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Battery power has been a popular choice of delivering DC power to many portable RF systems including wireless sensor nodes/internet of Everything (IoE). An autonomously powered RF system of the orders of 100’s of µwatts is becoming increasingly popular in recent times because of integrated solutions in energy harvesting. The minimum sensitivity of an RF energy harvester and the targeted deliverable output voltage for a specific load resistance are dictated by threshold voltage of transistors used and reverse leakage of such transistors. A detailed look into the architectures of rectifiers can help tackle design problems in the RF-DC conversion process. So in this work we focused on the design of integrated RF energy harvesting by studying four important architectures of RF-DC converters. To achieve a fair comparison between these architectures, a matching network operating at 0.8 MHz is designed and applied for simulation. All of these converters are tested in LT-SPICE XVII using the same designed matching network and the rectifiers are implemented in 180 nm CMOS technology.

Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customised services. A fundamental requirement of these services is person identification. Although a variety of person identification approaches have been proposed, they suffer from several limitations in practical applications such as low energy efficiency, accuracy degradation, and privacy issue. This paper proposes an energy harvesting based privacy-preserving gait recognition scheme for smart space which is named . In , we extract discriminative features from one-dimensional gait signal and design an attention-based long short term memory (LSTM) network to classify different people. Moreover, we leverage a novel Bloom filter-based privacy-preserving technique to address the privacy leakage problem. To demonstrate the feasibility of , we design a proof-of-concept prototype using off-the-shelf energy harvesting hardware. Extensive evaluation results show that the proposed scheme outperforms state-of-the-art by 6–10% and incurs low system cost while preserving user’s privacy.

In the era of the sixth generation (6G), the deployment of massive Internet of Things (IoT) generates and processes large amounts of data, resulting in high energy demand and huge challenges to the energy-limited IoT devices. To achieve green and sustainable communication, energy harvesting is a feasible technology to prolong the lifetime of IoT. However, the existing energy harvesting architecture cannot guarantee the privacy of energy users while improving the intelligence and effectiveness of energy transmission. To solve these issues, we propose a differential privacy and intelligent reflecting surface empowered privacy-preserving energy harvesting framework for 6G-enabled IoT. First, a secure and intelligent energy harvesting framework is designed, which includes an intelligent reflecting surface-aided radio frequency power transmission mechanism and a differential privacy-based energy harvesting mechanism. Secondly, an exponential mechanism-based privacy-preserving energy harvesting scheme is established, where we analyze the adversary mode, propose the differential privacy-enabled location-preserving algorithm, and provide security analysis and proof. Third, we quantify the user satisfaction for energy harvesting and propose a deep reinforcement learning empowered resource allocation scheme to maximize the weighted satisfaction of all system users. Finally, simulation results show the effectiveness of the proposed secure and intelligent energy harvesting architecture for 6G IoT.

Piezoelectric energy harvester (PEH) arrays are promising in many application scenarios. However, few interface circuits have been developed to manage the multiple AC inputs from PEHs. This paper proposes an extensible P-SSHI (parallel synchronized switch harvesting on inductor) array interface scheme to realize a multi-input conversion from PEH arrays. We develop a split-inductor-capacitor topology that can extract electrical energy from multiple PEHs. The proposed circuit topology effectively handles the inductor access conflict in the cases of PEHs with close, identical, and opposite vibration phases, insensitive to AC input phase changes. For demonstrating the capability of dealing with multiple AC inputs from PEHs and the enhancement effect on power output, we construct and test a self-powered three-channel array circuit with the passive peak detection function. Excited by sinusoidal vibrations, our circuit effectively avoids the energy return and efficiently achieves the power combination of the three PEHs. Compared with the classic full-bridge circuit, the proposed circuit helps increase the power output by 4.8 times. Also, to show the universality of the circuit, the circuits operation under various excitations is tested and analyzed.

This paper proposes digitally controlled power management circuit (PMC) for vibration energy harvesting in vehicle suspension system. The PMC is tested with a mechanical motion rectifier based electromagnetic energy harvester that converts from bi-directional vibration to unidirectional rotation, with improved energy harvesting performance and efficiency. Topology of one-stage DC-DC converter is adapted, and it is digitally controlled while considering the uncertainty of vibration sources. In order to efficiently transfer the harvested power to the electrical load, the algorithm of digital controller is designed to have four operation modes, which are impedance matching mode, voltage regulation mode, generator protection mode, and low power mode, for increasing the PMC efficiency while reducing the power consumption of controller. Experimental results show that proposed circuit can successfully operate and switch between the four operation modes. In the evaluation of PMC performance with 2mm and 2Hz excitation, the efficiency of proposed one-stage power converter is 86%. The total power consumption of controller in active mode and low power mode are 109 mW and 2.52 mW respectively while harvesting about 3W vibration energy.

As wearable microelectronics become more ubiquitous, and the size and power requirements of such devices decrease, there is increasing research interest in harnessing power from ambient environmental sources through embedded systems as alternative to battery replacements. Accordingly, a multimodal hybrid piezo-electromagnetic insole energy harvester (PEM-IEH) has been presented in this paper as a means to reclaim the biomechanical energy wasted in the surroundings during daily walking. The hybrid device consists of two piezo-ceramic wafer plates, two magnets, and two wound coils. The designed harvester has been simulated, fabricated and experimentally validated. From the frequency response, the hybrid harvester exhibits four resonant frequencies concentrated around 8, 25, 50, and 51 Hz. A maximum combined power of 1400 µW is generated across the optimal load resistances of upper and lower electromagnetic generators at first resonant frequency (8 Hz) under 0.5 g base acceleration, and a 269 µW peak power is obtained across the optimum load resistances of the upper and lower piezoelectric generators at 4th resonance (51 Hz) under 0.5 g. The miniature (46.8 cm3) and lightweight (43.3 g) harvester was incorporated into the sole of an adult-sized commercial shoe, and has been shown to be able to charge a 100 µF capacitor, up to 2.4 Volt within approximately 10 min of slow jogging. The capacitor charging performance presents a remarkable potential application of the harvester in development of micro-power monitoring sensors and wearable microelectronic gadgets where batteries pose a practical bottleneck.

