Tiny Battery Research Articles

A microscale soft lithium-ion battery for tissue stimulation

AbstractAdvances in the development of tiny devices with sizes below a few cubic millimeters require a corresponding decrease in the volume of driving power sources. To be minimally invasive, prospective power sources in biomedical devices must be fabricated from soft materials. Previous endeavors with droplet-based devices have produced promising miniature power sources; however, a droplet-based rechargeable battery has remained out of reach. Here we report a microscale soft flexible lithium-ion droplet battery (LiDB) based on the lipid-supported assembly of droplets constructed from a biocompatible silk hydrogel. Capabilities such as triggerable activation, biocompatibility and biodegradability and high capacity are demonstrated. We have used the LiDB to power the electrophoretic translocation of charged molecules between synthetic cells and to mediate the defibrillation and pacing of ex vivo mouse hearts. By the inclusion of magnetic particles to enable propulsion, the LiDB can function as a mobile energy courier. Our tiny versatile battery will thereby enable a variety of biomedical applications.

Tiny batteries for tiny robots

Tiny batteries for tiny robots

Tiny Machine Learning Battery State-of-Charge Estimation Hardware Accelerated

Tiny Machine Learning Battery State-of-Charge Estimation Hardware Accelerated

Drone Technology and it’s Application

Drones were first used by the military, but now they're not just for the army – they're for regular folks too. People started using them in the 2000s, and they're not just for serious stuff like analyzing power system faults. Now, we call them drones, and they're like flying robots. You can use them for all kinds of fun things like taking cool pictures, exploring hard-to- reach places, and even joining drone competitions. They've become a big deal on social media and in business competitions. Lately, smart people are working on making tiny drones that can fly by themselves, especially in indoor spaces. The good news is that the parts that make drones work, like tiny computers, sensors, batteries, and ways for them to talk wirelessly, are getting smaller and cheaper. So, soon, we might see small drones everywhere, doing all sorts of stuff in our daily lives at prices we can all afford. But, as drones become more popular, there are some worries. Imagine if someone used a drone to spy on you in your private space – that's not cool! And when drones fly in busy places like cities and airports, there could be problems. That's why we need rules and checks to make sure things don't go wrong. So, while drones are super cool and fun, we also need to make sure everyone stays safe and feels secure. Keywords--Unmanned Aerial Vehicle, Drone, Drone Features, Technology, Drone usage fields.

Energy Efficient Quantum-Informed Ant Colony Optimization Algorithms for Industrial Internet of Things

One of the most prominent research areas in information technology is the Internet of things (IoT) as its applications are widely used such as structural monitoring, health care management systems, agriculture and battlefield management, and so on. Due to its self-organizing network and simple installation of the network, the researchers have been attracted to pursue research in the various fields of IoTs. However, a huge amount of work has been addressed on various problems confronted by IoT. The nodes densely deploy over critical environments and those are operated on tiny batteries. Moreover, the replacement of dead batteries in the nodes is almost impractical. Therefore, the problem of energy preservation and maximization of IoT networks has become the most prominent research area. However, numerous state-of-the-art algorithms have addressed this issue. Thus, it has become necessary to gather the information and send it to the base station in an optimized method to maximize the network. Therefore, we propose a novel quantum-informed ant colony optimization (ACO) routing algorithm with the efficient encoding scheme of cluster head selection and derivation of information heuristic factors. The algorithm has been tested by simulation for various network scenarios. The simulation results of the proposed algorithm show its efficacy over a few existing evolutionary algorithms using various performance metrics such as residual energy of the network, network lifetime, and the number of live IoT nodes.

Five Level H-Bridge Configuration Based Microgrid with Sugeno Fuzzy Controller for New Energy Generation from Renewable Systems

Hybrid microgrids run by renewable energy sources are gaining popularity around the world. Solar (PV) and permanent magnet synchronous generator (PMSG) based wind energy systems (WES) are well-known and easy to install renewable energy options. Unfortunately, wind speeds and solar irradiance levels fluctuate unpredictably. Energy generation from both WES and PV panels must therefore fluctuate. Simultaneously, the load is fluctuating irregularly. Hence, storage devices must be incorporated into hybrid systems in order to keep the generation and consumption of electricity in equilibrium. In addition, for a fuel cell and electrolyzer that run on hydrogen, a tiny battery is added into the system to keep costs down. In order to enhance power quality and reliability, all the components in a microgrid need to be connected to an effective energy management system. For optimal use, renewable energy sources are combined with maximum power point trackers. When there are sudden shifts in both the energy supply and demand on a standalone microgrid, the energy balance and frequency response are crucial. In this study, a Takagi Sugeno based innovative fuzzy controller is implemented for a system to manage energy in order to achieve a precious and rapid reaction. The suggested system's Hardware-In-the-Loop is built using OPAL-RT modules in order to demonstrate detailed findings.

