Low Battery Life Research Articles

IQL‐OCDA: An intelligent Q‐learning‐based for optimal clustering and data‐aggregation for wireless sensor networks

AbstractWireless sensor networks (WSNs) can suffer from low battery life due to the energy consumption of the routing protocol. Small sensor nodes are often difficult to recharge after deployment. In a WSN, data aggregation is generally used to reduce or eliminate data redundancy between nodes in order to save energy. In the proposed algorithm, sensor nodes are deployed in appropriate clusters and cluster heads are elected using Q‐learning techniques. Nodes are clustered based on the mean values computed during the clustering phase. Lastly, a performance evaluation and comparison of existing clustering algorithms are performed based on Intelligent Q‐learning. The proposed IQL‐OCDA model reduces end‐to‐end delay by 10.11%, increases throughput by 4.15%, and increases network lifetime by 5.1%.

WHY GOOGLE GLASSES FAILED?

In this research paper we are basically trying to find out why Google Glasses failed as a product in the market. Google Glasses was launched back in 2012 as a product that created a lot of buzz in the market as “Wearable Smart Glasses”. But it never managed to effectively capitalise on the hype that surrounded the product and failed in capturing the market share and did not turn out as a money-making product. On the contrary, Google lost $895 million and incurred heavy losses and ultimately had to give up on the product. It failed to captivate the imagination of the people and people were not really interested in the product. When we dig deeper into the problem, we found several loopholes and flaws in the product, and in the basic business idea on the fundamental level. First of all, the designers of the idea and the product lacked the clarity as to whether the glasses would be considered as a fashionable device or just stand out as a utilitarian product. The problem was also with the price of the product, as this was so expensive that only the rich could afford and hence inaccessible to the masses and a limited target market. The people were also concerned with the privacy aspect as the current generation is quite conscious about their data being recorded and people did not really like this aspect of Google Glasses. People were even concerned with the safety of this product. People were not really great fans of the design of the glasses and generally regarded the product as uncool. Moreover, the grim problem of low battery life on the glasses was another major flaw. Nobody likes it, if they have to charge their product every now and then, it really drops the satisfaction level, and this happened with Google Glasses as well. The design of the glasses was unappealing and the glasses regularly faced heating and language issues. So overall these were the factors we found out that contributed in the product ending up as a huge failure in the market, despite the fact that it had a huge brand value as the likes of Google backing it up.

Electrochemical Impedance Spectroscopy of Li‐S Batteries: Effect of Atomic Vanadium‐ and Cobalt‐Modified Ketjen Black‐Sulfur Cathode, Sulfur Loading, and Electrolyte‐to‐Sulfur Ratio

AbstractThe polysulfide shuttle mechanism and insulating characteristics of sulfur and discharge products are the two major drawbacks of Li−S batteries. These increase internal cell resistances, resulting in low battery performance and life. In this study, we investigate the effect of cathode material on the cell resistances by preparing two different cathodes: by encapsulating sulfur (S) with pure Ketjen black (KBS) and with atomic vanadium and cobalt‐modified Ketjen black (VCKBS). In addition to the cathode material, the influence of crucial cell design parameters, namely electrolyte‐to‐sulfur (E/S) ratio and sulfur loading, on the cell resistances and battery performance is also compared. Electrochemical impedance spectroscopy (EIS) is applied to determine the individual cell resistances, whereas a system‐level performance model is used to estimate the system‐level specific energies and energy densities. The comparison of the cathodes shows that VCKBS significantly improves both cell‐ and system‐level performances, which are attributed to a significant decrease in cell resistances. The cells with higher sulfur loadings and lower E/S ratios show poorer performance for both cathodes. On the other hand, an E/S ratio of 6 mg L−1 can result in high cell‐ and system‐level performances for the VCKBS cathode.

Virtual Smartphones: Exploring the Evolution and Impact of Virtualization Technology on Mobile Devices

With the ability to fully immerse users in a virtual environment, virtual reality (VR) has grown in popularity among consumers in recent years. Technology has grown to be one of the most significant tools for communication, which is to be expected to change how companies advertise their goods and services to prospective clients. The purpose of this study is to look at how virtual smartphones: exploring the evolution and impact of virtualization technology on mobile devices perceived usefulness and enjoyment influence customers’ future intention. Nowadays, smartphones are used in the majority of human tasks in daily life, making work easier for people. The work may involve communicating with a different business via video conferencing, emailing documents, using a Google Map to find a place, etc. We all know that smartphones are useful, but occasionally users find it difficult to use them because of a lack of resources. Less storage space, a slow processor, low battery life, etc. are some of the issues. In this work, we present VSP, or Virtual Smart Phone, which is essentially a step toward connecting the real and virtual worlds over the internet with a small projector, camera, speaker, microphone, and cloud computing technology.

