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Abstract This article proposes a polarization-insensitive compact Metamaterial (MM) energy harvester that can be used seamlessly in the S-band and C-band frequencies. It is important to focus on the limitations of many current designs of harvesters, which need to be overcome. The existing devices are large and often operate in a single frequency band, while their Energy Harvesting (EH) efficiency is low. The proposed harvester solves these problems using smart technology, using a rectangle strip with two gaps, each containing 50 Ω resistors for efficient energy collecting. Also, four hexagonal ring resonators are embedded into the cross-dumbbell configuration, connecting them with strip lines. Smaller rectangular rings surround these hexagonal rings, each with gaps labelled g1–g4. Despite its sophisticated design, the size of this harvester is (10 × 10) mm2 only. This harvester operates at frequencies of 3.5 GHz and 5.5 GHz, demonstrating remarkable absorption responses across varying polarizations and incident angles in both transverse electric (TE) and transverse magnetic (TM) modes. The simulation results indicated impressive energy harvesting efficiencies of 97% at 3.5 GHz and 98% at 5.5 GHz. In addition, experiments in an anechoic chamber with a 3 × 3 array (30 × 30) mm2 were used to confirm the efficiencies empirically. The simulated and measured results showed a strong correlation, confirming the reliability of the proposed design. The proposed MM harvester is distinguished by its high efficiency, polarization-insensitive behaviour, and compactness, making it very promising for many applications in EH.

Abstract Energy harvesting from vibrations is a popular research topic. However, it is difficult to change the values of its dynamic stiffness characteristics during the operation of device. This paper analyzes the nonlinear dynamical behavior and energy harvesting performance of an energy harvesting device with a gear unit and an inertial amplifier. The Melnikov method is used to discriminate the chaos behavior of the system and is illustrated by numerical simulations. Chaotic dynamics analysis provides a simplified analytical idea that offers more insight into the performance of this energy harvesting device. In addition, the basins of attraction of the coexistence solution of the system are plotted, and the trajectory and energy harvesting efficiency of the system are analyzed for changes in the initial value. The results show that the device has the convenience to change the form and efficiency of system energy harvesting. The theory of Melnikov functions recognizes the presence of chaos and can provide solutions for the parameterization of the system. The choice of initial value greatly affects the energy harvesting efficiency.

Abstract In this study, we achieved energy localization and amplification of flexural vibrations by utilizing the defect mode of plate-attachable locally resonant metamaterials, thereby realizing compact and low-frequency vibration energy suppression and energy harvesting with enhanced output performance. We designed a cantilever-based metamaterial unit cell to induce local resonance inside a periodic supercell structure and form a bandgap within the targeted low-frequency range of 300–450 Hz. Subsequently, a defect area was created by removing some unit cells to break the periodicity inside the metamaterial, which led to the isolation and localization of the vibration energy. This localized vibration energy was simultaneously converted into electrical energy by a piezoelectric energy harvester coupled with a metamaterial inside the defect area. Consequently, a substantially enhanced energy harvesting output power was achieved at 360 Hz, which was 43-times higher than that of a bare plate without metamaterials. The proposed local resonant metamaterial offers a useful and multifunctional platform with the capability of vibration energy isolation and harvesting, while exhibiting easy handling via attachable designs that can be tailored in the low-frequency regime.

Abstract With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance.

Research conducted around the world shows that energy harvesting (EH) systems can be used in modern vehicles powered by combustion, hybrid or electric engines. The efficiency of modern combustion engines is about 40%, the rest of the energy is lost and can be recovered to some extent. Therefore, the search is ongoing for systems that will use this part of the energy to power specific systems or micro-sensors installed in the vehicle. The article presents the possibilities of energy recovery from such vehicle systems as: energy recovered during braking, damping energy in the vehicle suspension, energy recovery from the exhaust system of an internal combustion engine and energy from the vibrations of the internal combustion engine. Based on the analysis of the literature on the presented research of various scientific centers and the author's experiment, it can be concluded that there is a huge potential for obtaining thermal energy from the engine exhaust system and the vehicle suspension system. A field that has not been explored much, but according to the authors also has energy potential, is energy recovery from the combustion engine suspension system in the vehicle's engine compartment. Preliminary research shows the possibility of mounting the energy recovery system in the engine compartment and the potential possibility of obtaining electricity in certain operating states of the combustion engine.

Cooperative communication through energy harvested relays in Cognitive Internet of Things (CIoT) has been envisioned as a promising solution to support massive connectivity of Cognitive Radio (CR) based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems. In this work, a cooperative CIoT system is contemplated, in which a source acts as a satellite, communicating with multiple CIoT devices over numerous relays. Unmanned Aerial Vehicles (UAVs) are used as relays, which are equipped with onboard Energy Harvesting (EH) facility. We adopted a Power Splitting (PS) method for EH at relays, which are harvested from the Radio frequency (RF) signals. In conjunction with this, the Decode and Forward (DF) relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices. We developed a Multi-Objective Optimization (MOO) framework for joint optimization of source power allocation, CIoT device selection, UAV relay assignment, and PS ratio determination. We formulated three objectives: maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission. The MOO formulation is a Mixed-Integer Non-Linear Programming (MINLP) problem, which is challenging to solve. To address the joint optimization problem for an epsilon optimal solution, an Outer Approximation Algorithm (OAA) is proposed with reduced complexity. The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search (NOMAD) algorithm.