Intrusion detection method for internet of things based on the spiking neural network and decision tree method

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices’ power usage. Also, a rand order code (ROC) technique is used with SNN to detect cyber-attacks. The proposed method is evaluated by comparing its performance with two other methods: IDS-DNN and IDS-SNNTLF by using three performance metrics: detection accuracy, latency, and energy usage. The simulation results have shown that IDS-SNNDT attained low power usage and less latency in comparison with IDS-DNN and IDS-SNNTLF methods. Also, IDS-SNNDT has achieved high detection accuracy for cyber-attacks in contrast with IDS-SNNTLF.

A Comparative Analysis of ANN-based Homogeneous and Heterogeneous Routing Protocols for Selection of Cluster Head in WSN

Background: WSNs are composed of various tiny low battery power Sensor Nodes (SNs). It is required to sense the dynamic network environments, which may fluctuate due to external factors or the system model itself. Furthermore, sensory data is transmitted over the communication channel to the destination. Integration of Artificial Neural Network (ANN) in WSNs provides the facility to learn SNs and networks from past experiences and make the predictions based on them. The computational ability of ANN may help to choose an efficient route for data transfer in WSNs. Also, it is able to improve the performance of the network w.r.t power consumption, latency, throughput, etc. This work explores an efficient way to manage the energy of the SNs using an ANN-based routing approach for the selection of Cluster Head (CH). Methods: In this work, an ANN-based and algorithmic approach has been applied to select the CH. Various popular routing strategies such as LEACH-C, TEEN, SEP & DEEC have been used for simulation. LEACH-C and TEEN belong to the homogeneous category, while SEP and DEEC are categorized as heterogeneous. ANN based CH selection strategy has been proposed and compared with the other routing techniques. Results: ANN based CH selection strategy has been simulated and compared. Results revealed that CH election based on ANN will enhance the network lifetime. It is clear from the simulation results that ANN-DEEC is much more stable than protocols of the same category. Conclusion: ANN-DEEC outperforms five times more than LEACH-C, 2.5 times more than TEEN and SEP, twice DEEC and 10-20% more than EDDEC and Advanced-DEEC. ANN-DEEC transmits 71021 packets to BS more than any other protocol. other: Thanks

Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks.

Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project’s aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes.

FaceBit

The COVID-19 pandemic has dramatically increased the use of face masks across the world. Aside from physical distancing, they are among the most effective protection for healthcare workers and the general population. Face masks are passive devices, however, and cannot alert the user in case of improper fit or mask degradation. Additionally, face masks are optimally positioned to give unique insight into some personal health metrics. Recognizing this limitation and opportunity, we present FaceBit: an open-source research platform for smart face mask applications. FaceBit's design was informed by needfinding studies with a cohort of health professionals. Small and easily secured into any face mask, FaceBit is accompanied by a mobile application that provides a user interface and facilitates research. It monitors heart rate without skin contact via ballistocardiography, respiration rate via temperature changes, and mask-fit and wear time from pressure signals, all on-device with an energy-efficient runtime system. FaceBit can harvest energy from breathing, motion, or sunlight to supplement its tiny primary cell battery that alone delivers a battery lifetime of 11 days or more. FaceBit empowers the mobile computing community to jumpstart research in smart face mask sensing and inference, and provides a sustainable, convenient form factor for health management, applicable to COVID-19 frontline workers and beyond.

Research and classification of wireless power transfer with relative application

In this paper, wireless power transfer (WPT) will be discussed in its research and application. The basic information like the reason why devices choose to use wireless power and the concept of typical WPT types is introduced. The wireless power transfer system can be divided into 5 diverse types by the theory of power transmitting, and the working principle will be introduced separately. Then, the detail of WPT via magnetically-coupled resonance is mainly discussed, including the analyzing methods, optimization scheme and the current problems. Finally, this paper give two examples on medical use and mobile phone battery charging. Using the technology of WPT, the problem of the medical tiny robots battery charging is solved, and it provides a more convenient method of charging the mobile phones without the cables. The wireless power transfer technique has potential advantages and broad prospects, which is of vital significance in power transfer development.

