Self-powered Internet Of Things Research Articles

Efficient Sb2S3 and Low Se Content Sb2SeyS3-y Indoor Photovoltaics.

Herein, the precise fabrication of Sb2S3 and low Se content Sb2SeyS3-y indoor photovoltaics is reported, and a measurement protocol for photovoltaic performance is suggested and applied. Insertion of the SnO2 buried layer decreases the thickness and parasitic absorption of the CdS layer. The introduction of minor Se into Sb2S3 and the use of spiro-OMeTAD:TMT-TTF improve the charge transport of indoor photovoltaics. Using a white light-emitting diode (LED) under illuminance of 1000, 500, and 200 lx with color temperatures of 3347 and 6103 K, indoor photovoltaics with fluorine doped tin oxide (FTO)/SnO2 (17 nm)/CdS (20 nm)/Sb2S3/spiro-OMeTAD:TMT-TTF/Au exhibit power conversion efficiency (PCE) values of 17.59, 16.66, 16.44, 16.56, 15.50, and 14.07%, respectively. Indoor photovoltaics with FTO/SnO2 (17 nm)/CdS (20 nm)/Sb2SeyS3-y(Sb/S/Se = 1:1.42:0.06)/spiro-OMeTAD:TMT-TTF/Au achieve PCE values of 18.53, 17.62, 17.07, 17.30, 16.24, and 15.38%, respectively. The PCE values of 17.59, 16.66, and 16.44% are the highest values reported for Sb2S3 indoor photovoltaics, and the other PCEs are all reported for the first time. Considering the trillion-dollar-sized market from the Internet of Things (IoT), this work can further bring an unprecedented thrust to the development of self-powered IoT devices by harvesting energy from indoor photovoltaics, thereby realizing the recycling of photon energy and reducing the use of batteries and the emission of CO2.

Light power resource availability for energy harvesting photovoltaics for self-powered IoT

As the Internet of Things (IoT) expands, the need for energy-efficient, self-powered devices increases and so a better understanding of the available energy resource is necessary. We examine the light power resource availability for energy harvesting photovoltaics (PV) in various environments and its potential for self-powered IoT applications. We analyse light sources, considering spectral distribution, intensity, and temporal variations, and evaluate the impact of location, seasonal variation, and time of day on light power availability. Additionally, we discuss human and building design factors, such as occupancy, room aspect, sensor placement, and décor, which influence light energy availability and therefore power for IoT electronics. We propose a best-case and non-ideal scenario in terms of light resource for energy-harvesting, and using a commercially available organic PV cell, show that the energy yield generated and available to the IoT electronics, can be anywhere between 0.7 mWh and 75 mWh per day, depending on the lighting conditions.

SALA-IoT: Self-Reduced Internet of Things With Learning Automaton Sleep Scheduling Algorithm

The extensive development of wireless communications has led to the popularity of the Self-Powered Internet of Things (SPIoT) networks. Even though significant advances made in keeping energy consumption at a low level, making such networks live longer are still one of the biggest challenges. In particular, a significant question is how to cover the maximum range of the environment by the sensor nodes with the lowest amount of energy. In this research, we have proposed a sleep Scheduling Algorithm based on Learning Automaton for IoT (SALA-IoT), utilizing machine learning approaches to find the optimal set of sensor nodes that can cover a wide range of the environment. This algorithm consists of learning and covering phases, in which the essential sensor nodes are activated, and the rest are turned off. Although the implementation of learning algorithms requires a high energy level, after the learning phase’s performance, the network gathers complete information about the status of the nodes. It can meet the needs of the network with a limited amount of energy. We have evaluated the proposed algorithm with several simulation scenarios and considered the coverage area and the number of active sensor nodes as the main evaluation metrics. The simulation results show that the sensors sensing and covering ranges are directly related to their transmitted power, and the transmitted power of the sensors can be adjusted to match the expected network requirements in terms of primary coverage factors; the proposed method improved by 6.743 for 50 nodes and 5.204 for 100 nodes, respectively, for distance and intervals in a different number of nodes.

