Superhydrophobic, Highly Conductive, and Trilayered Fabric with Connected Carbon Nanotubes for Energy-Efficient Electrical Heating

Current electrically heated fabrics provide heat in cold climates, suffer from abundant wasted radiant heat energy to the external environment, and are prone to damage by water. Thus, constructing energy-efficient and superhydrophobic conductive fabrics is in high demand. Therefore, we propose an effective and facile methodology to prepare a superhydrophobic, highly conductive, and trilayered fabric with a connected carbon nanotube (CNT) layer and a titanium dioxide (TiO2) nanoparticle heat-reflecting layer. We construct polyamide/fluorinated polyurethane (PA/FPU) nanofibrous membranes via first electrospinning, then performing blade-coating with the polyurethane (PU) solution with CNTs, and finally fabricating FPU/TiO2 nanoparticles via electrospraying. This strategy causes CNTs to be connected to form a conductive layer and enables TiO2 nanoparticles to be bound together to form a porous, heat-reflecting layer. As a consequence, the as-prepared membranes demonstrate high conductivity with an electrical conductivity of 63 S/m, exhibit rapid electric-heating capacity, and exhibit energy-efficient asymmetrical heating behavior, i.e., the heating temperature of the PA/FPU nanofibrous layer reaches more than 83 °C within 90 s at 24 V, while the heating temperature of the FPU/TiO2 layer only reaches 53 °C, as well as prominent superhydrophobicity with a water contact angle of 156°, indicating promising utility for the next generation of electrical heating textiles.

Dehydration-Induced Cluster Consolidation in a Metal-Organic Framework for Sieving Hexane Isomers

Metal-organic frameworks (MOFs) that exhibit dynamic phase-transition behavior under external stimuli could have great potential in adsorptive separations. Here we report on a zinc-based microporous MOF (JNU-80) and its reversible transformation between two crystalline phases: large pore (JNU-80-LP) and narrow pore (JNU-80-NP). Specifically, JNU-80-LP can undergo a dehydration-induced cluster consolidation under heat treatment, resulting in JNU-80-NP with a reduced channel that allows exclusion of di-branched hexane isomers while high adsorption of linear and mono-branched hexane isomers. We further demonstrate the fabrication of MOF-polymer composite (JNU-80-NP-block) and its application in the purification of di-branched isomers from liquid-phase hexane mixtures (98% di-branched) at room temperature, affording the di-branched hexane isomers with 99.5% purity and close to 90% recovery rate over ten cycles. This work illustrates an interesting dehydration-induced cluster consolidation in MOF structure and the ensuing channel shrinkage for sieving di-branched hexane isomers, which may have important implications for the development of MOFs with dynamic behavior and their potential applications in non-thermal driven separation technologies.

Flexible and Energy-Efficient Synaptic Transistor with Quasi-Linear Weight Update Protocol by Inkjet Printing of Orientated Polar-Electret/High-k Oxide Composite Dielectric

Inkjet printing artificial synapse is cost-effective but challenging in emulating synaptic dynamics with a sufficient number of effective weight states under ultralow voltage spiking operation. A synaptic transistor gated by inkjet-printed composite dielectric of polar-electret polyvinylpyrrolidone (PVP) and high-k zirconia oxide (ZrOx) is proposed and thus synthesized to solve this issue. Quasi-linear weight update with a large variation margin is obtained through the coupling effect and the facilitation of dipole orientation, which can be attributed to the orderly arranged molecule chains induced by the carefully designed microfluidic flows. Crucial features of biological synapses including long-term plasticity, spike-timing-dependence-plasticity (STDP), "Learning-Experience" behavior, and ultralow energy consumption (<10 fJ/pulse) are successfully implemented on the device. Simulation results exhibit an excellent image recognition accuracy (97.1%) after 15 training epochs, which is the highest for printed synaptic transistors. Moreover, the device sustained excellent endurance against bending tests with radius down to 8 mm. This work presents a very viable solution for constructing the futuristic flexible and low-cost neural systems.

An Accuracy-Aware Energy-Efficient Multipath Routing Algorithm for WSNs

In the fields of industrial production or safety monitoring, wireless sensor networks are often content with unreliable and time-varying channels that are susceptible to interference. Consequently, ensuring both transmission reliability and data accuracy has garnered substantial attention in recent years. Although multipath routing-based schemes can provide transmission reliability for wireless sensor networks, achieving high data accuracy simultaneously remains challenging. To address this issue, an Energy-efficient Multipath Routing algorithm balancing data Accuracy and transmission Reliability (EMRAR) is proposed to balance the reliability and accuracy of data transmission. The multipath routing problem is formulated into a multi-objective programming problem aimed at optimizing both reliability and power consumption while adhering to data accuracy constraints. To obtain the solution of the multi-objective programming, an adaptive artificial immune algorithm is employed, in which the antibody initialization method, antibody incentive calculation method, and immune operation are improved, especially for the multipath routing scheme. Simulation results show that the EMRAR algorithm effectively balances data accuracy and transmission reliability while also saving energy when compared to existing algorithms.