A solid-liquid triboelectric nanogenerator (TENG) has attracted increasing research interest in relation to the development of regeneration energy based on water resources. The output of solid-liquid TENG remains unsolved, however, because of the low voltage output that impedes wide applications. To this end, in this work we developed a miniaturized microfluidic channel-based TENG device for highly efficient conversion of energy from the transport of a water droplet to an electrical output. We investigated an optimized design in a triboelectric material, the droplet transport and the electrostatic induction layer to provide a high voltage output and stable energy harvesting. The optimized device demonstrated maximum voltage amplitude 102 mV with an ultralow liquid consumption, 0.36 [Formula: see text], resulting in sample-energy conversion 283.33 mV/ [Formula: see text]. This novel device is expected potentially to address the limitations imposed by sample consumption in energy harvesting in the future.

Inspired by hand push whisk blenders that are widely used in the kitchen, we here propose an energy harvester that enables conversion of low-frequency translational vibration to high-speed rotations and further generates electricity via the electromagnetic effect. The whisk-inspired energy harvester (W-EH) is composed of an internal thread sleeve, an external thread driving shaft, a spring, and a buoy. Compared with transmission approaches used by electromagnetic power generators, the proposed design has the superiority of low cost, ultra-low operation frequency (lower than 1 Hz), and high power output. Tests in water indicate that the normalized power density is 300% higher than the state of the art. Excited by mimicking ocean waves at 1.5 Hz, the W-EH prototype generates a maximum power of 64.4 milliwatts and succeeds in lighting up 115 LEDs simultaneously, which power is enough for continuous operations of most wireless sensors.

To break through the limitation of battery-powered wireless sensor networks, a novel kind of network, named Battery-Free Wireless Sensor Network (BF-WSN), is proposed. Battery-free sensor nodes in BF-WSNs harvest energy from power sources in their ambient environment, such as solar power, wind power and radio frequency (RF) signal power, etc., instead of batteries. Therefore, the energy consumption of battery-free sensor nodes are not limited by the battery capacity anymore. However, they still have limited energy harvesting rates and energy capacities. Data aggregation is an fundamental operation in sensor networks where the sensory data gathered by the relay nodes can be merged by in-network computation, such as taking the maximum, average, or sum, etc., of them. Due to the energy features of BF-WSNs, the data aggregation scheduling problem in BF-WSNs is more complicated and the previous aggregation scheduling algorithms designed for battery-powered WSNs are no longer applicable. This paper investigates the Minimum-Latency Aggregation Scheduling problem in BF-WSNs, which is proved to be NP-hard. Then, we propose the Data Aggregation Scheduling algorithm to solve the problem. Finally, the theoretical analysis and extensive simulation results are provided to verify the performance of the proposed algorithm.

Radio frequency (RF) wireless energy transfer (WET) is a key technology that may allow seamlessly powering future massive low-energy Internet of Things (IoT) networks. To enable efficient massive WET, channel state information (CSI)-limited/free multi-antenna transmit schemes have been recently proposed in the literature. The idea is to reduce/null the energy costs to be paid by energy harvesting (EH) IoT nodes from participating in large-scale time/power-consuming CSI training, but still enable some transmit spatial gains. In this paper, we take another step forward by proposing a novel CSI-free rotary antenna beamforming (RAB) WET scheme that outperforms all state-of-the-art CSI-free schemes in a scenario where a power beacon (PB) equipped with a uniform linear array (ULA) powers a large set of surrounding EH IoT devices. RAB uses a properly designed CSI-free beamformer combined with a continuous or periodic rotation of the ULA at the PB to provide average EH gains that scale as $0.85\sqrt{M}$, where $M$ is the number of PB's antenna elements. Moreover, a rotation-specific power control mechanism was proposed to i) fairly optimize the WET process if devices' positioning information is available, and/or ii) to avoid hazards to human health in terms of specific absorption rate (SAR). We show that RAB performance even approaches quickly (or surpasses, for scenarios with sufficiently large number of EH devices, or when using the proposed power control) the performance of a traditional full-CSI based transmit scheme, and it is also less sensitive to SAR constraints. Finally, we discuss important practicalities related to RAB such as its robustness against non line-of-sight conditions compared to other CSI-free WET schemes, and its generalizability to scenarios where the PB uses other than a ULA topology., Comment: 12 pages, 10 figures. Accepted for publication in IEEE IoT Journal

The fourth industrial revolution is paving the way for Industrial Internet of Things applications where large number of wireless nodes, equipped with sensors and actuators, monitor the production cycle of industrial goods. This paper proposes and analyses LoRaIN, a network architecture and MAC-layer protocol thought for on-demand monitoring of industrial machines. Our proprietary system is an energy-efficient, reliable and scalable solution, where the protocol is built on top of LoRa at 2.4 GHz. Indeed, the low-power characteristics of LoRa allow to reduce energy consumption, while Wireless Power Transfer is used to recharge batteries, avoiding periodic battery replacement. High reliability is obtained through the joint use of Frequency and Time Division Multiple Access. A dynamic LoRaIN scheduler manages the communication and recharging phases depending on the tasks assigned to the nodes, as well as the number of monitoring devices. Performance is measured in terms of network throughput, energy consumption and latency. Results demonstrate that the proposed solution is suitable for monitoring applications of industry machines.

This paper proposes a new transmission policy for intelligent reflecting surface (IRS) empowered wireless powered internet of things systems. Particularly, an energy station (ES) wirelessly charges for multiple IoT devices during downlink wireless energy transfer (WET) and then these devices deliver their own message to an access point (AP) during uplink wireless information transfer (WIT). Also, an IRS is deployed to improve energy harvesting and data transmission capabilities. To enhance self-sustainability of the IRS, the IRS harvests energy from the ES based on the harvest-then-transmit protocol. In this paper, we maximize the sum throughput via optimizing the phase shifts of the IRS, the transfer time scheduling as well as the power splitting ratio. Due to the non-convexity of the formulated problem, we divide the problem into two sub-problems, each of which can be handled separately. Then, we adopt an alternating optimization (AO) algorithm with the semidefinite programming (SDP) relaxation. Also, we consider a special case where the circuit power consumption of IoT devices can be neglected. In this case, we derive a closed form solution for the optimal transmission time slots, power allocation and phase shift by the Lagrange dual method. Finally, numerical evaluations validate effectiveness of the proposed scheme, which significantly benefits from the IRS in improving network throughput.