Optimizing the design of wide magneto-mechano-electric generators to maximize their power output and lifetime in self-powered environmental monitoring systems

Magneto-mechano-electric (MME) generators are increasingly being investigated as a sustainable power source for Internet of Things (IoT) systems owing to their ability to efficiently harvest electrical energy from stray magnetic field noise. However, to be practical, this technology must achieve a longer lifespan while maintaining high-power output and withstanding magnetic field fluctuations. To address this, extensive numerical simulations and experimental verifications have been performed to amplify the magneto-mechanic vibration by increasing the magnetic proof mass volume, generate high electrical output through a larger active piezoelectric volume, and enhance lifetime by optimizing the cantilever structure in a wide-structural MME architecture. MME generators with a wide and short (WS) trapezoidal structure (WS-MME) have demonstrated excellent performance, with a high output power of 7.4 mW (equivalent power density of 0.58 mW/cm3. Oe) and an excellent lifespan of over 1012 fatigue cycles under a magnetic noise field level of 3 Oe. Moreover, a self-powered environmental IoT sensor node has been demonstrated by continuously powering the multifunctional (temperature, humidity, light, sound noise, UV index, pressure, discomfort index, and heatstroke) sensor and wireless communication systems by utilizing the stray magnetic field noise around the electrical power cables of various home appliances. In conclusion, the combination of a longer lifespan and high-power generation achieved with WS-MME generators is a significant step towards the commercialization of MME generators for powering wireless sensor technology.

Energy harvesting and wireless communication by carbon fiber-reinforced polymer-enhanced piezoelectric nanocomposites

Piezoelectric Internet of Things (IoT) sensors with energy-harvesting capabilities, which can convert mechanical energy into electrical energy, promote battery-less systems. Such sensors can harness the vibration generated by spacecraft and other moving objects, eliminating the need for external power sources or battery replacements, thereby improving the autonomy and reliability of the system. This study investigates the features of a novel piezoelectric vibration energy harvester (PVEH) that comprises a carbon fiber-reinforced polymer (CFRP) electrode. The CFRP electrode provides outstanding electrical conductivity (7190 S/m) and enhances the mechanical characteristics of the energy collector, thereby ensuring a steady electrical energy yield during resonance. The piezoelectric composite consists of potassium sodium niobate (KNN) nanoparticles mixed with epoxy resin. Results show that when the KNN content is about 30 vol%, the piezoelectric properties of d33 and d31 are 15.21 pC/N and − 5.68 pC/N, respectively. Under an applied displacement of 0.05 mm, the CFRP-reinforced PVEH (C-PVEH) provides an impressive output energy volume density of 89.61 μW/cm3, which is capable of lighting LED bulbs with ease. Notably, this technology shows great application potential for powering wireless communication systems, indicating a remarkable advancement in the field of self-powered IoT sensors. This study provides valuable insights into the potential application of this groundbreaking technology.

Investigation of Self-Powered IoT Sensor Nodes for Harvesting Hybrid Indoor Ambient Light and Heat Energy.

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period.

An Advanced Strategy to Enhance TENG Output: Reducing Triboelectric Charge Decay.

The Internet of Things (IoT) is poised to accelerate the construction of smart cities. However, it requires more than 30 billion sensors to realize the IoT vision, posing great challenges and opportunities for industries of self-powered sensors. Triboelectric nanogenerator (TENG), an emerging new technology, is capable of easily converting energy from surrounding environment into electricity, thus TENG has tremendous application potential in self-powered IoT sensors. At present, TENG encounters a bottleneck to boost output for large-scale commercial use if just by promoting triboelectric charge generation, because the output is decided by the triboelectric charge dynamic equilibrium between generation and decay. To break this bottleneck, the strategy of reducing triboelectric charge decay to enhance TENG output is focused. First, multiple mechanisms of triboelectric charge decay are summarized in detail with basic theoretical principles for future research. Furthermore, recent advances in reducing triboelectric charge decay are thoroughly reviewed and outlined in three aspects: inhibition and application of air breakdown, simultaneous inhibition of air breakdown and triboelectric charge drift/diffusion, and inhibition of triboelectric charge drift/diffusion. Finally, challenges and future research focus are proposed. This review provides reference and guidance for enhancing TENG output.