Development and Optimization of a Wireless Power Charging System for an Inspection Drone

Unmanned aerial vehicles (UAVs) have advanced and are now employed in a variety of industries, including aerial photography, the military, and transportation. Due to its low battery life, charging it can be difficult. A good UAV solution has been thought of as wireless charging. In this research, we suggested an inductively coupled wireless power transmission system (WPT) and examined the inductive coupling’s power efficiency. A portable energy receiving device positioned on the base of the UAV and a charging station with an induction coil array were both included in the WPT. Additionally, the WPT equivalent circuit was used to examine power efficiency, and a prototype model of the battery coupled with a quadcopter for testing power efficiency was developed. The results onboard the charging circuit design contributed with polarity modulation and safety charging the battery pack, with very light components that considerably decrease the size and weight as much as possible. The charging power conversion efficiency has achieved 83.76% at the maximum.

Communication and computational resource optimization for Industry 5.0 smart devices empowered by MEC

Smart devices in Industry 5.0, such as sensors and robots, are often limited by low battery life and finite computational resources, hindering their ability to perform complex tasks. By offloading computation-intensive tasks to Mobile Edge Cloud Computing (MEC) servers at the network’s edge, businesses can achieve real-time data processing and analysis, reducing communication latency, quicker response times, and improved system reliability. This work presents an integrated framework for MEC and Industry 5.0, aimed at enhancing the performance, efficiency, and flexibility of industrial processes. In particular, we propose a joint optimization problem that maximizes computational energy efficiency by optimally allocating resources, such as processing power and computational resources, as well as device association, in the most efficient manner possible. The problem is formulated as nonconvex/nonlinear, which is intractable and poses high complexity. To solve this challenging problem, we first transform and decouple the original optimization problem into a series of subproblems using the block coordinate descent method. Then, we iteratively obtain an efficient solution using convex optimization methods. In addition, our work sheds light on the fundamental trade-off between local computation and partial offloading schemes. The results show that for small data size requirements, the performance is comparable among different schemes. However, as data size increases, our proposed hybrid scheme, which includes a partial offloading scheme, outperforms others, highlighting the effectiveness of the proposed joint optimization scheme.

Dual-functional trisiloxane as binder additive for high volume expansion Li-ion battery electrodes

Silicon-based anodes for lithium-ion batteries have the inherent advantage of higher capacity. However, the inherent expansion of Si within the anodes during cycling, causing low battery life, has limited its application. Various approaches are being investigated to mitigate the adverse effects, ranging from the patterned deposition of Si, blending silicon materials with graphite active materials, and using modified polymeric binders. Inspired by the super spreading capabilities of siloxane compounds and with an aim to optimize the graphite-SiO composite electrode, this work focuses on tweaking the binder formulation with a trisiloxane-based additive which enables uniform dispersion of active material within the electrode and enhances the wetting of the electrolyte within the electrode. In this work, graphite with 15 wt% silicon monoxide was used as an electrode with trisiloxane-modified binder showing much improved electrochemical performance with better mechanical integrity compared to the benchmark electrode. The cell with modified binder exhibited remarkable cycling stability up to 400 cycles at 0.2 C-rate. A detailed study on the role of the trisiloxane additives on the physicochemical properties of electrode materials has also been elucidated. The prospects of employing these additives for similar high-volume expansion electrodes are also discussed.

The effects of fast and normal charging, driving cycle, and a 24-hour regional climate on the performance of electric vehicle batteries

Battery performance is significantly influenced by temperature; therefore, many plug-in electric cars and battery-powered vehicles employ thermal management strategies to improve battery efficiency. The study includes the modeling of an electric vehicle battery pack to simulate the effects of different driving cycles, charging conditions, environmental conditions, and fast and normal charging with different HTC values. The equivalent circuit model was used to simulate the 18650 batteries consisting of 72 cells in a 6S12P configuration. The battery pack was then tested with realistic HWFET, US06, and UDDS drive cycles matched to the dimensions of the battery pack, and the battery pack was examined for the effects of fast and normal charging. The model predicted how the cell will behave thermally when subjected to stress from variables like excessive consumption of power and high surrounding temperatures. In the stress scenario, a significant temperature increase was observed during the US06 drive cycle, followed by the HWFT and UDDS drive cycles. Due to the high ambient temperature in New Delhi during the rest cycle, it takes a while for the battery pack temperature to reach the ambient temperature. Fast charging is causing damage to batteries since the temperature of the battery rises as a result of the high charging rate, resulting in lower battery life when compared to normal charging.