The emerging hybrid backscatter and energy harvesting devices have been regarded as a promising scheme for green Internet-of-Things (IoT). In the interwoven primary and secondary wireless powered IoT networks, we develop a novel hybrid scheme that integrates the backscatter communication and the harvest-then-transmit (HTT) protocol. In order to mitigate the adverse effect on the primary user (PU), the secondary users (SUs) are classified into ‘Cooperation Scenario’ and ‘Coexistence Scenario’ based on their different levels of interference to the PU. In ‘Cooperation Scenario’, we propose a cooperation protocol where the SUs operate in the backscatter mode so as to relay information to the PU. Therefore, the SUs are rewarded for harvesting energy and obtaining the spectrum access time from the primary system. Also, in ‘Coexistence Scenario’, a coexistence strategy is developed to enable the SUs to operate in either ambient backscatter or energy harvesting mode during the channel busy time. When the primary channel becomes idle, the SUs are capable of active transmission by using the harvested energy. For each scenario, we investigate the sum-throughput maximization problem of the secondary system. Employing the Lambert W function and the block coordinate descent method, the optimal time allocation can be obtained via the Lagrangian dual method. Numerical results validate that the proposed hybrid backscatter and HTT scheme improves the performance of the secondary system evidently compared with benchmark methods.

This paper studies the complete targets coverage problem in a novel and practical context: sensor nodes operating in an Internet of Things (IoT) network that have a dual-battery system with non-ideal properties. Specifically, sensor nodes have batteries that cannot be charged and discharged simultaneously. Also, sensor nodes must fully discharge/charge a battery before it is charged/discharged again. We outline a Mixed Integer Linear Program (MILP) and use it to optimize the activation schedule of sensor nodes. Its objective is to maximize complete targets coverage lifetime. We also propose a heuristic solution named Battery Switching Aware Algorithm (BSAA) to solve large problem instances. Simulation results show the performance of BSAA achieves approximately 98% of the coverage lifetime of MILP. In addition, equipping sensor nodes with a dual battery system prolongs the coverage lifetime by up to 70.2%.

Owing to the shorter wavelength in the millimeter-wave (mmWave) spectrum, miniaturized antennas can receive power with a higher efficiency than UHF bands, promising sustainable mmWave-powered Internet of Things (IoT) devices. Nevertheless, the performance of a mmWave power receiver has not been compared, numerically or experimentally, to its sub-6 GHz counterpart. In this paper, the performance of mmWave-powered receivers is evaluated based on a novel wearable textile-based higher-order mode microstrip antenna, showing the benefits of wireless power transmission (WPT). Firstly, a broadband antenna is proposed maintaining a stable wearable measured bandwidth from 24.9 to 31.1 GHz, over three-fold improvement compared to a conventional patch. The proposed antenna has a measured 8.2 dBi co-polarized gain with the highest thickness-normalized efficiency of a wearable antenna. When evaluated for compact power receivers, the measured path gain shows that WPT at 26 GHz outperforms 2.4 GHz by 11 dB. A rectenna array based on the proposed antenna is then evaluated analytically showing the potential for up to 6.3x higher power reception compared to a UHF patch, based on the proposed antenna's gain and an empirical path-loss model. Both use cases demonstrate that mmWave-powered rectennas are suitable for area-constrained and large-area wearable IoT applications.

An energy harvesting system requires a power converter with its compact size and high power efficiency. Following the trend, this study suggests a new switched capacitor converter (SCC). The proposed converter is designed by a parallel- and cross-connecting two Fibonacci topologies. This connection leads the proposed SCC to generate its multilevel outputs as well. The proposed SCC has the lowest output resistors under five times conversion ratios from the theoretical analysis and comparison of two different SCC topologies. Simulation results confirm that the proposed SCC can be operated over 90% power efficiencies under 100 mW.

Vibration energy harvesting using multiple piezoelectric transducers (multi-PZTs) can increase its output power and environmental adaptability. At present, there are still few researches on multi-input interface circuits for multi-PZTs, especially those using the parallel synchronized switching harvesting on inductor (PSSHI) technique. Therefore, this article presents a self-powered dual-inductor MI-PSSHI-VDR interface circuit. It can process multi-PZT voltages with arbitrary phases input. The measurements demonstrate that the prototyped MI-PSSHI-VDR circuit can extract a peak power of 1.93 mW from four PZTs under an excitation of 1.5 g and 75.5 Hz. The energy integration efficiency and energy extraction efficiency of the prototyped circuit are 93.2% and 75.1%. Compared with a multi-input full-bridge rectifier, the proposed circuit can achieve 3.22 power improvement and 3.58 voltage improvement, which grasps a good balance between the indexes of peak output power and load voltage range. Additionally, the MI-PSSHI-VDR circuit is easy to implement and shows a good scalability, which can be an alternative solution for multi-PZTs energy harvest