Mechanical intelligent wave energy harvesting and self-powered marine environment monitoring

Harvesting wave energy to power wireless sensors can realize marine environment monitoring. However, the low frequency and irregularity of waves, as well as the harsh marine environment, have become bottlenecks limiting the development of wave energy harvesting. Herein, we propose a novel concept of mechanical intelligent energy harvesting, i.e., adaptive external excitation and regulation of energy harvesting system by mechanical structure or mechanism rather than electrical components, and illustrate this concept by designing an irregular wave energy harvesting system. The proposed gravity-driven roller and seesaw-inspired structure are sensitive to low-frequency and irregular excitation, thereby wave energy can be more easily harvested into the system. Further, the bidirectional swinging of the seesaw is converted into a high-speed unidirectional rotation of the permanent magnet disc in one direction, resulting in a significant increase in the efficiency of electromechanical conversion. Moreover, symmetrical discs on both sides can rotate synchronously via magnetic coupling mechanism, which increases the magnetic flux in the coils for higher output power and the consistent phase of the voltage is conducive to the use of electricity. Besides, the rolling behavior is used by the triboelectric nanogenerator (TENG) to convert more mechanical energy into electricity without affecting the electromagnetic energy harvester. The experimental results show that the harvester can work effectively at the ultra-low frequency (0.1 Hz) and it can charge a 0.47 F capacitor to 5 V within 6 min to achieve a self-powered wireless marine environment monitoring system under simulated wave excitation. This work demonstrates that mechanical intelligent energy harvesting is a potential solution for irregular energy harvesting and self-powered Internet of Things (IoT).

Recent Strategies for High-Performing Indoor Perovskite Photovoltaics.

The development of digital technology has made our lives more advanced as a society familiar with the Internet of Things (IoT). Solar cells are among the most promising candidates for power supply in IoT sensors. Perovskite photovoltaics (PPVs), which have already attained 25% and 40% power conversion efficiencies for outdoor and indoor light, respectively, are the best candidates for self-powered IoT system integration. In this review, we discuss recent research progress on PPVs under indoor light conditions, with a focus on device engineering to achieve high-performance indoor PPVs (Id-PPVs), including bandgap optimization and defect management. Finally, we discuss the challenges of Id-PPVs development and its interpretation as a potential research direction in the field.

A focus on sustainable energy management for self-powered IoT devices via indoor photovoltaics.

The future of information technologies lies in the form of trillions of autonomous 'smart objects' that can sense and communicate with their environment delivering pervasive and ubiquitous computing beyond today's imagination. Michaels et al. (H. Michaels, M. Rinderle, I. Benesperi, R. Freitag, A. Gagliardi and M. Freitag, Chem. Sci., 2023, 14, 5350, https://doi.org/10.1039/D3SC00659J) have achieved a key milestone in this context by developing an integrated autonomous and light-powered Internet of Things (IoT) system. They also show that dye-sensitized solar cells are particularly well-suited for this purpose with an indoor power conversion efficiency of 38%, far surpassing conventional silicon photovoltaics and alternative indoor photovoltaics technologies.