Organic High-Temperature Synaptic Phototransistors for Energy-Efficient Neuromorphic Computing

Organic optoelectronic synaptic devices that can reliably operate in high-temperature environments (i.e., beyond 121°C) or remain stable after high-temperature treatments have significant potential in biomedical electronics and bionic robotic engineering. However, it is challenging to acquire this type of organic devices considering the thermal instability of conventional organic materials and the degradation of photoresponse mechanisms at high temperatures. Here, high-temperature synaptic phototransistors (HTSPs) based on thermally stable semiconductor polymer blends as the photosensitive layer are developed, successfully simulating fundamental optical-modulated synaptic characteristics at a wide operating temperature range from room temperature to 220°C. Robust optoelectronic performance can be observed in HTSPs even after experiencing 750 h of the double 85 testing due to the enhanced operational reliability. Using HTSPs, Morse-code optical decoding scheme and the visual object recognition capability are also verified at elevated temperatures. Furthermore, flexible HTSPs are fabricated, demonstrating an ultralow power consumption of 12.3 aJ per synaptic event at a low operating voltage of -0.05 mV. Overall, the conundrum of achieving reliable optical-modulated neuromorphic applications while balancing low power consumption can be effectively addressed. This research opens up a simple but effective avenue for the development of high-temperature and energy-efficient wearable optoelectronic devices in neuromorphic computing applications.

Dual-Functional Electrochromic Smart Window Using WO3·H2O-rGO Nanocomposite Ink Spray-Coated on a Low-Cost Hybrid Electrode

Electrochromic windows have gained growing interest for their ability to change their optical state in the visible and NIR ranges with minimal input power, making them energy-efficient. However, material processing costs, fabrication complexity, and poor electrochromic properties can be barriers to the widespread adoption of this technology. To address these issues, electrochromic material and fabrication processes are designed to realize their potential as a cost-effective and energy-efficient technology. In this work, an electrochromic composite material-based ink is synthesized consisting of WO3·H2O nanoplates supported on rGO (reduced graphene oxide) nanosheets (WH-rGO), wherein an optimized amount of rGO (0.05 to 0.5 wt %) is introduced for providing a higher conduction pathway for efficient charge transport without sacrificing the electrochromic performance of WO3·H2O nanoplates. The stable ink dispersion prepared in the study is deposited by spray coating on transparent conducting electrodes over large areas (25 cm2). The WH-rGO nanocomposite (0.4 wt %) results in 43% optical modulation at 700 nm, with bleaching and coloration times of 6 and 8 s, respectively. Interestingly, the device also possesses an electrochemical energy storage capability with an areal capacitance of 16.3 mF/cm2. The electrochromic composite material is successfully translated on tin doped indium oxide (ITO)-coated Al metal mesh hybrid electrodes (T = 80%, Rs = 40 Ω/□) to replace ITO. Finally, an electrochromic device of 5 × 5 cm2 is fabricated by spray-coating the ink on cost-effective ITO/Al-mesh hybrid electrodes. The device displays blue to colorless modulation with an excellent bleaching time of 0.43 s and a coloration time of 2.16 s, making it one among the fast-operating devices fabricated by complete solution processing. This work showcases the economical production of a dual-function electrochromic device, which can be a feasible option as an alternative to existing ITO-based devices in both automotive and infrastructure applications.

A Comparative Assessment of Different Aerogel-Insulated Building Walls for Enhanced Thermal Insulation Performance

Aerogel is widely recognized as a superinsulating material with great potential for enhancing the thermal insulation performance of building walls. It can be applied in various forms such as aerogel plasters (AP), aerogel fibrous composites (AFC), and aerogel concrete (AC) in practical engineering applications. This study aims to investigate the most efficient application form for maximizing building insulation performance while minimizing the amount of aerogel used. To predict the thermal insulation performance of aerogel-insulated walls, a resistance-capacitance network model integrating the aerogels' effective thermal conductivity model was developed and was validated by comparing it with Fluent simulation software results in terms of surface temperature. Using the validated models, the thermophysical parameters, transient thermal properties, and transmission load were predicted and compared among AP, AFC, and AC walls. The results indicate that using AFC can result in approximately 50% cost savings to achieve the same thermal resistance. After adding a 20 mm thickness of aerogel to the reference wall without aerogel, the AFC wall exhibited the highest improvement in thermal insulation performance, reaching 46.0-53.5%, followed by the AP wall, and then the AC wall, aligning with considerations of microstructural perspectives, thermal resistance distributions, and thermal non-uniformity factors. Therefore, giving priority to AFC use could reduce the required amount of silica aerogel and enhance economic efficiency. These results provide valuable insights for theoretical models and the application of aerogel-insulated walls in building engineering insulation.

Joint User Association and Deployment Optimization for Energy-Efficient Heterogeneous UAV-Enabled MEC Networks

Unmanned aerial vehicles (UAVs) providing additional on-demand communication and computing services have become a promising technology. However, the limited energy supply of UAVs, which constrains their service duration, has emerged as an obstacle in UAV-enabled networks. In this context, a novel task offloading framework is proposed in UAV-enabled mobile edge computing (MEC) networks. Specifically, heterogeneous UAVs with different communication and computing capabilities are considered and the energy consumption of UAVs is minimized via jointly optimizing user association and UAV deployment. The optimal transport theory is introduced to analyze the user association sub-problem, and the UAV deployment for each sub-region is determined by a dragonfly algorithm (DA). Simulation results show that the energy consumption performance is significantly improved by the proposed algorithm.