A book-shaped all-in-one energy harvester module with a piezo-triboelectric hybrid structure as a next-generation eco-friendly energy source was manufactured based on flexible piezoceramic nanofibers with enhanced current characteristics obtained by controlling the added amount of carbon black (CB). To prepare flexible piezoceramic nanofibers with favorable current properties, 0.78Bi0.5Na0.5TiO3−0.22SrTiO3 (BNT-ST) piezoelectric ceramics were composited with CB, a highly conductive material, and then electrospun with a poly(vinylidene fluorideco–trifluoroethylene) polymer. The prepared CB/BNT-ST nanofibers were modularized into piezoelectric energy harvester modules (PEHMs) with interdigitated electrodes, yielding an improved output performance with a high voltage of 10.1 V and high current of 2.02 nA. A book-shaped triboelectric energy harvester module (TEHM) was manufactured with polydimethylsiloxane on one side and the CB/BNT-ST nanofibers on the other side, affording an improved output performance with a high voltage of 391 V and high current of 130 μA. A book-shaped all-in-one hybrid energy harvester module (HEHM) was then manufactured by fitting PEHMs at both ends of the book-shaped TEHMs. As a result of optimizing the output performance by connecting HEHM multiple layers, a high voltage and current of 1043 V and 579 μA were observed, respectively, and charging of a 1.0 μF capacitor was completed in 25 s. Furthermore, in simulated energy harvesting experiments using the all-in-one HEHM, LED light bulbs were clearly illuminated in real time, and an electronic calculator was operated without charging. This work suggests the application potential of the all-in-one HEHM as the next generation of eco-friendly flexible energy sources.

In this article, we study resource optimization issues for hybrid energy harvesting massive multiple-input–multiple-output (MIMO) systems, where renewable energy harvested from surrounding environments is introduced as additional energy supply to the base station (BS) together with the grid power. Our purpose is to maximize system energy efficiency with the preferential use of renewable energy under several practical restrictions, such as limited battery capacity, energy causality, quality-of-service (QoS) requirement, and transmit power constraints. An offline policy is first presented under ideal assumptions, i.e., noncausal knowledge of the channel state information and energy harvesting dynamics are known in advance, which causes it to become a performance upper bound. In particular, the offline policy is designed in an iterative manner with the use of the fractional programming technique. Moreover, inspired by the offline policy, we exploit statistical information to present two practical online algorithms. Specifically, the Markov chain method predicts prospective information through use of the finite-state Markov model, whereas the timing detection scheme focuses only on the resource optimization of the current time slot. Numerical results illustrate that both online algorithms perform closely to the offline policy, which indicates that they can achieve a good tradeoff between performance and implementation complexity.

In this paper, a single-stage rectifier-less boost converter circuit (SSRBC) for piezoelectric energy harvesting from ambient vibration was proposed. The proposed rectifier-less circuit acted as a boost converter to extract energy from a piezoelectric device (PD). It combined the conventional boost, buck-boost methods using two split inductors and single filter capacitor. The proposed integrated circuit topology functioned in both positive and negative half cycles generated by the PD. In the proposed topology, inductors were invigorated by being enveloped with the current, which was produced by the PD through the switches. This facilitated active rectification of ultra-low AC (amplitude < 0.5 VP). Theoretical analysis, control strategies, simulation and experimental study, were presented. The proposed circuit was capable of converting a low amplitude AC voltage of 0.5 VP into 5.1 Vdc. The highest output power extracted by the proposed circuit was 281.1 µW, which outperformed existing circuits. It could potentially facilitate the advancement of vibration-based energy harvesting system for low power demand applications such as sensors, quartz watches and portable charging devices.

For a downlink communication system, we propose a nonorthogonal multiple access scheme with two energy harvesting relays. The base station (BS) transmits the data of both near and far users simultaneously using the superposition coding technique. Two relays alternately amplify and forward the data to the far-user. Each relay can harvest wireless energy from the signals of both the BS and the other transmitting relay, so each relay can achieve more opportunities to accumulate more energy for a higher-quality cooperative relaying. The near-user performs adaptive interference cancelation to retrieve its desired data. Numerical results show that the nonorthogonal scheme greatly outperforms the orthogonal scheme in terms of throughput.

The emerging energy harvesting technology facilitates the development of ubiquitous and everlasting battery-free motion detectors. This paper introduces a robust design of the transient-motion-powered motion detector, which is called ViPSN-pluck. “ViPSN” is the acronym for vibration-powered sensing node while “pluck” stands for the plucking-motion energy harvester. By using a piezo-magneto-elastic structure, ViPSN-pluck can efficiently harvest energy from a transient motion. By properly making good use of this tiny harvested energy, ViPSN-pluck can effectively carry out motion detection and Bluetooth low-energy (BLE) wireless communication. Given the concurrency of mechanical potential energy pre-charging and motion detection, the transient-motion plucking energy harvester used in ViPSN-pluck has the merit of high energy reliability. This unique feature is unprecedented in the solar and RF energy harvesting cases, which might suffer from energy outages under fluctuating irradiance or RF signal strength, respectively. The working principle of ViPSN-pluck, in particular, the dynamic characteristics of the plucking energy harvester and the energy matching between generation and utilization, are discussed in detail to demonstrate the robustness in operation. The cyber-electro-mechanical synergy among the mechanical dynamics, power conditioning circuit, and low-power embedded system is highlighted. The design methodology of ViPSN-pluck provides a valuable reference for the developments of future motion-powered IoT devices.

Green wireless communications have been extensively studied in wireless sensor networks, including the use of new energy, renewable energy, and low power consumption and energy saving technologies for years. In these networks, due to channel fading, insufficient and random energy arrival, some possible bad deployment of sensors, etc. the communication among sensor nodes in a wireless sensor networks (WSNs) will inevitably be affected or even interrupted sometimes, which may result in unacceptable performance in entire network. In order to solve this problem, we propose a wireless sensor network composing of several local subnetworks with amplified forwarding relay and specially designed working time cycle. In this network, we study our resource allocation policies to manage both power and time for throughput maximization. We use deep reinforcement learning (DRL) to develop our resource allocation policies under the model constructed as a Markov decision process for this optimization problem in the subnetwork. We apply actor-critic strategy to find our optimal solution in continuous state and action space and adaptively achieve maximum throughput of this network based on energy harvesting, causal information of battery state and channel gains. The simulation results demonstrate that the proposed transmission policies can produce higher throughput in the local network and finally improve overall system performance in comparison with greedy policy, random policy and conservative policy.