Mass-Market Augmented Reality: The Difficulty behind its Integration and the Path to Success

The failure of Google Glass changed the path of augmented reality (AR), delaying its integration into a mass market by years. Google Glass contained numerous technical limitations that companies are still facing today. The product also showcased the social issues that come with the technology. Shared privacy concerns among many cause consumer reluctance, with information tyrants such as Google leading and largely controlling AR development. In addition to privacy concerns, health concerns steer people away from the technology. Worse yet, the many negative connotations associated with AR give it a stigma that causes major social limitations. Without normalization of the technology, people will not be interested to invest large sums of money in a product centered on convenience rather than purpose. This lack of purpose and perceived unknowns, combined with the pragmatic elements of a low battery life and glitchy, bulky design, makes the technology unappealing. Companies today are attempting to circumnavigate these problems in multiple ways. Some are attempting to create a product with a centralized purpose that solves a problem. Others are using already established industries such as the smartphone or gaming market to sell a more manageable product. Some companies have abandoned the idea of selling AR products, and are instead using it as a service. 
 Augmented reality is a field that still must develop due to its initial setbacks, compelling companies to become creative with the technology’s usage. The consumer market is not adapted to wearable AR, making normalization necessary for further progression in the field.

Towards Wearable Augmented Reality in Healthcare: A Comparative Survey and Analysis of Head-Mounted Displays.

Head-mounted displays (HMDs) have the potential to greatly impact the surgical field by maintaining sterile conditions in healthcare environments. Google Glass (GG) and Microsoft HoloLens (MH) are examples of optical HMDs. In this comparative survey related to wearable augmented reality (AR) technology in the medical field, we examine the current developments in wearable AR technology, as well as the medical aspects, with a specific emphasis on smart glasses and HoloLens. The authors searched recent articles (between 2017 and 2022) in the PubMed, Web of Science, Scopus, and ScienceDirect databases and a total of 37 relevant studies were considered for this analysis. The selected studies were divided into two main groups; 15 of the studies (around 41%) focused on smart glasses (e.g., Google Glass) and 22 (59%) focused on Microsoft HoloLens. Google Glass was used in various surgical specialities and preoperative settings, namely dermatology visits and nursing skill training. Moreover, Microsoft HoloLens was used in telepresence applications and holographic navigation of shoulder and gait impairment rehabilitation, among others. However, some limitations were associated with their use, such as low battery life, limited memory size, and possible ocular pain. Promising results were obtained by different studies regarding the feasibility, usability, and acceptability of using both Google Glass and Microsoft HoloLens in patient-centric settings as well as medical education and training. Further work and development of rigorous research designs are required to evaluate the efficacy and cost-effectiveness of wearable AR devices in the future.

Study on the Effect of Hydraulic Energy Storage on the Performance of Electro-Mechanical-Hydraulic Power-Coupled Electric Vehicles

In order to address the problems of low energy storage capacity and short battery life in electric vehicles, in this paper, a new electromechanical-hydraulic power coupling drive system is proposed, and an electromechanical-hydraulic power coupling electric vehicle is proposed based on this system. The system realizes the mutual conversion between mechanical energy, hydraulic energy, and electric energy through the electromechanical–hydraulic coupler. This paper describes the structural characteristics and working principles of the system and analyzes the different working modes during the driving of the vehicle. We established a mathematical model of the hydraulic accumulator and the hydraulic pump and motor. Based on the vehicle dynamics model, an AME Sim vehicle model was built and the vehicle, and the relevant hydraulic parameters were set in combination with the actual situation. The braking energy recovery and release process was jointly simulated by AME Sim and Simulink. The simulation results show that the hydraulic accumulator size of the accumulator volume can influence the maximum working pressure of the accumulator and the SOC of the vehicle battery, and it is verified that 35 L is the best capacity. This study has an important reference value for matching electromechanical–hydraulic coupling parameters of electric vehicles.