Copper Phosphide Nanowires as High-Performance Catalysts for Urea-Assisted Hydrogen Evolution in Alkaline Medium

Water electrolysis represented a promising avenue for the large-scale production of high-purity hydrogen. However, the high overpotential and sluggish reaction rates associated with the anodic oxygen evolution reaction (OER) posed significant obstacles to efficient water splitting. To tackle these challenges, the urea oxidation reaction (UOR) emerged as a more favorable thermodynamic alternative to OER, offering both the energy-efficient hydrogen evolution reaction (HER) and the potential for the treating of urea-rich wastewater. In this work, a two-step methodology comprising nanowire growth and phosphating treatment was employed to fabricate Cu₃P nanowires on Cu foam (Cu₃P-NW/CF) catalysts. These novel catalytic architectures exhibited notable efficiencies in facilitating both the UOR and HER in alkaline solutions. Specifically, within urea-containing electrolytes, the UOR manifested desirable operational potentials of 1.43 V and 1.65 V versus the reversible hydrogen electrode (vs. RHE) to reach the current densities of 10 and 100 mA cm^-2, respectively. Concurrently, the catalyst displayed a meager overpotential of 60 mV for the HER at a current density of 10 mA cm^-2. Remarkably, the two-electrode urea electrolysis system, exploiting the designed catalyst as both the cathode and anode, demonstrated an outstanding performance, attaining a low cell voltage of 1.79 V to achieve a current density of 100 mA cm^-2. Importantly, this voltage is preferable to the conventional water electrolysis threshold in the absence of urea molecules. Moreover, our study shed light on the potential of innovative Cu-based materials for the scalable fabrication of electrocatalysts, energy-efficient hydrogen generation, and the treatment of urea-rich wastewater.

A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN

Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols.

An Energy-Efficient BJT-Based Temperature Sensor with ±0.8 °C (3σ) Inaccuracy from -50 to 150 °C

This article presents an energy-efficient BJT-based temperature sensor. The output of sensing front-ends is modulated by employing an incremental Δ-Σ ADC as a readout interface. The cascoded floating-inverter-based dynamic amplifier (FIA) is used as the integrator instead of the conventional operational transconductance amplifier (OTA) to achieve a low power consumption. To enhance the accuracy, chopping and dynamic element matching (DEM) are applied to eliminate the component mismatch error while β-compensation resistor and optimized bias current are used to minimize the effect of β variation. Fabricated in a standard 180-nm CMOS process, this sensor has an active area of 0.13 mm2. While dissipating only 45.7 μW in total, the sensor achieves an inaccuracy of ±0.8 °C (3σ) from -50 °C to 150 °C after one-point calibration.

A 7.6-nW 1-kS/s 10-Bit SAR ADC for Biomedical Applications

This paper presents a 10-bit successive approximation register analog-to-digital converter with energy-efficient low-complexity switching scheme, automatic ON/OFF comparator and automatic ON/OFF SAR logic for biomedical applications. The energy-efficient switching scheme achieves an average digital-to-analog converter switching energy of 63.56 CV_ref², achieving a reduction of 95.34% compared with the conventional capacitor switching scheme for CDACs. With the switching scheme, the ADC can lower the dependency on the accuracy of V_cm and complexity of DAC control logic and DAC driver circuit. Moreover, dynamic circuits and automatic ON/OFF technology are used to reduce power consumption of comparator and SAR logic. The prototype is designed and fabricated in a 180 nm CMOS with a core size of 500 μm × 300 μm (0.15 mm²). It consumes 7.6 nW at 1 kS/s sampling rate and 1.8-V supply with an achieved signal-to-noise-and distortion ratio of 45.90 dB and a resulting figure of merit of 51.7 fJ/conv.-step.

Novel Modification of the Collective Dynamic Routing Method for Sensors' Communication in Wi-Fi Public Networks

The widespread use of the Internet of Things makes it relevant to use public IP networks for simultaneous access by both users and wireless sensors. To achieve this, a significant reduction in the subscriber devices' energy consumption is required. This paper analyzes the application features of the collective dynamic routing method both with and without the use of a robust method for estimating the channel data rate for sensors' communication in wireless public networks. Based on the analysis, a novel modification of the collective dynamic routing method has been developed that reduces the sensors' energy consumption while keeping a high data rate and short delivery time for users. An analysis of the network load, the total data transfer rate over the network, and the parameters affecting the sensors' energy consumption was carried out for a segment of a seamless IEEE 802.11ax network. The simulation demonstrated a high efficiency of using a novel modification of the collective dynamic routing method for access to users and wireless sensors.

Tasseled Crop Rows Detection Based on Micro-Region of Interest and Logarithmic Transformation

Machine vision-based navigation in the maize field is significant for intelligent agriculture. Therefore, precision detection of the tasseled crop rows for navigation of agricultural machinery with an accurate and fast method remains an open question. In this article, we propose a new crop rows detection method at the tasseling stage of maize fields for agrarian machinery navigation. The whole work is achieved mainly through image augment and feature point extraction by micro-region of interest (micro-ROI). In the proposed method, we first augment the distinction between the tassels and background by the logarithmic transformation in RGB color space, and then the image is transformed to hue-saturation-value (HSV) space to extract the tassels. Second, the ROI is approximately selected and updated using the bounding box until the multiple-region of interest (multi-ROI) is determined. We further propose a feature points extraction method based on micro-ROI and the feature points are used to calculate the crop rows detection lines. Finally, the bisector of the acute angle formed by the two detection lines is used as the field navigation line. The experimental results show that the algorithm proposed has good robustness and can accurately detect crop rows. Compared with other existing methods, our method's accuracy and real-time performance have improved by about 5 and 62.3%, respectively, which can meet the accuracy and real-time requirements of agricultural vehicles' navigation in maize fields.