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer (SWIPT)-based multi-relay network with a direct link. To achieve high throughput in the network, a novel protocol is first developed, in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission (SRS-CT) mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes (RCs). Then, under this protocol, an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode. The formulated problem is difficult to solve because not only does the noncausal Channel State Information (CSI) cause the problem to be stochastic, but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation. Assuming that noncausal CSI is available, the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming, where the complicated energy state evolution issue is addressed by a layered optimization method. Then, based on a finite-state Markov channel model and assuming that CSI statistical properties are known, the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case. Finally, a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties. The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40% throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

Energy harvesting from external Ultra-low frequency vibrations is currently attracting a lot of attention. However, for the same system, it is difficult to satisfy the need for more efficient energy harvesting in a variety of external environments. Accordingly, an adjustable gearing device connected to the energy harvesting system is used herein for adapting energy harvesting to a wide range of external environments. The device uses four symmetrical inclined springs. One end of the springs is connected to a gear and the other end to a mass element. The geometrical parameters of the system can be varied by rotating the gears, thus varying the dynamic stiffness of the system. The kinetic equations of the system are derived and their nonlinear terms are Taylor-expanded. The amplitude-frequency response curve of the system is obtained by solving using the harmonic balance method. Multi-color plots of RMS values of induced voltage and electric power are obtained using the fourth-order Runge-Kutta method. The results show that the device has excellent adjustable performance. Adjusting the rotation angle of the gears can change the soft and hard characteristics of the system's dynamic stiffness and the intrinsic frequency, thus improving the system's energy harvesting performance in different environments.

Energy harvesting is a clean technique for obtaining electrical energy from environmental energy. Mechanical vibrations are an energy source that can be used to produce electricity using piezoelectric energy harvesters. Vibrations and wind in bridges have the potential to produce clean energy that can be employed to supply energy to electronic devices with low consumption. The purpose of this paper was to validate the functioning of an energy harvester and test the electrical power generation potential of a system based on the oscillation of a rod with a tip mass to stimulate piezoelectric transducers by impact. The obtained results showed the electric energy productions for different test conditions. Experimentally, the proposed structure produced 0.337 µJ of energy after 14 s of testing. In addition, after one hour of operation, an estimated production of 10.4 mJ was obtained, considering four stacks of 25 piezoelectric disks each when periodic impacts of 50 N at 5.7 Hz stimulated the transducers. In future work, we will focus on taking advantage of the vibrations produced in the proposed structure induced by the mechanical vibration of bridges and vortex-induced vibration (VIV) through interaction with wind to produce clean energy that is useful for low-power applications.

The development of energy recovery systems in vehicles is a form of synergy between energy efficiency and renewable energy to overcome the energy crisis and global warming problems. This paper addresses such challenges by introducing a novel design of a piezoelectric energy harvester (PEH) for a vehicle suspension system. The PEH is designed to capture the linear vibration of the suspension system subjected to road surface roughness and move on uniform bridges. The vibration is amplified by a pressurized liquid cylinder-piston mechanism which deforms the piezoelectric bar to produce electric power. An additional novel mechanism in the form of a piezoelectric protector is also proposed to avoid physical damage due to excessive unidirectional compressive force as a result of an unpredictable uneven road. Given the key design parameters, the electric power can be harvested up to 67.5 W for a PEH with a span of 150 m of the bridge, a velocity of 40 m/s, and a vehicle mass of 2,691.6 kg.

Abstract Fuel cell vehicles (FCVs) are gaining significance due to their potential to reduce greenhouse gas emissions and dependence on fossil fuels. Their efficient fuel cell cycle makes them ideal for last-mile transportation, offering zero emissions and longer range compared to battery electric vehicles. Additionally, the generation of electricity through fuel cell stacks is becoming increasingly popular, providing a clean energy source for various applications. This paper focuses on utilizing the energy from fuel cycle bicycles when it's not in use and feeding it into the home DC grid. To achieve this, a dual-phase DC to DC converter is proposed to boost stack voltage and integrate with the 24 V DC home grid system. The converter design is simulated using the PSIM platform and tested in a hardware-in-the-loop (HIL) environment with real-time simulation capabilities.

Smart renewable energy harvesting has been implemented from hybrid sources such as solar and wind. The wireless sensor node is created for monitoring surface water. In the intelligent building, electrical energy is harvested from the hybrid source of solar and wind energy. The source energy was selected for the harvesting process by using a fuzzy controller. In this proposed method, piezo-electric reverse electro-wetting on di-electric energy harvesting is proposed where constant DC voltage is generated by a rectifier. A DC-DC converter is designed to power up the remote read-out sensor. The produced charge is transformed by a charge amplifier with the proportion of output voltage that is delivered to the wireless receiver. The harvested DC voltage varies with the temperature and external environmental effect. In our work, we obtained 6 × 10−3 W/m2 of voltage and this harvested energy is monitored using the Internet of Things (IoT) by the proposed EHOR (Energy Harvested Optimized Routing) algorithm.

In recent years, the energy requirements for devices in internet of things (IoT) applications have increased, making energy harvesting (EH) technology an important way to alleviate the energy shortage problem in edge computing and extend the battery life of devices. However, when there was insufficient renewable energy in the environment, the depletion of device power can cause task interruption and affect the performance of IoT. To solve this problem, a task offloading framework that combined energy harvesting and device-to-device (D2D) communication technology was proposed, using a deep reinforcement learning (DRL)-based edge collaborative offloading computing scheme to make autonomous decisions and solve resource allocation problems using simulated annealing algorithms to minimize the total cost of system operation. Simulation results on stable and extreme energy environments show that the proposed scheme can run stably and cost-effectively in single-user multiple-device scenarios.

Abstract With the rapid development of digital technologies such as intelligent control and information communication, digitization has gradually become an inevitable trend to promote technology innovation and industrial upgrading for the power grid. As the basis of digital technology, digital sensing technology will gradually penetrate all aspects of the power system for comprehensive perception and high operational reliability. First, this article introduces the application status and technical requirements of power intelligent sensor technology in various aspects of the power system, including the generation, transmission, transformation, distribution, and consumption of electricity. Next, domestic and foreign scholars' latest research achievements in power sensing technology are described from three major aspects, that is, optical fiber sensing technology, MEMS sensing technology, and sensor self‐powered technology. Finally, future challenges for the electric power intelligent sensors are discussed and an outlook of future widespread application in the clean, safe, and efficient digital power grid is provided.

Energy harvesting from human body kinetics is a crucial issue. The primary challenge lies in designing and optimizing the energy converter. This paper presents an analysis of energy harvesting using three variants of electromagnetic harvesters designed for backpack integration. The first harvester comprises a single levitating magnet within a coil. The second concept involves a specially designed oscillating magnet consisting of two divided magnets with a separator. The third harvester variant utilizes two levitating magnets within the coil. The results indicate that, for harmonic excitation, the harvested power is the highest for the classical harvester with a single oscillating magnet. However, when integrated into a backpack, the concept of two levitating magnets proves to be more effective in lower speed ranges.