A Coaxial Wrist-Worn Energy Harvester for Self-Powered Internet of Things Sensors

Energy harvesting from human motion has great potential of sustainably powering Internet of Things (IoT) sensors and satisfying their continuous sensing requirement. In this article, we propose a high-performance wrist-worn energy harvester to efficiently capture the biomechanical energy of arm swinging to self-power wearable sensors. Based on coaxial topology, a planetary gear system serves as frequency-up converter to increase energy conversion capacity, and all the functional units are coaxially installed to achieve a highly compact structure. Thanks to improved energy conversion capacity and structure compactness, the energy harvester can efficiently capture the kinetic energy of arm swinging and achieve high average power. We derive an analytical model to predict the system dynamics and power generation performance using the Lagrangian approach and mirror image method. We fabricate a miniature prototype with different proof mass configurations, which is characterized under bench-top excitations and tested under real walking excitations. The results show that in bench-top testing, the prototype generates maximum average power of 2.73 mW and maximum power density of 535.29 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {\mathrm {\mu }}\text{W}$ </tex-math></inline-formula> /cm3 at the excitation frequency of 1.2 Hz among different configurations. In terms of average power and power density, this energy harvester significantly overperforms its counterparts. In real walking testing, the prototype generates maximum average power of 3.13 mW at a walking frequency of 1.2 Hz among different configurations and achieves higher power output than bench-top testing. Finally, the prototype is used to simultaneously power four sensors and demonstrates great potential in self-powered IoT applications.

Perovskite Piezoelectric-Based Flexible Energy Harvesters for Self-Powered Implantable and Wearable IoT Devices

In the ongoing fourth industrial revolution, the internet of things (IoT) will play a crucial role in collecting and analyzing information related to human healthcare, public safety, environmental monitoring and home/industrial automation. Even though conventional batteries are widely used to operate IoT devices as a power source, these batteries have a drawback of limited capacity, which impedes broad commercialization of the IoT. In this regard, piezoelectric energy harvesting technology has attracted a great deal of attention because piezoelectric materials can convert electricity from mechanical and vibrational movements in the ambient environment. In particular, piezoelectric-based flexible energy harvesters can precisely harvest tiny mechanical movements of muscles and internal organs from the human body to produce electricity. These inherent properties of flexible piezoelectric harvesters make it possible to eliminate conventional batteries for lifetime extension of implantable and wearable IoTs. This paper describes the progress of piezoelectric perovskite material-based flexible energy harvesters for self-powered IoT devices for biomedical/wearable electronics over the last decade.

Piezoelectric Energy Harvesting at Circuit Resonance with Active Inductor (CRAI)

Background: Most of the proposed interface circuits use bulky inductors to enhance the key performance parameter i.e., power transfer efficiency. This sets constraints on the design of power conditioning circuitry for constrained IoT applications. Objective: To replace the bulky physical inductor with area optimized components suitable for integrated circuit realization with reduced silicon footprint for constrained applications like Internet-of-Things (IoT). Method: This paper presents the implementation of Circuit Resonance with Active Inductor (CRAI) technique based interface circuit design to deliver the maximum power generated from the Piezoelectric Energy (PEH) source to the load. Results: Compared to the conventional FWBR technique, the proposed CRAI technique improves ≈2X power delivered to the load. Conclusion: The proposed work presents an inductor-less interface circuit for PEH. An active inductor (gyrator) is used to induce ‘IP’ rejection at the PEH circuit resonant frequency to enhance the performance parameters. Since the proposed technique is based on active inductor, it can be easily fabricated in small integrated circuit (IC) packages, allowing integration with state-of-the-art constrained IoT applications. CRAI technique based on the rejection of ‘IP’ at the resonance using active inductor is first reported here. The proposed concept is non-adiabatic, but it could be used for constrained self-powered autonomous IoT applications and it could be of importance in guiding the design of new interface circuits for PEH.

Boosting the lifespan of magneto-mechano-electric generator via vertical installation for sustainable powering of Internet of Things sensor