In this paper, we propose a cooperative non-orthogonal multiple access (NOMA)-enabled simultaneous wireless information and power transfer (SWIPT) Internet-of-Things (IoT) networks, where one information source harvests energy from a multi-antennas power beacon (PB) to serve two IoT users via the help of multiple energy-limited relay nodes. To improve the performance of far IoT user, we propose reactive and proactive relay selection protocols together with time-power energy harvesting mechanism under imperfect successive interference cancellation. Closed-form expressions for the outage probability (OP), throughput, and energy efficiency (EE) of the proposed system are obtained, from which the asymptotic analysis for the throughput is also carried out. To further enhance the system performance, we propose a low-complexity method to optimize the outage and throughput performance subject to power allocation, time, and power splitting parameters. Towards real-time configurations in IoT networks, we design a deep learning framework for the sum-throughput and EE predictions with low computation complexity and high accuracy. The influences of antennas setting at PB, time-switching ratio, power-splitting ratio, power allocation factor, and the number of relays on the system OP, throughput, and EE are evaluated and discussed along with numerical results.

We propose a battery-free temperature monitoring device that can be fitted inside the ear for an accurate body temperature measurement of a subject. The proposed application consists of two primary systems: 1) a battery-free temperature sensing ultra-high-frequency radio frequency identification sensory tag and 2) an auxiliary energy harvesting system, which enhances the sensing device's measurement accuracy and precision. The system can record changes in the localized body temperature of authenticated users with an average latency of 501 ms. The assembly demonstrated a temperature average accuracy of ± 0.14 °C operating at 866 MHz. The system performance demonstrated high stability and repeatability of reported temperature measurements. The device's dimension is a form factor that can easily fit in a front shirt pocket, with a wire tethered earbud temperature sensor. The system is developed to make sensor measurements without requiring a battery for the device. Measurements are made remotely as users pass by checkpoints installed throughout a building. The device is a cost-effective solution for monitoring body temperature in work environments.

In this paper, we consider an energy-harvesting (EH) relay network composing of multiple sources, a destination and multiple EH decode-and-forward (DF) relays. The EH relays all equip with a power splitter to divide the received signal power into two parts, one for information decoding and the remaining for signal relaying. The power splitting ratio (PSR) depicts the trade-off between the relaying energy and decoding energy. We propose an optimal power splitting and joint source-relay selection (OPS-JSRS) scheme where the optimal power-splitting ratio is obtained and the best source-relay pair is selected to transmit the message. For the purpose of comparison, we examine the optimal power splitting and round-robin (OPS-RR) scheme and the traditional power splitting and joint source-relay selection (TPS-JSRS) scheme. The exact and asymptotic closed-form expressions of outage probability for OPS-RR, TPS-JSRS and OPS-JSRS schemes are derived. Numerical results show that OPS-JSRS scheme is better than OPS-RR and TPS-JSRS schemes in terms of outage probability, explaining the superiority of the proposed OPS-JSRS scheme. Additionally, outage probability performance of OPS-JSRS scheme can be improved by increasing the number of sources and relays.

Backscatter communication is an emerging paradigm for pervasive connectivity of low-power communication devices. Wirelessly powered backscattering wireless sensor networks (WSNs) become particularly important to meet the upcoming era of the Internet of Things (IoT), which requires the massive deployment of self-sustainable and maintenance-free low-cost sensing and communication devices. This article will introduce the state-of-the-art antenna design and radio frequency (RF) system integration for wirelessly powered backscatter communications, covering both the node and the base unit. We capture the latest development in ultralow-power RF front ends and coding schemes for μW-level backscatter modulators, as well as the latest progress in wireless power transfer (WPT) and energy harvesting (EH) techniques. Newly emerged rectenna system, waveform design, and channel optimization are reviewed in light of the opportunities for adaptively optimizing the WPT/EH efficiency for low-power signals with varying conditions. In addition, advanced device packaging and integration technologies in, e.g., additively manufactured RF components and modules for microwave and millimeter-wave ubiquitous sensing and backscattering energy-autonomous RF structures are reported. Inkjet printing for the sustainable and ultralow-cost fabrication of flexible RF devices and sensors will be reviewed to provide a prospective insight into the future packaging of backscatter communications from the chip-level design to complete system integration. Finally, this article will also address the challenges in fully wireless powered backscatter radio networks and discuss the future directions of backscatter communication in terms of ``Green IoT'' and ``Low Carbon'' smart home, smart city, smart skin, and machine-to-machine (M2M) applications.

The rapid development of wearable sensing and interfacing electronics is facing challenges in sustainability and energy independence. The reliable sustainable operation of such autonomous wearable electronics hinges on the rational integration of energy harvesting and storage modules, as well as their corresponding control and regulation circuitries. Such emerging self-powered wearable systems still lack systematic system-level energy management considerations and are thus limited in efficiency, reliability, and practicality for their targeted use cases. Viewing the scattered wearable energy technologies through the concept of independent microgrids allows us to reassess the goal of establishing a reliable, practical, and energy-economical wearable system. Powered by distributed on-body energy harvesting modules, the continuous operation of wearable devices can thus be realized with their strategic integration with energy storage managed by the decentralized, hierarchical control system. This Perspective discusses the vision of a wearable microgrid, based on a judicious scenario-specific selection of harvesting and storage modules, with commensurate performance, towards the rational design of practical wearable electronic systems with high energy autonomy and reliability. The energy supply via different sources and power demands of various wearable applications are examined for determining appropriate energy reserve, attainable functionalities, and suitable operation modes, along with key considerations in device form-factors for maximizing system efficiency. By applying the concept of a microgrid on miniaturized self-powered systems for wearables, we propose three system-level design guidelines - commensurate energy rating, complimentary device characteristics, and compatible form factors - towards the future development of reliable, self-sustainable on-body systems and autonomous implantable, ingestible, or small mobile devices. We conclude by discussing the prospects for developing more efficient and sustainable wearable microgrids for higher power applications, through accurate and smart energy budgeting and regulation involving artificial intelligence and advanced algorithms towards dynamic data-driven prediction of rapidly changing power supply and demands.