Green energy harvesting devices are potential sustainable power sources for self-powered sensors, electronics, and the Internet of Things. Triboelectric nanogenerators (TENGs) based on natural polymers and waste materials can harvest green energy from vibration sources to convert it into electrical energy. These nanogenerators could substitute conventional electrochemical batteries to power future smart sensors and electronic devices without contaminating our ambient. Herein, we present a novel portable triboelectric nanogenerator formed by a waste corn husk and a recycled polystyrene (PS) plate as triboelectric layers. This nanogenerator has a compact and lightweight structure developed by a low-cost and eco-friendly fabrication process. This nanogenerator can convert vibrational kinetic energy into electrical energy, achieving a power density of 670.5 mW∙m−2 with a 51.9 MΩ load resistance and operating at 14 Hz. This portable nanogenerator includes simple signal processing and it can power an array of 472 commercial blue LEDs, a digital calculator, and a stopwatch. The output voltage of this nanogenerator is stable even after 25,211 operating cycles at 14 Hz with 25 mm of separation distance between triboelectric layers. The proposed nanogenerator has potential applications to power small electronic devices and sensors using vibrational kinetic energy from the environment.

Thermoelectric generators (TEGs) harness temperature differences to produce electricity and hold promise for diverse industrial applications. However, their limited conversion efficiency casts doubt on their role in achieving energy independence. This study introduces an advanced technique that exploits temperature gradients in water pipes, utilizing supplementary TEGs to augment power generation. This method maintains a stable temperature gradient for TEG operation. Additionally, TEG power output can be efficiently modulated via flow control. In the feasibility evaluation for residential settings, the temperature fluctuations across each system unit were analyzed. In the active system, the chosen sites for TEG integration were units equipped to manage heat transfer using working fluids. The inlet and outlet temperatures were calculated for photovoltaic-thermal (PVT) systems, ground heat exchangers (GHEs), and heat storage tanks (HSTs). The electricity produced by the TEGs was benchmarked against their conversion efficiency, zT. The results indicated that the TEGs yielded 10.95 kWh of electricity when systematically implemented in each unit. To realize a zero-energy building, an area of 64.5 m2 per unit is necessitated for TEG deployment, given a zT value of 1.

Abstract Metal‐organic frameworks (MOFs) are nanomaterials with engineered chemical structures, offering remarkable properties. However, their limited film‐formation capability hinders their integration into triboelectric nanogenerators (TENGs). This study proposes a simple yet effective solution to overcome this challenge by employing electrospinning techniques to integrate the zeolitic imidazolate framework (ZIF‐8) into an easy‐to‐use nanofibrous mat. ZIF‐8 has high surface potential, a unique cubical structure, and an easy fabrication process that makes it an ideal material for TENGs. By incorporating ZIF‐8 into the electrospinning solution, significant improvements are achieved in the electropositivity of the resulting nanofibers. It leads to notable changes in the shape, morphology, and roughness of electrospun fibers, consequently enhancing the overall performance of the TENG. The results indicate that utilizing the ZIF‐based electrospun mat as a tribo‐positive material can increase transferred charges between electrodes by more than 100%. Utilizing the MOF‐based nanofibrous mat, this study also introduces a novel rotary TENG that works based on a mode of TENG operation called rolling mode. The reliable charge generation by the proposed rolling system reveals that this mode of TENG operation could be a superb alternative for traditional TENG modes, like contact/separation or sliding, which cause high levels of mechanical stress due to harsh physical impact or friction.

Abstract Water motion‐induced energy harvesting has emerged as a prominent means of facilitating renewable electricity from the interaction between nanostructured materials and water over the past decade. Despite the growing interest, comprehension of the intricate solid–liquid interfacial phenomena related to solid state physics remains elusive and serves as a hindrance to enhancing energy harvesting efficiency up to the practical level. Herein, the study introduces the energy harvester by utilizing inversion on the majority charge carrier in graphene materials upon interaction with water molecules. Specifically, various metal electrode configurations are employed on reduced graphene oxide (rGO) to unravel its distinctive charge carriers that experience the inversion in semiconductor type upon water contact, and exploit this characteristic to leverage the efficacy of generated electricity. Through the strategic arrangement of the metal electrodes on rGO membrane, the open‐circuit voltage (Voc) and short‐circuit current (Isc) have exhibited a remarkable augmentation, reaching 1.05 V and 31.6 µA, respectively. The demonstration of effectively tailoring carrier dynamics via electrode configuration expands the practicality by achieving high power density and elucidating how the water‐induced carrier density modulation occurs in 2D nanomaterials.

Abstract Mechanical energy harvesters have recently emerged as promising options for self‐powering sensors and small electronic devices. In this work, aluminum ferrite (AlFeO3)/PVDF hybrid perovskite electrospun nanofiber‐based tribo‐enhanced piezoelectric nanogenerators (TPENGs) are developed for energy harvesting. The as‐fabricated TPENG achieves an average voltage output of 52.3 V and an average current output of 1.23 µA. Additionally, the power density of the TPENG is calculated to be 0.085 W.m−2 at an 80 MΩ external resistance load. A 3D‐printed device is fabricated, containing nylon fabric (tribo‐positive) as a rotor attached to printed fins, while six (AlFeO3)/PVDF hybrid perovskite electrospun nanofiber piezoelectric nanogenerators (PENGs) wrapped with Kapton tape (tribo‐negative) serve as the stator. The three printed fins of the device are moved by a string‐based pulley, generating an open circuit voltage of 200 V and a short circuit current of 4.5 µA. The as‐fabricated 3D‐printed device with TPENGs is used to power small electronics (e.g., LEDs and watch) and an exercise setup, allowing patients to generate power by pulling the attached string, thereby estimating the level of impairment. Integrating energy harvesting into rehabilitation motivates patients to move impaired body parts, enhancing TPENG's application in healthcare as a practical and engaging tool for patient rehabilitation.