Energy Efficient Routing Protocall By One Way Multi-Hope Sensor Nodes

Multi-hope is widely used for data aggregation and transmission in various applications. The resource availability determines the life time of a WSN. Sensor nodes are powered by a tiny battery that supplies the required energy for the sensor and transmitter. The residual energy available at any moment decides the fitness of the sensor node. The sensor node senses the environment and transmits the data to the sink. Efficient data transmission and aggregation with less energy consumption can prolong the lifetime of the sensor network. The sensor node that is inside the coverage area of the sink can directly transmit the data to sink in a single-hop transmission. The sensor node that is not inside the coverage area should transmit the data to the neighbor node which is in the coverage area of the sink. The data is then turn transmitted by the node close to it fall in multi-hop transmission involving a number of intermediate nodes to forward the data to the sink and consumes extra energy for the forwarding process. The formation clusters and data transmission of data by Cluster Heads (CH) can eliminate many nodes involved in the transmission of same data. Clusters are a group of self-organized nodes in a geographic location that can communicate among them. A node in a cluster with higher residual energy will be acting as CH and all other nodes in the cluster transmit the data to the CH. The CH transmits the aggregated data to the sink. The CH transmits the data to the sink either in single-hop transmission or multi-hop transmission. The cluster head consumes more energy than other nodes in the cluster as it is involved in aggregation and transmission process.

Tiny robots and sensors need tiny batteries - here's how to do it.

Improve materials and architectures to shrink microscopic devices. Improve materials and architectures to shrink microscopic devices.

REVIEW OF ENERGY MINIMIZATION TECHNIQUES IN WIRELESS SENSORS NETWORK

The current decade of technology trends adopted the utilization of wireless sensors network. The wireless sensors network integrates with cloud based services and facilitate in every field of social engineering. The success story of sensors based network is utilization of energy. The sensor devices occupied tiny battery for energy. If the energy utilization is not maintained the life of network is expire. In this paper present the review of energy based protocol used in wireless sensor network. The maximum utilization of energy during the sensing of data of sensors node. Some authors used dual duty cycle for the sensing of sensor data and transmit data to sink node.

Record-breaking thin-film battery

A tiny new battery that packs an energy punch could power more compact next-gen pacemakers and other medical devices. The LiCoO2 battery was developed by researchers at CEA-Leti, part of the French atomic energy agency. Battery chemist Sami Oukassi says it has a higher energy density than any thin-film battery reported so far. The battery is just 3.10 by 1.70 mm in area—which doesn’t leave much room for energy-storing electrode materials. Oukassi says his group improved the thin-film battery’s performance by making a thicker layer of LiCoO2 at higher yield. Thin-film batteries generally use less than 10 µm of the material; the CEA-Leti group was able to double this value while still achieving good-quality films that provide an easy path for charge-carrying lithium ions. “We developed advanced patterning methods for this material—usually you can’t do that on lithium,” Oukassi says. That enabled the team to make a prototype battery that

ENERGY COMPETENCY FOR GEOGRAPHICAL ROUTING SCHEME USING DUTY CYCLED WIRELESS SENSOR NETWORK

Wireless sensor networks have wide range of applications. The major constraint in such application lies in the limitation of energy resource. The sensors are often equipped with tiny and irreplaceable batteries. It arise the need of energy efficient routing algorithms to prolong the network lifetime. This project mainly focuses on sleep scheduling for geographic routing in duty-cycled WSNs with mobile sensors by using geographic-distance-based connected-k neighborhood (GCKN) sleep scheduling algorithms. It ensures that coverage rotates such every purpose within the surroundings is perceived at intervals some default interval of your time, referred to as the detection delay. The structure is optimized for rare event detection and permits favorable compromises to be achieved between event detection delays and eventual coverage for every purpose. The cluster activation protocol makes sure that the foremost potential clusters activated to perform target pursuit, reducing consumed energy throughout the hand-off operation. The experimental results show that when there are mobile sensors, geographic routing can achieve much shorter average lengths for all paths using GCKN sleep scheduling compared with those in WSNs employing CKN and GSS sleep scheduling.