Charge Configuration Memory Devices: Energy Efficiency and Switching Speed

Current trends in data processing have given impetus for an intense search of new concepts of memory devices with emphasis on efficiency, speed, and scalability. A promising new approach to memory storage is based on resistance switching between charge-ordered domain states in the layered dichalcogenide 1T-TaS2. Here we investigate the energy efficiency scaling of such charge configuration memory (CCM) devices as a function of device size and data write time τW as well as other parameters that have bearing on efficient device operation. We find that switching energy efficiency scales approximately linearly with both quantities over multiple decades, departing from linearity only when τW approaches the ∼0.5 ps intrinsic switching limit. Compared to current state of the art memory devices, CCM devices are found to be much faster and significantly more energy efficient, demonstrated here with two-terminal switching using 2.2 fJ, 16 ps electrical pulses.

Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843-1864 (1960)] and [J. Sawada, D. S. Modha, "Synapse: Scalable energy-efficient neurosynaptic computing" in Application of Concurrency to System Design (ACSD) (2013), pp. 14-15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a [Formula: see text]-fold discrepancy between biological and lowest possible values of a neuron's computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).

Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSN

Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption.

Development of Energy-Efficient Superhydrophobic Polypropylene Fabric by Oxygen Plasma Etching and Thermal Aging

This study developed a human-friendly energy-efficient superhydrophobic polypropylene (PP) fabric by oxygen plasma etching and short-term thermal aging without additional chemicals. The effect of the microroughness on the superhydrophobicity was examined by adjusting the weave density. After the PP fabric was treated with oxygen plasma etching for 15 min and thermal aging at 120 °C for 1 h (E15H120 1 h), the static contact and shedding angles were 162.7° ± 2.4° and 5.2° ± 0.7° and the energy consumption was 136.4 ± 7.0 Wh. Oxygen plasma etching for 15 min and thermal aging at 120 °C for 24 h (E15H120 24 h) resulted in a static contact and shedding angle of 180.0° ± 0.0° and 1.8° ± 0.2° and energy consumption of 3628.5 ± 82.6 Wh. E15H120 1 h showed a lower shedding angle but had a higher sliding angle of 90°. E15H120 24 h exhibited shedding and sliding angles of less than 10°. Regardless of the thermal aging time, superhydrophobicity was higher in high-density fabrics than in low-density fabrics. The superhydrophobic PP fabric had a similar water vapor transmission rate and air permeability with the untreated PP fabric, and it showed a self-heading property after washing followed by tumble drying and hot pressing.

A Co-Design-Based Reliable Low-Latency and Energy-Efficient Transmission Protocol for UWSNs

Recently, underwater wireless sensor networks (UWSNs) have been considered as a powerful technique for many applications. However, acoustic communications in UWSNs bring in huge QoS issues for time-critical applications. Additionally, excessive control packets and multiple copies during the data transmission process exacerbate this challenge. Faced with these problems, we propose a reliable low-latency and energy-efficient transmission protocol for dense 3D underwater wireless sensor networks to improve the QoS of UWSNs. The proposed protocol exploits fewer control packets and reduces data-packet copies effectively through the co-design of routing and media access control (MAC) protocols. The co-design method is divided into two steps. First, the number of handshakes in the MAC process will be greatly reduced via our forwarding-set routing strategy under the guarantee of reliability. Second, with the help of information from the MAC process, network-update messages can be used to replace control packages through mobility prediction when choosing a route. Simulation results show that the proposed protocol has a considerably higher reliability, and lower latency and energy consumption in comparison with existing transmission protocols for a dense underwater wireless sensor network.

A Biological Retina Inspired Tone Mapping Processor for High-Speed and Energy-Efficient Image Enhancement

In this work, a biological retina inspired tone mapping processor for high-speed and energy-efficient image enhancement has been proposed. To achieve high throughput and high energy efficiency, several hardware design techniques have been proposed, including data partition based parallel processing with S-shape sliding, adjacent frame feature sharing, multi-layer convolution pipelining, and convolution filter compression with zero skipping convolution. Implemented on a Xilinx's Virtex7 FPGA, the proposed design achieves a high throughput of 189 frames per second for 1024 × 768 RGB images while consuming 819 mW. Compared with several state-of-the-art tone mapping processors, the proposed design shows higher throughput and energy efficiency. It is suitable for high-speed and energy-constrained image enhancement applications.

Smart Parking System with Dynamic Pricing, Edge-Cloud Computing and LoRa

A rapidly growing number of vehicles in recent years cause long traffic jams and difficulty in the management of traffic in cities. One of the most significant reasons for increased traffic jams on the road is random parking in unauthorized and non-permitted places. In addition, managing of available parking places cannot achieve the expected reduction in traffic congestion related problems due to mismanagement, lack of real-time parking guidance to the drivers, and general ignorance. As the number of roads, highways and related resources has not increased significantly, a rising need for a smart, dynamic and effective parking solution is observed. Accordingly, with the use of multiple sensors, appropriate communication network and advanced processing capabilities of edge and cloud computing, a smart parking system can help manage parking effectively and make it easier for the vehicle owners. In this paper, we propose a multi-layer architecture for smart parking system consisting of multi-parametric parking slot sensor nodes, latest long-range low-power wireless communication technology and Edge-Cloud computation. The proposed system enables dynamic management of parking for large areas while providing useful information to the drivers about available parking locations and related services through near real-time monitoring of vehicles. Furthermore, we propose a dynamic pricing algorithm to yield maximum possible revenue for the parking authority and optimum parking slot availability for the drivers.