Dynamic vibration absorbers (DVAs) have been widely employed in vibration suppression applications for decades. While DVAs offer an effective solution, they are limited by the need for a high mass ratio between the DVA and the primary system to achieve significant vibration attenuation. To overcome this, researchers have introduced lever mechanisms, allowing for enhanced vibration suppression without increasing the mass ratio. However, levers, commonly used as amplification mechanisms, suffer from high inertia and limited amplification, particularly in larger applications. Another limitation is when DVAs are employed for energy harvesting as a secondary objective, they exhibit high sensitivity to system parameter variations, requiring extensive optimization. Various optimization techniques have been applied to DVAs for multi-objective optimization, including fixed-point theory, which is complex and requires intensive mathematical derivation, and simple metaheuristic techniques such as genetic algorithms (GA). This study proposes four novel DVAs using a hydraulic amplifier (HA) to address the limitations of traditional lever mechanisms and a mechanical inerter to improve the vibration damping. Also, multi-objective optimization was performed using particle swarm optimization (PSO) which is considered innovative in this application and compared with commonly used genetic algorithms (GA). The governing equations were derived using Newton’s second law and solved numerically with the Runge-Kutta method. An AI-based approach was utilized for HA design. The results show that integrating HA and mechanical inerters significantly enhances vibration attenuation and broadens the frequency response. Additionally, the location of the mechanical inerter is critical in reducing vibration amplitude. Also, the multi-objective PSO outperforms GA in solution diversity and quality. The proposed integration of HA in DVAs offers potential applications across various engineering fields.

This work presents an economical IoT weather station with energy-efficient capabilities. It offers a multi-sensor platform, with balanced functionality and power optimization that ensures an extended- wireless range. The developed system features diverse sensors measuring temperature, humidity, pressure and light intensity. Employing power-saving techniques like sleep/wake cycles and controlled sampling rates makes the station economical and power-efficient. This setup allows distant observation via a web browser interface, addressing the challenge of low power and extended-range deployments of embedded systems. The adopted energy optimization strategy enabled autonomous long-range functioning, with real-time data collection and visualization. The recoded peak power consumption is only 2022 A for all the embedded operations.

Flexible piezoelectric nanogenerator (PENG) and triboelectric nanogenerators (TENG) have gained prodigious attention due to the increasing demand of nano and micro energy for driving of miniaturized electronic devices, sensors, and various internet of things. The key challenges that are currently in focus are material selection and simple fabrication techniques for improved electrical performance along with good mechanical properties and flexibility. Herein, a ferroelectric polymer, poly(vinylidenefluoride-co-trifluoroethyne) (PVDF-TrFE), is chosen as a flexible material due to its promising prospect for energy harvesting. To improve the performance, a ceramic material, 0.65Pb(Mg1/3Nb2/3)O3–0.35PbTiO3 (PMN-PT), with very high piezoelectric properties has been selected as the reinforcement. Further, reduced graphene oxide has been added as a conducting filler to promote charge conduction. A remarkable enhancement in output voltage of nearly 3 fold is achieved in PVDF-TrFE/PMN-PT (PP) polymer composite as compared to the base polymer PVDF-TrFE (P) TENG device. Furthermore, the PVDF-TrFE/rGO/PMN-PT (PPR) as a PENG illustrates a great improvement in output current of the order of 2 as compared to the pristine polymer. The maximum output voltage as shown by the TENG is 200 V and the maximum current that is shown by the PENG is 30 µA. Therefore, the fabricated PMN-PT based PVDF-TrFE nanogenerators have an immense prospect for applications in self-powered systems.

Piezoelectric nanogenerators have emerged as a pivotal platform technology in bioengineering, advancing cardiac healthcare. Unlike common pacemakers, these devices capitalize on the mechanical energy derived from cardiac movements to power themselves, presenting a sustainable alternative to the battery constraints faced by current implantable cardiac devices. This review explores the advances in piezoelectric nanogenerators for cardiac monitoring and therapy, highlighting their capabilities to not only track cardiac activity but also provide therapeutic interventions and reliable energy for pacemakers. It also discusses the electrical stimulation effects and biocompatible integration with human biology, positioning piezoelectric nanogenerators at the forefront of healthcare solutions. This enhances the effectiveness, durability, and personalization of cardiac care.

Cognitive radio non-orthogonal multiple access (CR-NOMA) technology was used to alleviate the shortage of spectrum resource, and improve the throughput of sensor devices. But the energy efficiency problem had been restricting the application of sensor devices. Therefore, for CR-NOMA, deep deterministic policy gradient-based energy efficiency optimization (DPEE) algorithm was proposed. By jointly optimizing the transmission power and time slot splitting coefficient, the energy efficiency of sensor devices was improved. The energy efficiency optimization problem was modeled as a Markov decision process, and it was solved by the deep deterministic policy gradient (DDPG) method. Finally, the influence of circuit power consumption, time slot durations and number of main devices on energy efficiency were analyzed. The simulation results show that the energy efficiency decreases as the circuit power consumption of sensor device increases. In addition, compared with other algorithms, the proposed algorithm improves energy efficiency.

In this manuscript, we present a novel approach for integrating Triboelectric Nanogenerators (TENGs) into signature stamps, termed Stamp TENG (S-TENG). We have modified a commercially available stamp holder to integrate triboelectric layers for multiple applications like effective energy harvesting, sensing, and embedded electronics for data prediction. S-TENG has been further explored in remote monitoring systems for elderly individuals and for gathering real-time statistics regarding persons or events at specific locations. The S-TENG is fabricated using FEP and Al as functional layers. It demonstrates an output voltage of 310 V, a current of 165 μA, and a power density of 14.8 W/m2. The simplicity of the S-TENG’s design is noteworthy. Its ability to generate energy through simple, repetitive stamping actions, which anyone can perform without specialized training, stands out as a key feature. The device is also designed for ease of use, being handheld and user-friendly. Its flexible and adaptable structure ensures that individuals with varying physical capabilities can comfortably operate it. An impressive capability of the TENG is its ability to illuminate 320 LEDs with each stamp press momentarily. Furthermore, using energy management circuits, the S-TENG can power small electronic gadgets such as digital watches and thermometers for a few seconds. In addition, when integrated with electronics, the S-TENG shows great potential in data prediction for various practical applications.

