rate of 0.5 Hz our generator produced 300 uW of power which is a sufficient amount of power for a low power wireless sensor node. The combination of our generator's small form factor and ability to harvest useful energy from low frequency motions provides an opportunity to deploy large numbers of wireless sensor nodes without the need for periodic, costly battery replacement.

Static Three-Dimensional Fuzzy Routing Based on the Receiving Probability in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a collection of low-cost, low-power and large-scale wireless sensor nodes. Routing protocols are an important topic in WSN. Every sensor node should use a proper mechanism to transmit the generated packets to its destination, usually a base station. In previous works, routing protocols use the global information of the network that causes the redundant packets to be increased. Moreover, it leads to an increase in the network traffic, to a decrease in the delivery ratio of data packets, and to a reduction in network life. In this paper, we propose a new inferential routing protocol called SFRRP (Static Three-Dimensional Fuzzy Routing based on the Receiving Probability). The proposed protocol solves the above mentioned problems considerably. The data packets are transmitted by hop-to-hop delivery to the base station. It uses a fuzzy procedure to transmit the sensed data or the buffered data packets to one of the neighbors called selected node. In the proposed fuzzy system, the distance and number of neighbors are input variables, while the receiving probability is the output variable. SFRRP just uses the local neighborhood information to forward the packets and is not needed by any redundant packet for route discovery. The proposed protocol has some advantages such as a high delivery ratio, less delay time, high network life, and less network traffic. The performance of the proposed protocol surpasses the performance of the Flooding routing protocol in terms of delivery ratio, delay time and network lifetime.

Bi-stable energy harvesting based on a simply supported piezoelectric buckled beam

Bi-stable piezoelectric energy harvester has been found as a promising structure for vibration energy harvesting. This paper presents a high performance and simple structure bi-stable piezoelectric energy harvester based on simply supported piezoelectric buckled beam. The potential energy function is established theoretically, and electrical properties of the device under different axial compressive displacements, excitation frequencies, and accelerations are investigated systematically. Experimental results demonstrate that the output properties and bandwidth of the bi-stable nonlinear energy harvester under harmonic mechanical excitation are improved dramatically compared with the traditional linear energy harvester. The device demonstrates the potential in energy harvesting application to low-power portable electronics and wireless sensor nodes.