International audience; This paper presents an ultra-flexible piezoelectric air flow energy harvester capable of powering a wireless sensor. The method to easily adapt the aero-electric generator to the wind is presented. In the wind tunnel, different configurations have been tested to determine the best one for energy harvesting at low wind speed. In particular, the galloping configuration, with the addition of a bluff body at the free end of the cantilever which allows to improve the performance of the micro-generator by coupling the vibrations induced by the vortices and the galloping phenomena. In this study, we also present a method to optimize the energy harvesting without increasing the volume of the device. The effects of mechanical and electrical coupling of several generators on the performance of energy harvesting are presented. Thus, with the electrical parallel coupling of four generators, we obtained a maximum power of 60 mW instead of 30 mW with two generators for a wind speed of about 6 m/s. The mechanical coupling of the micro-generators allowed the device to keep the same volume (z540 cm3), however the threshold wind speed to increase (>6 m/s). The harvested energy was then used to operate a wireless sensor.

Wireless powered communication networks (WPCNs) will act as a major enabler of massive machine type communications (MTCs), which is a major service domain for 5G and beyond systems. The MTC networks will be deployed by using low-power transceivers with finite discrete configurations. This paper considers minimum length scheduling problem for full-duplex WPCNs, where users transmit information to a hybrid access point at a rate chosen from a finite set of discrete-rate levels. The optimization problem considers energy causality, data and maximum transmit power constraints, and is proven to be NP-hard. As a solution strategy, we define the minimum length scheduling (MLS) slot, which is slot of minimum transmission completion time while starting transmission at anytime after the decision time. We solve the problem optimally for a given transmission order based on the optimality analysis of MLS slot. For the general problem, we categorize the problem based on whether the MLS slots of users overlap over time. We propose optimal algorithm for non-overlapping scenario by allocating the MLS slots, and a polynomial-time heuristic algorithm for overlapping scenario by allocating the transmission slot to the user with earliest MLS slot. Through simulations, we demonstrate significant gains of scheduling and discrete rate allocation., Scientific and Technological Research Council of Turkey (TÜBİTAK)

Energy harvesting (EH) powered sensor nodes can achieve theoretically unlimited lifetime by scavenging energy from ambient power sources, such as radio frequency (RF) and kinetic energy. The nodes can collect and transmit data wirelessly with the harvested energy. However, the transmission between two sensor nodes is successful only when both nodes have enough energy at the same time. While the receiver can be actively listening, it may deplete the energy long before the sender has accumulated enough energy. Thus, given the scarce, unpredictable, and unevenly distributed energy among sensor nodes, it is challenging to ensure efficient data transmission between them. To address this challenge, we propose a sensor node architecture with multiple radios, each with different energy consumption on the sender and receiver. A node can be put into sleep when charged up and wakes up for communication when it infers that both nodes have enough energy based on its observations. What is more, two nodes can cooperatively and dynamically select different radios according to the stored energy and historical information to maximize the data throughput. To achieve cooperative communication adaptively, the communication procedure is modeled as a cooperative Markov game with partial observability on each node, and multi-agent reinforcement learning (MARL) is employed to achieve the best results. Experimental results on hardware prototype and by simulation show that the proposed approaches achieve up to 89.1% of the optimal throughput and significantly outperform other online algorithms.

A backpack energy harvester converts mechanical energy associated with the oscillation of the backpack during human walking, into electric energy. It can be a very promising solution for supplying portable devices, especially in outdoor activities, disaster relief, and military applications. In this article, a backpack energy harvesting system that is able to self-adapt its operating condition to maximize the extracted power while supplying a dc load is presented and studied, analytically and experimentally. It is based on a mechanical motion rectifier that converts the up-and-down oscillation of the backpack into a unidirectional rotation of a dc generator. The generator output voltage is regulated by a power electronic interface implementing a maximum power point tracking technique to maximize the extracted power. Experimental results confirm the tracking ability of the proposed system and show the advantages with respect to other wearable energy harvesting systems published in the literature.

The ability of thermoelectric (TE) materials to convert thermal energy to electricity and vice versa highlights them as a promising candidate for sustainable energy applications. Despite considerable increases in the figure of merit zT of thermoelectric materials in the past two decades, there is still a prominent need to develop scalable synthesis and flexible manufacturing processes to convert high-efficiency materials into high-performance devices. Scalable printing techniques provide a versatile solution to not only fabricate both inorganic and organic TE materials with fine control over the compositions and microstructures, but also manufacture thermoelectric devices with optimized geometric and structural designs that lead to improved efficiency and system-level performances. In this review, we aim to provide a comprehensive framework of printing thermoelectric materials and devices by including recent breakthroughs and relevant discussions on TE materials chemistry, ink formulation, flexible or conformable device design, and processing strategies, with an emphasis on additive manufacturing techniques. In addition, we review recent innovations in the flexible, conformal, and stretchable device architectures and highlight state-of-the-art applications of these TE devices in energy harvesting and thermal management. Perspectives of emerging research opportunities and future directions are also discussed. While this review centers on thermoelectrics, the fundamental ink chemistry and printing processes possess the potential for applications to a broad range of energy, thermal and electronic devices.

Continuous advances in ultralow-power electronics are a fundamental driving force of developing far-field wireless power harvesting techniques, which generally harnesses low/ambient energy in free space or dedicated wireless power from a power base station. This article reviews recent developments and technology trends in far-field (radiative) wireless power harvesting, including modeling of rectification process inside nonlinear devices, insights into rectenna system design, and demonstrations of emerging applications. The rectification process inside nonlinear devices will be explored, upon which a device selection guideline is provided to help quickly identify suitable devices. Then, the optimization of rectenna design is discussed to realize efficiency enhancement at a limited input power level. Since far-field wireless power harvesting has become a critical enabling technology for battery-free Internet of Things, a series of promising applications is demonstrated in this article to highlight the challenges and opportunities in the field.