ABSTRACTThe secrecy performance of wireless networks powered up by a dedicated power beacon (PB) is addressed in this work. Particularly, the closed-form expression of the secrecy outage probability (SOP) under the presence of multiple eavesdroppers is given. The considered networks are asymmetric since there are multiple eavesdroppers but only a single legitimate receiver. As a consequence, two wiretap schemes are employed, namely, non-colluding and colluding schemes, to take advantage of multiple eavesdroppers. To draw insights from the derived framework, the asymptotic framework of the SOP under the high transmit power regime is also provided. Next, Monte Carlo simulations are provided to validate the theoretical foundations of the proposed approach. Our findings show that by increasing the transmit power from −10 dB to 30 dB, the SOP ameliorates almost a thousand times. Additionally, the SOP is a monotonic decreasing function with a time-switching ratio. We also make comparisons with work in the literature in which the full-duplex relay is employed to help the legitimate link. Numerical results illustrate that the proposed network outperforms those described in the literature. Particularly, through reliance on the setup, the SOP under the proposed system is better than those of the literature by about twofold.

Abstract Converting dispersed mechanical energy into electrical energy can effectively improve the global energy shortage problem. The dispersed mechanical energy generated by liquid flow has a good application prospect as one of the most widely used renewable energy sources. Solid–liquid triboelectric nanogenerator (S–L TENG) is an inspiring device that can convert dispersed mechanical energy of liquids into electrical energy. In order to promote the design and applications of S–L TENG, it is of vital importance to understand the underlying mechanisms of energy conversion and electrical energy output affecters. The current research mainly focuses on the selection of materials, structural characteristics, the liquid droplet type, and the working environment parameters, so as to obtain different power output and meet the power supply needs of diversified scenarios. There are also studies to construct a theoretical model of S–L TENG potential distribution mechanism through COMSOL software, as well as to obtain the adsorption status of different kinds of ions with functional groups on the surface of friction power generation layer through molecular dynamics simulation. In this review, we summarize the main factors affecting the power output from four perspectives: working environment, friction power generation layer, conductive part, and substrate shape. Also summarized are the latest applications of S–L TENG in energy capture, wearable devices, and medical applications. Ultimately, this review suggests the research directions that S–L TENG should focus on in the future to enhance electrical energy output, as well as to expand the diversity of application scenarios.

ABSTRACTThe average transmit power and coverage probability (Pcov) of uplink energy harvesting-enabled long-range networks are investigated in the present paper. Particularly, we model the end-device (EDs) according to the homogeneous Poisson point process while the power beacon is randomly distributed on the circle in the middle of the network. All EDs rely on the harvested energy to perform their operations and transmissions. Under this context, the upper bound of the average transmit power of an end-device is derived in the closed-form expression. The signal-to-noise-ratio condition of the coverage probability is given in the closed-form expression as well. Simulation results are provided to corroborate the accuracy of the derived mathematical framework as well as to feature the impact of some key parameters on the considered metrics. Our findings unveil that increasing either the number of power beacons or their transmit power will monotonically ameliorate the Pcov. Nevertheless, rising the average number of EDs will significantly decline the Pcov's performance.

Abstract The design and optimization of an electromagnetic wave absorber for far-field wireless power transmission (WPT) is the subject of this research study. The goal of the research is to effectively absorb energy from ambient RF electromagnetic waves without the usage of a ground plane by employing metasurfaces with chiral components.By integrating trioidal moments into the design theory, the objective is to create a metasurface that functions in two frequency bands and produces high-quality resonance. The study also explores the dual non-homogeneity property of structures, polarization tensor coefficients, and the electromagnetic response of non-homogeneous metasurfaces. Based on the relative orientation of induced fields and moments, it delves deeper into the two basic possibilities for dual non-homogeneous elements. The development of chiral metasurfaces and the notion of electromagnetic chirality and its implications for polarization properties are introduced.

Abstract Building structures are subjected to strong earthquakes, which result in lateral collisions between them. Such collisions often cause severe structural damage and exacerbate the seismic hazard risk of building structures during earthquake events. This paper discusses the application of vibration control devices based on negative stiffness inerter damper in single-story adjacent building structures. The dynamic equations of the vibration control system containing different types of negative stiffness inerter damper under seismic excitation are established as a unified model. The H2 norm theory and Monte Carlo pattern search method are used to optimize the design parameters to improve the vibration control performance of the system, and the dynamic characteristics of the system are investigated. The results demonstrate that attaching negative stiffness inerter damper to adjacent building structures can effectively improve the overall seismic capacity reserve of the building and reduce the risk of collision of adjacent building structures; improve the robustness and stability of the system, and better reduce the displacement response of the building structure under seismic excitation. In addition, the potential of NSID-based vibration control devices to convert seismic energy into usable electricity has been investigated.

Highlights A bionic phase-locked structure-inspired iontronic triboelectric gel is proposed with good mechanical compliance for wearable haptic sensing applications. Competitive hydrogen bonding systems are constructed through polymer-solvent-nonsolvent interactions, and regeneration of polymers with weak hydrogen bond donors triggers controlled phase separation. Self-powered haptic skin constructed with iontronic triboelectric gel has a modulus (150.6 kPa) and stretchability (> 400%) similar to that of the human body, enabling fidelity transmission of haptic signals and precise recognition of sensing objects.

Abstract Nowadays, the digital development of marine ranching requires a communication system with wide coverage, high transmission rate and stable communication links. It is known that fixed‐wing unmanned aerial vehicles (UAVs) have great advantages in long‐range applications. They have the potential to serve as low‐altitude communication platforms for maritime communication. In this study, with a developmental perspective, considering the intense growth of marine terminals in the future, a new clustering algorithm applied to cluster nonorthogonal multiple access (C‐NOMA) is proposed and its advantages are investigated. In addition, considering the limited energy of marine terminals, combining the wireless power communication (WPC) technology for the UAV to charge terminals, the charging and communication time are optimized with the Lagrange multiplier method and the bisection search method. After completing the above optimization content of charging and communication, combined with the optimization results, it is found the trajectory that maximizes the energy efficiency of the UAV with the convex optimization technique. Experimental results show that the proposed clustering algorithm has good throughput performance, better fairness and lower algorithm complexity, and the proposed trajectory optimization scheme has better energy efficiency.