An Energy-Efficient Fall Detection Method Based on FD-DNN for Elderly People

A fall detection module is an important component of community-based care for the elderly to reduce their health risk. It requires the accuracy of detections as well as maintains energy saving. In order to meet the above requirements, a sensing module-integrated energy-efficient sensor was developed which can sense and cache the data of human activity in sleep mode, and an interrupt-driven algorithm is proposed to transmit the data to a server integrated with ZigBee. Secondly, a deep neural network for fall detection (FD-DNN) running on the server is carefully designed to detect falls accurately. FD-DNN, which combines the convolutional neural networks (CNN) with long short-term memory (LSTM) algorithms, was tested on both with online and offline datasets. The experimental result shows that it takes advantage of CNN and LSTM, and achieved 99.17% fall detection accuracy, while its specificity and sensitivity are 99.94% and 94.09%, respectively. Meanwhile, it has the characteristics of low power consumption.

Energy-Efficient Depth-Based Opportunistic Routing with Q-Learning for Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) have aroused increasing interest of many researchers in industry, military, commerce and academe recently. Due to the harsh underwater environment, energy efficiency is a significant theme should be considered for routing in UWSNs. Underwater positioning is also a particularly tricky task since the high attenuation of radio-frequency signals in UWSNs. In this paper, we propose an energy-efficient depth-based opportunistic routing algorithm with Q-learning (EDORQ) for UWSNs to guarantee the energy-saving and reliable data transmission. It combines the respective advantages of Q-learning technique and opportunistic routing (OR) algorithm without the full-dimensional location information to improve the network performance in terms of energy consumption, average network overhead and packet delivery ratio. In EDORQ, the void detection factor, residual energy and depth information of candidate nodes are jointly considered when defining the Q-value function, which contributes to proactively detecting void nodes in advance, meanwhile, reducing energy consumption. In addition, a simple and scalable void node recovery mode is proposed for the selection of candidate set so as to rescue packets that are stuck in void nodes unfortunately. Furthermore, we design a novel method to set the holding time for the schedule of packet forwarding base on Q-value so as to alleviate the packet collision and redundant transmission. We conduct extensive simulations to evaluate the performance of our proposed algorithm and compare it with other three routing algorithms on Aqua-sim platform (NS2). The results show that the proposed algorithm significantly improve the performance in terms of energy efficiency, packet delivery ratio and average network overhead without sacrificing too much average packet delay.

Distributed Reliable and Efficient Transmission Task Assignment for WSNs

Task assignment is a crucial problem in wireless sensor networks (WSNs) that may affect the completion quality of sensing tasks. From the perspective of global optimization, a transmission-oriented reliable and energy-efficient task allocation (TRETA) is proposed, which is based on a comprehensive multi-level view of the network and an evaluation model for transmission in WSNs. To deliver better fault tolerance, TRETA dynamically adjusts in event-driven mode. Aiming to solve the reliable and efficient distributed task allocation problem in WSNs, two distributed task assignments for WSNs based on TRETA are proposed. In the former, the sink assigns reliability to all cluster heads according to the reliability requirements, so the cluster head performs local task allocation according to the assigned phase target reliability constraints. Simulation results show the reduction of the communication cost and latency of task allocation compared to centralized task assignments. Like the latter, the global view is obtained by fetching local views from multiple sink nodes, as well as multiple sinks having a consistent comprehensive view for global optimization. The way to respond to local task allocation requirements without the need to communicate with remote nodes overcomes the disadvantages of centralized task allocation in large-scale sensor networks with significant communication overheads and considerable delay, and has better scalability.

Optically Transparent Wood Substrate for Perovskite Solar Cells

Transparent wood is a candidate for use as an energy-saving building material due to its low density (ca. 1.2 g/cm³), high optical transmittance (over 85% at 1 mm thickness), low thermal conductivity (0.23 W m^-1 K^-1), and good load-bearing performance with tough failure behavior (no shattering). High optical transmittance also makes transparent wood a candidate for optoelectronic devices. In this work, for the first time, perovskite solar cells processed at low temperature (<150 °C) were successfully assembled directly on transparent wood substrates. A power conversion efficiency up to 16.8% was obtained. The technologies demonstrated may pave the way for integration of solar cells with light transmitting wood building structures for energy-saving purposes.

An Energy-Efficien Slotted Sense Multiple Access Broadcast Protocol for Reliable Command Delivery in Dynamic Wireless Sensor Networks

In industrial monitoring and control applications, a server often has to send a command to a node or group of nodes in wireless sensor networks. Flooding achieves high reliability of message delivery by allowing nodes to take the redundancy of receiving the identical message multiple times. However, nodes consume much energy due to this redundancy and the long duty cycle. A reliable slotted broadcast protocol (RSBP) tackles this problem by allocating a distinct broadcast slot (BS) to every node using a tree topology. Not only does it remove collision, but it also minimizes energy consumption such that every node remains active only during its parent’s broadcast slot and its own broadcast slot to receive and rebroadcast a message, respectively. However, it suffers from low reliability in harsh environments due to the compete removal of redundancy and low responsiveness to the changes in network topology due to the global scheduling of slots. Our approach allocates one distinct broadcast sharable slot (BSS) to each tree level, thus making a BSS schedule topology-independent. Then, nodes at the same level compete to rebroadcast a message to nodes at one level higher within the BSS, thus allowing the redundancy. In addition, it uses a slot-scheduled transmission within BSS that can further improve reliability by reducing message collisions and also enables the precise management of energy. According to simulations and experiments, the proposed approach can achieve high reliability comparable to flooding and low-energy consumption comparable to RSBP.