Summary As an emerging energy-harvesting technology, enhancing the output performance of triboelectric nanogenerators (TENGs) is crucial for its practical application. Here, a dielectric enhancement effect is firstly proposed to improve the output performance of TENGs. It is found that the dielectric enhancement layer greatly elevates the triboelectrification effect, and the enhanced performance is verified by all types of TENGs. Thus, the output power of alternative current TENG (AC-TENG) and direct current TENG (DC-TENG) realizes 8.5-fold and 2.6-fold enhancement of normal devices, respectively. Besides this, the dielectric enhancement layer with leakage performance is proven to be necessary for DC-TENG to produce a continuous output. Our work provides a simple and universal strategy for elevating the performance of all types of TENGs, which is beneficial to the promotion of large-scale energy harvesting by TENGs.

The study presents the pyroelectric performance improvement by employing exhaust emissions from automobiles. Electric outputs through the material BaSn0.05Ti0.95O3 are recorded after subjecting the surface of the sample for heating under infrared (IR) lamp and flowing water. The thickness of the automobile exhaust ink was nearly 35 µm on the sample surface. Observations show significant improvements with open circuit voltage increase to five times, electric current enhances upto six times across the resistor of 10 Ω and nearly 17 times increment in energy harvested. Peak values of open circuit voltage obtained were 0.3 and 1.2 V for uncoated as well as coated samples respectively. The electric current for the heating & cooling cycle represents peak value of 1.47 µA when compared with uncoated sample with a value of 0.24 µA. Moreover, energy stored across capacitor of10 µF founds an increment from 1.4 µJ for uncoated sample to 23.10 µJ for coated sample. The study proposes effective utilization of harmful automobile exhaust and harvesting of energy for low power electronics. Therefore this study systematically investigates the pyroelectric energy potential of BaSn0.05Ti0.95O3 ceramics by using automobile emission and compares it with similar class of materials.

A comprehensive review of metamaterials and metasurfaces for wireless power transfer (WPT) and wireless energy harvesting (WEH) is presented in this article. According to the features of the electromagnetic field from the source to the receiver, WPT is divided into nonradiative near-field technology and radiative (near and far-field) technologies. Many different and important designs are reviewed and compared. It is shown that metamaterials and metasurfaces can significantly improve the power transfer efficiency and operational distance for WPT systems. They can also improve the energy conversion efficiency of wireless energy harvesters by making the reception less sensitive to incident wave angle and polarization. A rectenna is a critical element for both WPT and WEH. It is shown that metamaterial-based rectennas can achieve a higher RF to dc conversion efficiency. Furthermore, metamaterials can also be used as either parasitic elements or loading components to improve WEH performance in terms of circuit size, beamwidth, and conversion efficiency. Future development directions and opportunities of metamaterials and metasurfaces for WPT and WEH are also proposed in this article.

The design of an ambient radio frequency (RF) energy harvesting system is introduced to replace the battery of the mass Internet-of-Things devices. This system can achieve high sensitivity with high efficiency over a wide input power range by optimizing the differential-drive cross-coupled (DDCC) rectifier and the load. The impedance of the dual-band four-port loop antenna array is directly conjugated to match with the rectifier, which reduces insertion loss of the matching network to improve efficiency. At 915 and 945 MHz for ISM and GSM bands, the rectenna can achieve high sensitivity of -30 dBm with 22% and 24% efficiency, high efficiency of 65% and 48% with -20-dBm input power, and a wide input power range from -30 to -18 dBm with 22-65% and 24-48% efficiency. The dual-band design explores the frequency diversity to harvest more RF energy from the environment, while the cross-shaped antenna array utilizes the space diversity to harvest RF energy from different directions with a compact size of 0.15λ x 0.15λ per antenna element (where λ is the free space wavelength at 915 MHz). This new harvesting system can provide output dc power of 21.4 and 2.95 μW in real-world outdoor and indoor ambient environments, respectively.

Energy harvesting systems powered by renewable energy sources employ hybrid volatile-nonvolatile memory to enhance energy efficiency and forward progress. These systems have unreliable power sources and energy buffers with limited capacity, so they complete long-running applications across multiple power outages. However, a power outage might cause data inconsistency, because the data in nonvolatile memories are persistent, while the data in volatile memories are unsteady. State of the art studies proposed various memory architectures and compiler-based techniques to tackle the data inconsistency in these systems. These approaches impose too many unnecessary check-points on the system to avoid data inconsistency. These studies did not consider the effect of cache memory to mask and postpone the imposed check-points on the system for the sake of consistency. In this paper, we utilize the cache memory and propose PROWL, a consistency aware cache replacement policy to avoid data inconsistency with fewer check-points. The results show that PROWL has by up to 85% fewer check-points compare to the state of the art approaches, and PROWL improves the average response time of the system by up to 65%.

Purpose The purpose of this study is to monitor the surface cooling of the photovoltaic (PV) panel and the effect of the dust accumulated on the panel surface on the electrical efficiency remotely and instantaneously. Design/methodology/approach An autonomous system has been designed that can measure and record the PV surface temperature, the amount of dust on the surface, current, voltage and power values at certain intervals. It can also perform surface cooling and cleaning with water cycle when the temperature and dust amount reach certain threshold values and transmit these values to the user via global system for mobile communications module, Bluetooth module and graphically with a touchscreen liquid crystal display panel. Thus, it is aimed to benefit from PV at the maximum level, and it was installed in Kahramanmaras Sütçü Imam University Faculty of Engineering and Architecture. Findings An increase in power was observed for PV surface cooling and surface dust removal by 3.78% and 45.99%, respectively. Originality/value This system is of vital importance in terms of time and energy-saving, especially for solar plants far from the city center, which are difficult to access because of climatic conditions. In other hand for future studies, it is foreseen that more efficiency gains can be achieved by using artificial intelligence and image processing techniques.