Abstract Light is a popular choice as an indoor energy source for Internet of Things (IoT) end devices. However, indoor light sources are intermittent, which can disrupt the operation of IoT end devices, potentially leading to safety concerns or inaccurate data. Therefore, there is a growing need to develop a long‐duration power supply for IoT end devices. The energy from ambient light is harnessed to charge a supercapacitor through an energy manager chip. This supercapacitor serves as the power source for IoT nodes when the ambient light is unavailable. Nevertheless, as the voltage of the supercapacitor drops below the operating threshold, the IoT end node will eventually shut down. This paper proposes a circuit that utilizes a Joule Thief circuit, booster converter, and capacitor stack‐up circuit to extract the remaining energy from the supercapacitor and boost the voltage, thereby extending the operational lifespan of IoT end nodes. Additionally, capacitor stack‐up circuits significantly enhance charging efficiency. PSpice design and simulations confirm circuit feasibility. High‐efficiency charging and long‐duration IoT nodes suggest replacing traditional batteries with supercapacitors, reducing environmental impact.

Abstract Unmanned aerial vehicles (UAVs) offer a new approach to wireless communication, leveraging their high mobility, flexibility, and visual communication capabilities. Ambient backscatter communication enables Internet of Things devices to transmit data by reflecting and modulating ambient radio waves, eliminating the need for additional wireless channels, and reducing energy consumption and cost for sensors. However, passive ambient backscatter communication has limitations such as limited range and poor communication quality. By utilizing UAVs as communication nodes, these limitations can be overcome, expanding the communication range and improving the quality of communication. Although some research has been conducted on combining UAVs and ambient backscatter, several challenges remain. One key challenge is the strong direct link interference in ambient backscatter under UAV conditions, which significantly affects communication quality. In this paper, we propose an intelligent backward and forward straight link interference cancellation algorithm based on NOMA decoding technique to enhance ambient backscatter communication quality under UAV conditions and extract more ambient energy for UAV energy supply. The paper includes theoretical derivation, algorithm description, and simulation analysis to validate the error bit rate of labeled information bits. The results demonstrate that the forward algorithm reduces the error bit rate by approximately 20% under low signal-to-noise ratio (SNR) conditions, while the backward algorithm reduces the error bit rate under high SNR conditions. The combination of the forward and backward algorithms reduces the error bit rate under both high and low SNR conditions. The proposed method contributes to improving the quality of ambient backscatter communication in UAV settings.

Energy efficiency is a key area of research aimed at achieving sustainable and environmentally friendly networks. With the rise in data traffic and network congestion, IoT devices with limited computational power and energy resources face challenges in analyzing, processing, and storing data. To address this issue, computing technology has emerged as an effective means of conserving energy for IoT devices by providing high-performance computing capabilities and efficient storage to support data collection and processing. As such, energy-efficient computing, or ''green computing,'' has become a focal point for researchers seeking to deploy large-scale IoT networks. This study provides a comprehensive Survey of recent research efforts aimed at achieving energy-efficient computing and green computing for IoT networks. To the best of our knowledge, none of the studies in the literature have discussed all types of green computing (edge, fog, cloud) and their role in enabling massive IoT networks in terms of energy efficiency. The article starts with an overview of computing technologies and then goes with a discussion of the empowering energy-saving techniques for computing (edge, fog, and cloud) environments including, energy-aware architecture, data aggregation and compression, low-power hardware, energy-aware scheduling, task offloading, switching on/off unused resources, virtualization, energy harvesting, and cooling optimization. This article is an outline of a roadmap toward realizing the vision of a sustainable computing environment for massive IoT networks; in addition, open the door for interested researchers to follow and continue the vision of Energy-Efficient Computing.

In the human body, non-centrosymmetric biological structures exhibit piezoelectric effect across from microscopic biomolecular building blocks to macroscopic tissues and organs. However, the fabrication of piezoelectric devices from discarded natural tissues and organs has rarely been exploited for energy harvesting applications. Herein, the extracted human teeth were recycled as an active layer in a piezoelectric nanogenerator for power generation. Due to the piezoelectric effect of enamel and dentin, a human teeth-based sandwiched piezoelectric nanogenerator was fabricated, producing high and stable power outputs with an open-circuit voltage of approximately 0.9 V under an external force at 60 N. Furthermore, the high mechanical durability of the piezoelectric nanogenerator was also verified after 1600 pressing-and-releasing cycles without noticeable output degradation. Notably, for the first time, a light-emitting diode (LED) was illuminated by the human teeth-based piezoelectric device. This work exemplifies a sustainable strategy to recycle the extracted human teeth by fabricating a piezoelectric nanogenerator for energy harvesting, providing inspiration for converting waste into wealth toward green energy in bionanotechnology.

Piezoelectric devices are transducers that convert pressure variations into electricity. Piezoelectric energy harvesting technology is based on harnessing pavement energy, using the pressure of vehicles due to gravity, where electricity is generated through the deformation of pavement materials. The main objective of this article is to show how bicycle traffic- on a bikeway- can be harnessed to obtain electrical energy with piezo-electric devices, analyzing an existing model of bicycle forces and gathering a model of traffic on the bikeway. This article implements three phases of analysis: the characterization of the bicycle according to the type of bicycle and traffic characteristics, the classification and selection of piezoelectric devices, and the amount of electrical energy produced by bicycle traffic that can be harnessed in signaling. The results are promising since with average daily traffic of 40,000 bicycles, 1.02 kWh is obtained in one linear meter with a piezoelectric device, which means that this same traffic in one kilometer of bikeway can generate approximately 1000 kWh per day.