Sustainability is essential for magneto-mechano-electric (MME) energy harvesters that convert low-frequency magnetic noise into useful electrical energy to be considered a practical power source for implementing real-life Internet of Things (IoT) sensor networks. In this study, we propose a vertically installed MME energy harvester based on a piezoelectric lead magnesium niobate-lead zirconate titanate (Pb(Mn1/3Nb2/3)O3-Pb(Zr,Ti)O3, PMN-PZT) single-crystal macro fiber composite cantilever. The MME harvester generates 12.2 mW output power from a low-amplitude stray magnetic field of 2.5 Oe and exhibits a long-term usable lifetime of 2.5 × 109 cycles while maintaining over 90 % of its output. An accelerated life test method is employed to predict the usable lifetime of the MME harvester using an inverse power law-Weibull model with accelerating stress of magneto-mechanical vibration-induced strain. In addition, a standalone wireless environmental monitoring system is demonstrated to operate for 10 weeks by exploiting the harvested power from stray magnetic fields (~2.2 Oe) near the power cables of home appliances. This study paves the way for lifetime assessment and prediction of sustainable MME harvesters to increase the practicability of self-powered IoT devices in smart infrastructures.

Hybrid energy harvesting for self-powered rotor condition monitoring using maximal utilization strategy in structural space and operation process

The energy harvesting technology is capable of harnessing the intrinsic rotating energy of the rotor system to realize self-powered rotor condition monitoring for the Internet of Things (IoT). It is promising to solve the issue of sustainable energy supply of the rotor monitoring system and achieve a self-powered IoT. In this work, we propose a novel maximal utilization strategy for piezoelectric-electromagnetic-triboelectric energy harvesting in a broad speed range and achieve the self-powered rotor condition monitoring system. The piezoelectric energy harvester (PEH), triboelectric nanogenerator (TENG), and electromagnetic energy harvester (EMH) are respectively arranged in the place where the system exhibits the maximum strain, the maximum contact area, and the maximum displacement, respectively, which can make full use of their characteristics in the structural space. The modulation boundaries (parts of TENG) render a more controllable dynamic behavior of the harvester, and realize the vibration and impact coordinated power generation mode, which can harvest more mechanical energy in the time domain. The theoretical mathematical model and working criteria of the proposed system are established and verified experimentally. In addition, the prototype can operate effectively in a wide speed range (0–1000 r/min) and it can charge a 100 μF capacitor to 5 V within 11 s. The self-powered rotor wireless temperature monitoring and self-powered wireless tire pressure monitoring are realized during the practical road tests. The maximum utilization strategy provides a new design methodology for hybrid energy harvesting, which has potential applications in intelligent driving and rotating machinery condition monitoring.

Piezoelectric Energy Harvesting towards Self-Powered Internet of Things (IoT) Sensors in Smart Cities.

Information and communication technologies (ICT) are major features of smart cities. Smart sensing devices will benefit from 5 G and the Internet of Things, which will enable them to communicate in a safe and timely manner. However, the need for sustainable power sources and self-powered active sensing devices will continue to be a major issue in this sector. Since their discovery, piezoelectric energy harvesters have demonstrated a significant ability to power wireless sensor nodes, and their application in a wide range of systems, including intelligent transportation, smart healthcare, human-machine interfaces, and security systems, has been systematically investigated. Piezoelectric energy-harvesting systems are promising candidates not only for sustainably powering wireless sensor nodes but also for the development of intelligent and active self-powered sensors with a wide range of applications. In this paper, the various applications of piezoelectric energy harvesters in powering Internet of Things sensors and devices in smart cities are discussed and reviewed.

Self-Powered Sensing for Smart Agriculture by Electromagnetic-Triboelectric Hybrid Generator.

The lack of efficient, low-cost, distributed energy collection methods is a vital factor restricting the application of the Internet of Things (IoT) in smart agriculture. This paper proposes a method based on triboelectric nanogenerator and electromagnetic generator to realize self-powered IoT nodes and self-powered sensors at the same time. An energy harvesting and sensing device based on electromagnetic-triboelectric hybrid generator (ES-ETHG) is designed. The peak power of ES-ETHG is 32.4 mW, which can supply power to IoT nodes for a long time with power management circuits. In addition, ES-ETHG can critically measure wind speed and wind level within the range of 3-15 m/s, and accurately detect wind direction within 2 s. Furthermore, the self-powered distributed weather sensing system based on ES-ETHG is developed to realize the remote collection of wind speed, wind direction, temperature, and humidity. This work proposes a solution for developing self-powered IoT and sensor in the field of smart agriculture.