Large pyroelectric and energy harvesting properties have been attracting increasing attentions due to the practical applications in infrared detectors and energy harvesting technologies. Ferroelectric-antiferroelectric (FE-AFE) phase transitions are usually accompanied by a sharp drop in polarization, which will lead to excellent pyroelectric properties and energy harvesting density. Therefore, FE-AFE phase boundary design is an effective strategy to develop new pyroelectric materials. In this paper, Pb(Lu1/2Nb1/2)O3-PbTiO3 (PLN-PT) single crystals with FE-AFE phase transitions were obtained by molten salt growth method. The temperature-induced FE-AFE phase transition was verified by temperature-dependent macrodomain structure, DSC curves and dielectric properties. Obviously, PLN-PT crystals display excellent peak pyroelectric coefficient (∼6.8 μC/(cm2·K)) with a maximum depolarization temperature of 118 °C. Meanwhile, the pyroelectric energy harvesting density is as high as 2.62 J/cm3, which is much higher than other pyroelectric materials. The results reveal that the PLN-PT crystal is a promising candidate for infrared detectors and energy harvesting devices.

In this paper, we investigate the physical-layer security for an Internet of Things (IoT) relaying network employing non-orthogonal multiple access (NOMA) in the context of non-linear energy harvesting. In particular, a power-constrained source transmits its confidential information to a destination via an IoT device, which first decodes the received signal and then forwards the decoded data together with its own information using the NOMA technique to their respective destinations, while an eavesdropper is overhearing this transmission. Considering the scenario that both the power-constrained source and the IoT device are assumed to work under non-linear energy harvesting modes, and are capable of harvesting energy from a power beacon with a time switching protocol, both analytical and asymptotic expressions for secrecy outage probability as well as the analytical expression for the probability of strictly positive secrecy capacity are derived. In addition, those expressions are also verified with Monte-Carlo simulations.

There has been a significant disruption in the energy market because of the pandemic. Now the focus is shifting towards investing more in renewable energy to address the present health and energy crisis. Wind power has gained special prominence in our clean energy transition as wind energy is the easiest to harvest, most efficient resources, and lowest carbon emitter among the available technologies. The prime focus of this study is towards implementing an array configuration of Savonius turbines beside the train track to maximize the power production. A model is set up on OpenFOAM platform and studied for the different arrangements of turbine clusters. The effect of energy production by the series of turbines was assessed by varying distance among turbines in a staggered or inline manner and the location from the train as well. A systematic characterization of the optimum Savonius turbine cluster in a railway tunnel, which is relatively an unexplored area in the energy harvesting community, has been taken up in this study. It is exciting to note that our computer-oriented result matches well with the benchmark solution and proved to be a viable green energy resource that can possibly erase the energy crisis at remote places.

Converting mechanical deformation from surrounding environment into detectable electrical signals remains one of the most attractive fields due to its potential applications in sustainable energy harvesting, self-powered sensors, and others. Presently, deformation energy is harvested by generating voltage/current through bending/twisting of piezoelectric materials, but its recyclability is limited in number. In contrast, polarization is generated in all known insulators/semiconductors due to elastic strain gradient, which offers unique electromechanical coupling and in turn, could generate significant potential differences to drive charge transfer. Here, we demonstrate that extremely high direct current with density of 28 × 106 A m−2 is generated without need of any external power supply by applying pointed force using conductive-atomic force microscope (cAFM) tip on multilayer graphene/substrate (SiO2, Si, glass). Further, the ramp-dependent time-resolved current is measured at a localized point, which indicates that pointed force-induced flexoelectric potential differences are the main driving factor to utilize mechanoelectrical coupling and in turn generate high current density. This research work provides a new strategy to utilize the flexoelectric effect to utilize electromechanical coupling to generate giant energy harvesting, which will have a potential impact on the various multiple fields including smart devices, materials, and even a fundamental understanding of physics.

In wireless multi-hop networks, a fundamental problem is to disseminate continuous data traffic from a source node to all other network nodes, which is known as the broadcast problem. Such a problem becomes even more complicated in wireless multi-hop networks with energy-harvesting capabilities at nodes when facing the interaction between stochastics of traffic arrivals at the source and randomness of energy-harvesting process at nodes. In such networks, the energy consumable at a node cannot exceed the amount of the energy harvested at the node. In this paper, we investigate the throughput-optimal broadcast problem in time-varying directed acyclic wireless multi-hop networks with such energy harvesting constraints. The topologies of such networks change dynamically with time while satisfying the directed acyclic property and the energy arrival time and harvested amount at a node are random, which causes the consumable energy in each time slot to fluctuate with time. Existing throughput-optimal broadcast algorithms did not consider such energy-harvesting constraints in their designs and therefore their throughput-optimal properties do not hold anymore in such a network. In this paper, we characterize the energy-harvesting uncertainties at nodes by using time-varying per-slot-based supportable transmission rates of wireless links. We consider the time-varying property of supportable link transmission rates caused by energy-harvesting dynamics in the per-slot transmission scheduling and propose an online max-weight broadcast algorithm. We derive a tight upper bound of broadcast capacity of the wireless networks under study in this paper and further prove that our proposed algorithm is throughput-optimal. We evaluate the throughput and latency performance of the proposed algorithm by simulations and the simulation results affirm our theoretical analysis.

The Internet of Things (IoT) is an interface with the physical world that usually operates in random-sparse-event (RSE) scenarios. This article discusses main challenges of IoT chips: power consumption, power supply, artificial intelligence (AI), small-signal acquisition, and evaluation criteria. To overcome these challenges, many works recently aimed at IoT system design have emerged. This work reviews the architecture and circuit innovations that have contributed to IoT developments. This paper does not cover security of IoT. Event-driven architectures and nonuniform sampling ADCs significantly reduce the long-term average power. Besides, embedding AI engines in IoT nodes (AIoT) is one critical trend. The computing-in-memory technique improves the energy efficiency of the AI engine. Asynchronous spike neural networks (ASNNs) AI engines show low power potential. In addition to data processing, small-signal acquisition is also critical. The charge-domain analog-front-end (AFE) techniques such as floating inverter-based amplifiers improve energy efficiency. In addition to the above low power and high energy efficiency technologies, energy harvesting can also enhance the lifetime of AIoT devices. This article discusses recent ambient RF and natural energy harvesting approaches and high-efficiency DC-DC with a wide load range. Finally, novel evaluation criteria are introduced to establish benchmark standards for AIoT chips.