This paper presents a comprehensive review of the latest developments in fuzzy logic (FL) applications across critical domains which include energy harvesting (EH), ambient conditioning systems (ACS), and robotics and autonomous systems (RAS), highlighting FL's capability to address nonlinearities and uncertainties in diverse technological environments. Through a detailed comparative analysis of research trends over the past decade, it underscores the increasing significance of FL in EH and RAS, contrasting with the sustained interest in ACS. Furthermore, the evaluation of different fuzzy inference systems across domains provides valuable insights into their specific strengths and limitations, aiding researchers and practitioners in making informed decisions aligned with their application needs. Additionally, the paper explores advanced modifications and hybridizations of FL, such as swarm intelligence and integrations with other control strategies, emphasizing the necessity for robust and adaptive FL systems. The review also identifies key open problems and potential research directions, such as the demand for adaptive FL systems in EH and advanced optimization techniques in ACS and RAS. Overall, this state-of-the-art review not only summarizes the current state of FL applications but also outlines a roadmap for future research, offering valuable insights for advancing FL's role in handling uncertainties and nonlinearities in complex systems.

Energy harvesting from Vortex-Induced Vibration (VIV) presents a promising avenue for renewable energy generation by harnessing the kinetic energy of fluid flows through innovative technologies. Despite the increasing interest in VIV energy harvesting, there is a need for a systematic evaluation of the existing literature to understand the research trends, key contributors and emerging areas of focus. A bibliometric analysis offers a quantitative approach to address this gap, providing valuable insights into the evolution and dynamics of research on energy harvesting from VIV. The analysis employs VOSviewer software to analyze publication data retrieved from Scopus, focusing on publication trends, top authors, subject area, top citation, popular keywords, co-authorship countries’ collaboration and network mapping based on citation by country. By examining publication patterns, citation counts and collaboration networks, this study aims to uncover underlying patterns and identify critical factors driving research in this field. The bibliometric analysis reveals a significant upward trend in research activity, with a notable increase in publications from recent years, indicating growing interest and recognition of VIV energy harvesting. In conclusion, this bibliometric analysis provides valuable insights into the research trends, key contributors and collaborative networks in energy harvesting from VIV. The findings guide for both academic and industrial , facilitating informed decision-making and driving progress toward sustainable energy solutions. This study also lays the groundwork for future research directions and interdisciplinary collaborations aimed at maximizing the potential of VIV energy harvesting for renewable energy generation.

In this paper a new renewable energy source was proposed based on rain power. Rain energy was not used as an energy source up to now; so, in this research its applicability was investigated as a green large scale power source. Hence, three innovative mechanisms were presented to harvest the energy of rain. Firstly, the kinetic energy of rain drops was converted to electricity using piezoelectric harvesters designed and named as Pizo-panel collectors. Secondly, potential energy of collected rainwater was enhanced by utilizing designed towers and converted to electricity using a water turbine. Thirdly, collected water was used in osmotic power units to generate electricity from the salinity gradient of that rain water and brine. The results show that generated power in the presented power plant named as rain power plant, was considerable and can be used for diversifying of energy basket. In addition to power generation, collected water in the rain power plant can be used for supplying urban and agricultural need for water. The presented power source not only does not have destructive impacts on the environment, but also helps the soil to prevent it from splash and crusting erosion. The results showed that total global annual rain energy potential amount was estimated to be 3.44 × 108 GW h which is comparable with global potential of solar energy. Also, the results showed that for rainy areas with an annual rainfall of 200 cm, 2.59 kW h/m2 could be produced, which is equal to 51.7 MW h for an area of 200,000 m2.

Abstract The intensifying energy crisis has made it urgent to develop robust and reliable next‐generation energy systems. Except for conventional large‐scale energy sources, the imperceptible and randomly distributed energy embedded in daily life awaits comprehensive exploration and utilization. Harnessing the latent energy has the potential to facilitate the further evolution of soft energy systems. Compared with rigid energy devices, flexible energy devices are more convenient and suitable for harvesting and storing energy from dynamic and complex structures such as human skin. Stretchable conductors that are capable of withstanding strain (≫1%) while sustaining stable conductive pathways are prerequisites for realizing flexible electronic energy devices. Therefore, understanding the characteristics of these conductors and evaluating the feasibility of their fabrication strategies are particularly critical. In this review, various preparation methods for stretchable conductors are carefully classified and analyzed. Furthermore, recent progress in the application of energy harvesting and storage based on these conductors is discussed in detail. Finally, the challenges and promising opportunities in the development of stretchable conductors and integrated flexible energy devices are highlighted, seeking to inspire their future research directions.

Abstract This letter presents the design of a 13.56 MHz offset‐enhanced full‐wave active rectifier, tailored for wirelessly powered biomedical implants. The design incorporates digitally assisted, delay‐compensated active diodes and symmetrical bulk biasing in the rectifier core to enhance conduction time, thus improving the voltage conversion ratio (VCR) and power conversion efficiency (PCE). A delay improvement is achieved both in no‐load and high‐load conditions through an additional comparison path with an offset voltage that is higher than zero. The proposed rectifier is implemented and fabricated in a 180 nm CMOS technology with an area of 0.024 mm2. The rectifier, tested and measured with inductive links, offers a maximum VCR of 96.4% and a maximum PCE of 89%.

Although batteries are a highly popular energy source in biosensors, batteries can be an economic limitation for low‐cost sensing applications and pose significant challenges in miniaturization, biocompatibility, and disposal. To surmount such issues, “self‐powered sensors” gain the spotlight thanks to their energy harvesting from the environment through embedded miniaturized systems. In this review, the recent developments in self‐powered devices are summarized with a specific focus on the integration of supercapacitors with sensors and biosensors. The working principles of microsupercapacitors, fabrication methods, their integration with biosensors, and their ultimate applications (i.e., biomedical monitoring and analytical biomarker detection) are described. Different energy harvesting systems are summarized and their integration with self‐powered sensors or biosensors is highlighted. The limitations and challenges of the existing approaches and the future of supercapacitor‐integrated sensing systems are also critically discussed.