Fully "Erase-free" Multi-Bit Operation in HfO2-Based Resistive Switching Device

Fully "Erase-free" multi-bit operation was demonstrated in a W/HfO₂/TiN-stacked resistive switching device. The term Erase-free means that a digital state in a multi-bit operation can be achieved without initializing the device resistance state when the device moves to another digital state. Because initializing the resistance state of a resistive switching device causes high energy consumption, omitting this sequence can achieve energy efficient multi-bit operation during rewriting of the resistance state of the device. Experimentally, an operational energy savings of up to 75% was confirmed. For stable and reliable Erase-free operation, several prerequisites are required, such as gradual resistance change with electric pulse stimuli during both writing and erasing, predictable operational voltages for certain resistance states, and high reliability of resistive switching. These prerequisites could be achieved by adopting a W top electrode in a W/HfO₂/TiN-stacked resistive switching device. These results can pave the way to future nonvolatile memory applications.

An Integrated Energy-Efficient Wireless Sensor Node for the Microtremor Survey Method

The microtremor survey method (MSM) has the potential to be an important geophysical method for identifying the strata velocity structure and detecting the buried fault structures. However, the existing microtremor exploration equipment has been unable to satisfy the requirements of the MSM, which suffers from low data accuracy, long measurement time, and blind acquisition. In this study, we combined a 2 Hz moving coil geophone with advanced acquisition systems to develop a new integrated energy-efficient wireless sensor node for microtremor exploration. A high-precision AD chip and noise matching technology are used to develop a low-noise design for the sensor node. Dynamic frequency selection technology (DFS) and dynamic power management technology (DPM) are used to design an energy-efficient mode. The data quality monitoring system solves the closed technical flaws between the acquisition systems and the control center via 4G wireless monitoring technologies. According to the results of a series of in situ tests and field measurements, the noise level of the system was 0.7 μV@500 Hz with 0 dB attenuation and 220 mW power consumption of the system in the autonomous data acquisition mode. Therefore, it provides substantial support for the effective data acquisition over long measurement durations in microtremor exploration processes. The applicability of the system is evaluated using field data, according to which the integrated energy-efficient wireless sensor node is convenient and effective for MSM.

An Energy-Efficient and Obstacle-Avoiding Routing Protocol for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks (UASNs) have become one of the promising technologies for exploring underwater natural resources and collecting scientific data from the aquatic environment. As obstacles hinder the communications among sensor nodes in UASNs, designing an effective bypass routing protocol to avoid obstacles is an urgent need. Moreover, the sensor nodes are typically powered by batteries, which are difficult to replace, restricting the network lifetime of UASNs. In this paper, an Energy-efficient and Obstacle-Avoiding Routing protocol (EOAR) is proposed not only to address the issue of marine animals acting as obstacles that interfere with communications, but also to balance the network energy according to the residual energy. In the EOAR protocol, when the current node perceives the existence of marine animals, the interference area of the animal-nodes is first calculated using the underwater acoustic channel model, and then the candidate forwarding relay set of the current node is obtained according to the constraint conditions. The optimal candidate forwarding relay is determined by a fuzzy logic-based forwarding relay selection scheme based on considering the three parameters of the candidate forwarding relay, which includes the propagation delay, the included angle between two neighbor nodes, and the residual energy. Furthermore, in order to solve the problem of energy waste caused by packet collision, we use a priority-based forwarding method to schedule the packet transmission from the candidate forwarding relay to the destination node. The proposed EOAR protocol is simulated on the Aqua-sim platform and the simulation results show that proposed protocol can increase the packet delivery ratio by 28.4% and 11.8% and can reduce the energy consumption by 53.4% and 32.7% and, respectively, comparing with the hop-by-hop vector-based forwarding routing protocol (HHVBF) and void handling using geo-opportunistic routing protocol (VHGOR).

Nonelectric Sustaining Bistable Polymer Framework Liquid Crystal Films with a Novel Semirigid Polymer Matrix

In this work, a bistable polymer framework liquid crystal (PFLC) thin film by thermal curing of epoxy monomers with two different thiols, a traditional flexible-structure thiol and a novel original rigid-structure thiol, has been successfully fabricated, combining a novel mixed morphology of polymer matrix and cholesteric liquid crystals with negative dielectric anisotropy. The polymer framework morphology has been formed by curing two types of epoxy monomers with two types of thiols, and the liquid crystals tend to be focal conic textures with large size domains at the initial state in the PFLC film so that it has a moderate light transmissivity at this state between the transparent state and the opaque state. Thus, the devices based on PFLC films can be switched reversibly between the transparent state and the opaque state by alternative electric field. In addition, the states can be sustained after the electric field is removed. The bistable memory effect comes from the anchoring effects of the polymer frameworks with a novel morphology in the microdomains of the PFLCs. Therefore, the optimized bistable PFLC film keeps its initial state without external electric field and any other energy consumption for a long time after altering the state by applying an instant electric field. The special polymer frameworks in the bistable PFLC films endow the films with excellent electro-optical properties and mechanical properties. The devices are energy-efficient and cost-saving and have great potential applications in energy-efficient reflective displays, electronic papers, writing tablets, and smart windows.