Striking a Balance Between System Throughput and Energy Efficiency for UAV-IoT Systems

The proliferation of Internet of Things (IoT) systems provides us a formidable way to monitor a multitude of things by recording field data and delivering it to the faraway controlling center. However, in hostile or inaccessible areas without infrastructure supports, transmission of IoT data is a daunting task due to the limited physical constraints associated with the weak communication unit and tiny battery supply at the ground sensors. A feasible solution to this problem is to use flexible and programmable unmanned aerial vehicles (UAVs) to gather the ground IoT data and then relay it to the end user, forming a UAV-IoT data collection system. Nevertheless, as we reveal in this article, there is a tradeoff between the two performance metrics—system throughput and sensor energy efficiency. Therefore, the data collection for UAV-IoT system should be power-aware, i.e., expending just enough energy to achieve the required system performance. To this end, in this article, by locating the optimal system parameters—the UAV flying speed and altitude, as well as the frame length at the MAC layer, we can strike a balance between the two conflicting metrics, in that, we can maximize the energy efficiency at the ground sensors, while satisfying the required system performance at the same time. In addition, with a cross-layer design, we can adaptively tune the frame length at MAC layer according to the varying UAV flying speed at the PHY layer, thus promptly switching the system between “system-efficient mode” and “energy-efficient mode.”

Implementation of ITREE-MAC Protocol for Effective Power Management and Time Synchronization in Wireless Sensor Networks

The advent of wireless sensor networks (WSN) has led in recent revolutionary modifications in electronic and communication systems .Various applications in wireless network needs time synchronization as a basic requirement. Wireless sensor nodes are tiny in size and operated at low energy to record the required physical parameters for low-duty apps. Because nodes have a tiny battery with a lower life span, power management is crucial for long-term working with the sensors. Wireless Sensor Network is a set of sensor nodes used to send and receive data packets from one sensor node to another. This work aims to propose three protocols such as Receiver Centric MAC protocol (RC-MAC), Improved Receiver Centric MAC protocol (IRC-MAC) and Intelligent Traffic and Resource Elastic Energy MAC protocol (ITREE-MAC) for the WSN environment and based on the application. These protocols help in studying the parametric measures such as delay, energy consumption, packet delivery ratio and throughput. The comparative analysis is carried out to select the more efficient protocol for the application of wireless sensor networks. This research work is implemented and simulated by using NS 2.35 Simulator. Based on the simulation results obtained for proposed protocols using the NS2 simulator. The performance of ITREE-MAC protocol shows better results for parameters end to end delay, energy consumption, throughput, packet delivery ratio. So the overall performance of ITREE-MAC protocol is much better than other three IEEE802.11 MAC, RC-MAC and IRC-MAC protocols. As per results obtained, energy consumption is less in ITREE-MAC protocol and save the power in wireless sensor network applications

Stability and Design Limits of Hysteretic Current-mode Switched-inductor Converters

Emerging wireless microsystems rely on tiny batteries and intermittent energy-harvesting sources for energy and power. To sense, process, and report numerous events across extended periods, they often idle and wake to full-power conditions. Their power supplies must therefore be compact and efficient and respond quickly to sudden wide load changes. Hysteretic current-mode switched-inductor dc–dc converters are good for this application space because they are compact, efficient, and fast. Although also widely stable, they are nevertheless subject to instabilities. This paper explains how input and output voltages and load dumps limit stability, and as a result, bandwidth and response time. Measurements of a 200-mA, 1-V, 0.18-μm CMOS hysteretic current-mode buck with 95% peak powerconversion efficiency show how increasing the loaddump step by 140 mA and decreasing the input voltage by 400 mV compromise stability.

Energy Efficient NK-RLE Data Compression Scheme

Wireless sensor network vigorous research area now a day .In WSN sensor nodes are outfitted with tiny batteries having low power where power conservation is main concern to increase the network life time. In order to conserve energy by reduce the data to be send from sense nodes to sink node. Data compression is effective and well known technique, to get better compression results with varied data from data sources it is essential to introduce competent processing technique. In this paper we proposed improved data compression schemes motivated from RLE and K RLE. The proposed algorithm enhances the compression ratio in comparison of K-RLE and RLE. The result shows that our compression algorithms efficiently enhance the data compression ratio and hence improving energy efficiency in WSNs.