The Sustainable Development Goals (SDG) of the United Nations emphasize the need for renewable, low-cost, and environmentally friendly energy. The review analyses of progress and obstacles in the field of clean energy (SDG-7) production and storage in the United Arab Emirates (UAE). The potential of specific technologies, such as solar cells, enhanced wind turbines, and bioenergy conversion processes, to produce a greener energy environment is highlighted. An assessment is conducted on cutting-edge storage techniques such as lithium-ion batteries and thermal storage systems, to tackle the irregularity of renewable energy sources and enhance the stability of the power grid. Providing a comprehensive account of significant initiatives and the policies that are propelling its low-carbon economy. The review investigates challenges related to grid integration, energy intermittency, and infrastructure restrictions. It also presents proposed solutions to improve system reliability, durability, and efficiency.

Abstract Laser‐induced graphene (LIG) technology has provided a new manufacturing strategy for the rapid and scalable assembling of triboelectric nanogenerators (TENG). However, current LIG‐based TENG commonly rely on polymer films, e.g., polyimide (PI) as both friction material and carbon precursor of electrodes, which limit the structural diversity and performance escalation due to its incapability of folding and creasing. Using specialized PI paper composed of randomly distributed PI fibers to substantially enhance its foldability, this work creates a new type of TENG, which are structurally foldable and stackable, and performance tailorable. First, by systematically investigating the laser power‐regulated performance of single‐unit TENG, the open‐circuit voltage can be effectively improved. By further exploiting the folding process, multiple TENG units can be assembled together to form multi‐layered structures to continuously expand the open‐circuit voltage from 5.3 to 34.4 V cm−2, as the increase of friction units from 1 to 16. Last, by fully utilizing the unique structure and performance, representative energy‐harvesting and smart‐sensing applications are demonstrated, including a smart shoe to recognize running motions and power LEDs, a smart leaf to power a thermometer by wind, a matrix sensor to recognize writing trajectories, as well as a smart glove to recognize different objects.

Vibration signals are essential data for the health monitoring of structures and the cyber–physical system. However, commercial vibration sensors are generally installed on struts/surfaces to gather raw data, which affects the result or causes the detachment problem. This study uses a facile 3D printing method to fabricate a smart vibration absorber with an interior multifunctional multimaterial elastic lattice (MMEL). These lattices, which work as vibration absorbers, have been demonstrated to possess the functions of self‐powered sensing and energy harvesting via the triboelectric effect. The triangular geometry parameter, materials type, etc. have been investigated to illustrate their basic mechanical and triboelectric properties and their coupled influence. Further, the results of the shock test show that MMEL can decrease the peak force from approximately 625 to 90 N and convey the Voc impulse signal simultaneously. The vibration signal has been collected through the MMEL to detect the vibration frequency and charge a watch simultaneously, demonstrating the feasibility and practical potential of the MMEL. The research provides a new method for constructing a multifunctional vibration absorber for applications.

With the improvement in people’s quality of life, the requirements for health and safety are also increasing. While many wearable devices are available, those wearable devices specifically designed for the safety of night workers have yet to be effectively utilized. A survey conducted with 100 night workers revealed that they have expressed concerns about their safety and that of their colleagues due to lack of visibility while working on the road at night. To address this issue, a wearable electromagnetic energy generator was designed as a permanent solution to increase the visibility of night workers by illuminating LEDs and reduce the discomfort associated with wearable devices. The generator can be integrated with uniforms and converts the kinetic energy generated by the human body during work into electrical power. The generator achieved a maximum output power of 4.28 mW under 2.8 Hz, with a power density is 51.56 μW/cm3. The LED brightness driven by the generator reached 218 Lux. To ensure user customization, the Living Lab strategy was employed, allowing direct user participation during the development process and incorporating improvements based on their feedback. After gathering feedback from the workers, the uniform was redesigned and revised multiple times. Ultimately, the product received high satisfaction scores and was successfully delivered to local municipalities. This paper details a comprehensive study covering the process from needs survey to product design.

Abstract The human body continuously generates ambient mechanical energy through diverse movements, such as walking and cycling, which can be harvested via various renewable energy harvesting mechanisms. Triboelectric Nanogenerator (TENG) stands out as one of the most promising emerging renewable energy harvesting technologies for wearable applications due to its ability to harness various forms of mechanical energies, including vibrations, pressure, and rotations, and convert them into electricity. However, their application is limited due to challenges in achieving performance, flexibility, low power consumption, and durability. Here, we present a robust and high‐performance self‐powered system integrated into cotton fabric by incorporating a textile‐based triboelectric nanogenerator (T‐TENG) based on 2D materials, addressing both energy harvesting and storage. The proposed system extracts significant ambient mechanical energy from human body movements and stores it in a textile supercapacitor (T‐Supercap). The integration of 2D materials (graphene and MoS2) in fabrication enhances the performance of T‐TENG significantly, as demonstrated by a record‐high open‐circuit voltage of 1068 V and a power density of 14.64 W/m2 under a force of 22 N. The developed T‐TENG in this study effectively powers 200+ LEDs and a miniature watch while also charging the T‐Supercap with 4‐5 N force for efficient miniature electronics operation. Integrated as a step counter within a sock, the T‐TENG serves as a self‐powered step counter sensor. This work establishes a promising platform for wearable electronic textiles, contributing significantly to the advancement of sustainable and autonomous self‐powered wearable technologies.

Abstract Hydraulic fluid power systems are essential for a range of engineering applications such as transportation, heavy industry, and robotics. The scale of the industry is such that hydraulic pumps are estimated to account for 15% of all the energy consumption in the European Union and yet the average efficiency of fluid power systems is only 22%. The digitalization of hydraulic systems offers significant advantages in terms of energy efficiency, performance, reduced maintenance, and automation. However, this requires advances in the integration of smart sensing technologies to provide real‐time feedback on the operation and health of hydraulic components. This review details developing trends in hydraulic fluid power research and provides an overview of progress related to the digitalization of these systems and their integration within an Industry 4.0 framework. The fundamentals of relevant sensor technologies and innovative approaches for integrating sensors into hydraulics systems are discussed. Methods to deliver power to the sensors and associated electronics through harvested pressure ripples are also reviewed. An outlook with respect to future directions in this field is given, including an assessment of the potential for exploiting advanced manufacturing technologies, in particular additive manufacturing, to facilitate successful sensor integration into hydraulic fluid power systems.