A Dependable Localization Algorithm for Survivable Belt-Type Sensor Networks

As the key element, sensor networks are widely investigated by the Internet of Things (IoT) community. When massive numbers of devices are well connected, malicious attackers may deliberately propagate fake position information to confuse the ordinary users and lower the network survivability in belt-type situation. However, most existing positioning solutions only focus on the algorithm accuracy and do not consider any security aspects. In this paper, we propose a comprehensive scheme for node localization protection, which aims to improve the energy-efficient, reliability and accuracy. To handle the unbalanced resource consumption, a node deployment mechanism is presented to satisfy the energy balancing strategy in resource-constrained scenarios. According to cooperation localization theory and network connection property, the parameter estimation model is established. To achieve reliable estimations and eliminate large errors, an improved localization algorithm is created based on modified average hop distances. In order to further improve the algorithms, the node positioning accuracy is enhanced by using the steepest descent method. The experimental simulations illustrate the performance of new scheme can meet the previous targets. The results also demonstrate that it improves the belt-type sensor networks’ survivability, in terms of anti-interference, network energy saving, etc.

Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review

Wireless sensor networks (WSNs) can be used in agriculture to provide farmers with a large amount of information. Precision agriculture (PA) is a management strategy that employs information technology to improve quality and production. Utilizing wireless sensor technologies and management tools can lead to a highly effective, green agriculture. Based on PA management, the same routine to a crop regardless of site environments can be avoided. From several perspectives, field management can improve PA, including the provision of adequate nutrients for crops and the wastage of pesticides for the effective control of weeds, pests, and diseases. This review outlines the recent applications of WSNs in agriculture research as well as classifies and compares various wireless communication protocols, the taxonomy of energy-efficient and energy harvesting techniques for WSNs that can be used in agricultural monitoring systems, and comparison between early research works on agriculture-based WSNs. The challenges and limitations of WSNs in the agricultural domain are explored, and several power reduction and agricultural management techniques for long-term monitoring are highlighted. These approaches may also increase the number of opportunities for processing Internet of Things (IoT) data.

A Critical Review of Surveys Emphasizing on Routing in Wireless Sensor Networks-An Anatomization under General Survey Design Framework

A large number of routing-related surveys are published so far for Wireless Sensor Networks (WSNs) that exhibit either complete or partial emphasis on routing in WSNs. These surveys classify and discuss the relevant routing protocols published mainly in the fields of classical, energy efficient, secure, hierarchical, geographic, intelligent, Quality of Service (QoS)-based and multipath WSNs. However, to the best of our knowledge, no study is presented so far which may clearly categorize the routing-related survey literature for WSNs.To fill this gap, an effort is made in this paper for presenting an in-depth review of already published routing-related survey literature in WSNs. Our review initially proposes a generalized survey design model and afterwards analyzes the routing-related survey literature in the light of the devised General Survey Design Framework (GSDF). Such an analysis describes the design soundness of the published routing-related surveys. Therefore, our review puts forth an original classification based on the frequency-of-survey-publication and taxonomizes the corresponding routing-related fields into high, medium and low focused areas of survey publication in WSNs. Furthermore, the surveys belonging to each main category are sub-categorized into various sub-classes and briefly discussed according to their design characteristics. On the one hand, this review is useful for beginners who may easily explore the already published routing-related survey literature in WSNs in a single document and investigate it by spending less effort. On the other hand, it is useful for expert researchers who may explore the trends and frequency of writing surveys in different areas of routing in WSNs. The experts may explore those areas of routing which are either neglected or least focused or lack in design soundness as per general survey design framework. In the end, insights and future research directions are outlined and a reasonable conclusion is put forth which may outline guiding principles for routing-related survey research in future.

Low Duty-Cycling MAC Protocol for Low Data-Rate Medical Wireless Body Area Networks

Wireless body area networks (WBANs) are severely energy constrained, and how to improve the energy efficiency so as to prolong the network lifetime as long as possible is one of the most important goals of WBAN research. Low data-rate WBANs are promising to cut down the energy consumption and extend the network lifetime. Considering the characteristics and demands of low data-rate WBANs, a low duty-cycling medium access control (MAC) protocol is specially designed for this kind of WBAN in this paper. Longer superframes are exploited to cut down the energy consumed on the transmissions and receptions of redundant beacon frames. Insertion time slots are embedded into the inactive part of a superframe to deliver the frames and satisfy the quality of service (QoS) requirements. The number of the data subsections in an insertion time slot can be adaptively adjusted so as to accommodate low data-rate WBANs with different traffic. Simulation results show that the proposed MAC protocol performs well under the condition of low data-rate monitoring traffic.

A Survey on an Energy-Efficient and Energy-Balanced Routing Protocol for Wireless Sensor Networks

Wireless sensor networks (WSNs) form an important part of industrial application. There has been growing interest in the potential use of WSNs in applications such as environment monitoring, disaster management, health care monitoring, intelligence surveillance and defence reconnaissance. In these applications, the sensor nodes (SNs) are envisaged to be deployed in sizeable numbers in an outlying area, and it is quite difficult to replace these SNs after complete deployment in many scenarios. Therefore, as SNs are predominantly battery powered devices, the energy consumption of the nodes must be properly managed in order to prolong the network lifetime and functionality to a rational time. Different energy-efficient and energy-balanced routing protocols have been proposed in literature over the years. The energy-efficient routing protocols strive to increase the network lifetime by minimizing the energy consumption in each SN. On the other hand, the energy-balanced routing protocols protract the network lifetime by uniformly balancing the energy consumption among the nodes in the network. There have been various survey papers put forward by researchers to review the performance and classify the different energy-efficient routing protocols for WSNs. However, there seems to be no clear survey emphasizing the importance, concepts, and principles of load-balanced energy routing protocols for WSNs. In this paper, we provide a clear picture of both the energy-efficient and energy-balanced routing protocols for WSNs. More importantly, this paper presents an extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols. A taxonomy is introduced in this paper to classify the surveyed energy-efficient and energy-balanced routing protocols based on their proposed mode of communication towards the base station (BS). In addition, we classified these routing protocols based on the solution types or algorithms, and the input decision variables defined in the routing algorithm. The strengths and weaknesses of the choice of the decision variables used in the design of these energy-efficient and energy-balanced routing protocols are emphasised. Finally, we suggest possible research directions in order to optimize the energy consumption in sensor networks.