Task Scheduling for Energy-Harvesting-Based IoT: A Survey and Critical Analysis

The Internet of Things (IoT) has important applications in our daily lives, including health and fitness tracking, environmental monitoring, and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries resulting from their finite energy availability. A promising solution is to harvest energy from environmental sources, such as solar, kinetic, thermal, and radio-frequency (RF) waves, for perpetual and continuous operation of IoT sensor nodes. In addition to energy generation, recently energy harvesters have been used for context detection, eliminating the need for conventional activity sensors (e.g., accelerometers), saving space, cost, and energy consumption. Using energy harvesters for simultaneous sensing and energy harvesting enables energy positive sensing-an important and emerging class of sensors, which harvest more energy than required for context detection and the additional energy can be used to power other components of the system. Although simultaneous sensing and energy harvesting is an important step forward toward autonomous self-powered sensor nodes, the energy and information availability can be still intermittent, unpredictable, and temporally misaligned with various computational tasks on the sensor node. This article provides a comprehensive survey on task scheduling algorithms for the emerging class of energy harvesting-based sensors (i.e., energy positive sensors) to achieve the sustainable operation of IoT. We discuss inherent differences between conventional sensing and energy positive sensing and provide an extensive critical analysis for devising revised task scheduling algorithms incorporating this new class of sensors. Finally, we outline future research directions toward the implementation of autonomous and self-powered IoT.

An inductorless piezoelectric energy harvesting interface circuit using gyrator induced voltage flip technique

PurposeThe purpose of this research paper is to explore the possibility to enhance the power transfer from piezoelectric energy harvester (PEH) source to the load. As the proposed gyrator-induced voltage flip technique (GIVFT) does not require bulky components such as physical inductors, it is easily realizable in small integrated circuits (IC) package thereby offering performance benefits, reducing area overhead and providing cost benefits for constrained self-powered autonomous Internet-of-Things (IoT) applications.Design/methodology/approachThis paper presents an inductorless interface circuit for PEH. The proposed technique is called GIVFT and is demonstrated using active elements. The authors use gyrator to induce voltage flip at the output side of PEH to enhance the charge extraction from PEH. The proposed technique uses the current-voltage (I-V) relationship of gyrator to get appropriate phasor response necessary to induce the voltage flip at the output of PEH to gain power transfer enhancement at the load.FindingsThe experimental results show the efficacy of the GIVFT realization for enhanced power extraction. The authors have compared their proposed design with popular earlier reported interface circuits. Experimentally measured performance improvement is 1.86×higher than the baseline comparison of full-wave bridge rectifier circuit. The authors demonstrated a voltage flip using GIVFT to gain power transfer improvement in piezoelectric energy harvesting.Originality/valueTo the best of the authors’ knowledge, pertaining to the field of PEH, this is the first reported GIVFT based on the I-V relationship of the gyrator. The proposed approach could be useful for constrained self-powered autonomous IoT applications, and it could be of importance in guiding the design of new interface circuits for PEH.

Dual-Band Store-and-Use System for RF Energy Harvesting With Off-the-Shelf DC/DC Converters

RF energy harvesting (RFEH) has recently become part of the alternatives for powering wireless sensor networks. Our focus in this article was to introduce a design, MSwitch , able to use off-the-shelf dc/dc converters for running a real and self-powered Internet of Things (IoT) application. MSwitch is an RF dual-band energy harvesting stage employing the store-and-use principle that mixes efficiently and in a dynamic manner both inputs. We proved an increase on the performance with respect to the single-band case and to the most successful approaches found in the literature, achieving about 10 % better efficiency and around 35 % lower minimum power levels. Besides, we carried out an analysis of the commercial dc/dc converters, characterizing them for ultralow-power conditions. Likewise, we analyzed the state-of-the-art rectification circuits and commercial Schottky diodes, searching the best performance under our RFEH conditions. Finally, we manufactured our designs as a complete system and demonstrated its operation with an IoT concrete application.