A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks

For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes' being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network's best service quality and lifetime.

A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network

Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i) how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii) how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA) based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods.

An Energy-Efficient Skyline Query for Massively Multidimensional Sensing Data

Cyber physical systems (CPS) sense the environment based on wireless sensor networks. The sensing data of such systems present the characteristics of massiveness and multi-dimensionality. As one of the major monitoring methods used in in safe production monitoring and disaster early-warning applications, skyline query algorithms are extensively adopted for multiple-objective decision analysis of these sensing data. With the expansion of network sizes, the amount of sensing data increases sharply. Then, how to improve the query efficiency of skyline query algorithms and reduce the transmission energy consumption become pressing and difficult to accomplish issues. Therefore, this paper proposes a new energy-efficient skyline query method for massively multidimensional sensing data. First, the method uses a node cut strategy to dynamically generate filtering tuples with little computational overhead when collecting query results instead of issuing queries with filters. It can judge the domination relationship among different nodes, remove the detected data sets of dominated nodes that are irrelevant to the query, modify the query path dynamically, and reduce the data comparison and computational overhead. The efficient dynamic filter generated by this strategy uses little non-skyline data transmission in the network, and the transmission distance is very short. Second, our method also employs the tuple-cutting strategy inside the node and generates the local cutting tuples by the sub-tree with the node itself as the root node, which will be used to cut the detected data within the nodes of the sub-tree. Therefore, it can further control the non-skyline data uploading. A large number of experimental results show that our method can quickly return an overview of the monitored area and reduce the communication overhead. Additionally, it can shorten the response time and improve the efficiency of the query.

A Secure Routing Protocol for Wireless Sensor Networks Considering Secure Data Aggregation

The commonly unattended and hostile deployments of WSNs and their resource-constrained sensor devices have led to an increasing demand for secure energy-efficient protocols. Routing and data aggregation receive the most attention since they are among the daily network routines. With the awareness of such demand, we found that so far there has been no work that lays out a secure routing protocol as the foundation for a secure data aggregation protocol. We argue that the secure routing role would be rendered useless if the data aggregation scheme built on it is not secure. Conversely, the secure data aggregation protocol needs a secure underlying routing protocol as its foundation in order to be effectively optimal. As an attempt for the solution, we devise an energy-aware protocol based on LEACH and ESPDA that combines secure routing protocol and secure data aggregation protocol. We then evaluate its security effectiveness and its energy-efficiency aspects, knowing that there are always trade-off between both.

An ultra-low power wireless sensor network for bicycle torque performance measurements

In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach.

A Fully-Implantable Cochlear Implant SoC with Piezoelectric Middle-Ear Sensor and Arbitrary Waveform Neural Stimulation

A system-on-chip for an invisible, fully-implantable cochlear implant is presented. Implantable acoustic sensing is achieved by interfacing the SoC to a piezoelectric sensor that detects the sound-induced motion of the middle ear. Measurements from human cadaveric ears demonstrate that the sensor can detect sounds between 40 and 90 dB SPL over the speech bandwidth. A highly-reconfigurable digital sound processor enables system power scalability by reconfiguring the number of channels, and provides programmable features to enable a patient-specific fit. A mixed-signal arbitrary waveform neural stimulator enables energy-optimal stimulation pulses to be delivered to the auditory nerve. The energy-optimal waveform is validated with in-vivo measurements from four human subjects which show a 15% to 35% energy saving over the conventional rectangular waveform. Prototyped in a 0.18 μm high-voltage CMOS technology, the SoC in 8-channel mode consumes 572 μW of power including stimulation. The SoC integrates implantable acoustic sensing, sound processing, and neural stimulation on one chip to minimize the implant size, and proof-of-concept is demonstrated with measurements from a human cadaver ear.

Energy-efficient Optimization of Reorganization-Enabled Wireless Sensor Networks

This paper studies the target tracking problem in wireless sensor networks where sensor nodes are deployed randomly. To achieve tracking accuracy constrained by energy consumption, an energy-efficient optimization approach that enables reorganization of wireless sensor networks is proposed. The approach includes three phases which are related to prediction, localization and recovery, respectively. A particle filter algorithm is implemented on the sink node to forecast the future movement of the target in the first prediction phase. Upon the completion of this phase, the most energy efficient sensor nodes are awakened to collaboratively locate the target. Energy efficiency is evaluated by the ratio of mutual information to energy consumption. The recovery phase is needed to improve the robustness of the approach. It is performed when the target is missed because of the incorrect predicted target location. In order to recapture the target by awakening additional sensor nodes as few as possible, a genetic-algorithm-based mechanism is introduced to cover the recovery area. We show that the proposed approach has excellent tracking performance. Moreover, it can efficiently reduce energy consumption, prolong network lifetime and reduce network overheads.