Incorporation of Energy Efficient Computational Strategies for Clustering and Routing in Heterogeneous Networks of Smart City

For decision-making and governance, smart cities depend on tracking data collected via a substantial percentage of wireless sensing nodes. However, several limitations affect Wireless Sensor Network (WSN)-based Internet of Things (IoT) services, such as low battery life, recurrent connectivity problems due to multi-hop connections, and a limited channel capacity. Furthermore, in many systems, clustering and routing are handled independently, which prevents the adaptation of effective strategies for optimal energy usage and prolonged network lifespan. This research gathers data from heterogeneous IoT nodes linked via WSN and distributed across a smart infrastructure. There are two interrelated problems to be addressed with respect to energy efficiency computations: clustering and routing. We provide a new clustering strategy through which efficient routing of critical and regular data is handled. As a result, both clustering and routing have been significantly strengthened, which balances the communication load across different sectors of the smart infrastructure network. Minkowski distance and ranking strategy are used for routing and selecting cluster heads, respectively. Deterministic distributed–time division multiple access (DD-TDMA) scheduling is employed to balance the communication load across the network. The experimental results show that the proposed work outperforms some of the popular cluster-based routing strategies.

Drone Deployment Algorithms for Effective Communication Establishment in Disaster Affected Areas

Communication establishment is crucial for rescue operations in disaster affected areas. A standard tool for communication is the use of cell phones. However, they can be useless in situations where the cellular network’s base stations are damaged in a disaster. A contemporary approach to re-establishing a communication network is by hosting base stations in drones. However, low battery life and difficulty in calculating the number of drones needed in different terrains are limitations of the above approach. This paper introduces a novel terrain-aware algorithm that calculates the minimum number of drones needed to cover an area with no voids in the network coverage. Our method ensures that the drones are deployed at optimal heights to maximize the average leftover energy in the network. We apply the algorithm for an actual location in Pettimudi, India and find the optimal number and positions of the drones to cover the area effectively without voids. In addition, we provide a simulation of the the communication establishment using above drones, and our experiments yield an average network efficiency of 98%, showing the effectiveness of our method.

A Review of Approaches for Compassionate Checkpointing with Mobile Computing Systems

A distribution system is a group of autonomous entities working together to address a challenge that cannot be addressed by any one of them alone. A distributed system called a mobile computing device (MCD) has certain processes that are executed on mobile nodes, whose position within the network shifts over time. Distributed mobile systems create new problems such as mobility, poor wireless channel bandwidth, disconnections, low battery life, and a lack of a steady, trustworthy store on mobile nodes. The issue of fault-tolerant computation in mobile distributed databases is discussed in this study. Checkpointing and roll- it-back recovery are the foundations for the procedures outlined.

A Novel Secure Patient Data Transmission through Wireless Body Area Network: Health Tele-Monitoring

The security of sensitive data obtained from a patient has not been implemented properly because of energy issues of sensor nodes in Wireless Body Area Network (WBAN) and constrained resources such as computational power and low battery life. The main of this paper is to enhance the security level of data transmission between patient and health service provider by considering the availability of energy at sensor nodes. The proposed system consists of a hybrid Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC), which provides simple, fast and high cryptographic strength of data security. ECC is used for securing AES encryption keys, and AES algorithm is used for encrypting/decrypting text. A scenario where sensor nodes are continuously supplied energy from solar power is considered and based upon the energy availability; respective encryption technique is implemented. The result shows that the proposed EEHEE algorithm increases the encryption of the data file by more than 19% compared to the State of Art's solution. The proposed EEHEE system is 11% faster in encrypting data file and reduces the energy consumption by 34 % compared to the current best solution. The proposed system concentrates on reducing the energy consumption in WBAN and increasing cryptographic strength to the system by using the hybrid symmetric and asymmetric algorithm. Thus, this study provides an efficient scheme to enhance security for real-time data transmission in telemedicine.

Lessons Learned from two iterations of LLAMA, an Electrically Powered, Dynamic Quadruped Robot

This paper presents the design, control, and initial performance from two iterations of human-scale (∼75 kg) quadrupedal robots built under the U.S. Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (RCTA) LLAMA (Legged Locomotion and Movement Adaptation) project. These all-electric, quadruped robots are designed with custom quasi-directdrive actuators powering 3-DOF, serial-parallel legs. To our knowledge, this is the first all-electric quadruped robot of this mass scale. The centralized energy management system uses a capacitor bank to supply burst loads and buffer regenerated energy. A hierarchical control scheme enables rapid motions (up to 1.8 m/s) over a variety of terrains. The onboard sensing suite enables deliberate, autonomous operation across rubble fields. In addition, we report on practical observations, lessons learned from field testing of two generations of the platform, and current drawbacks, such as low absolute payload (9 kg) and battery life (35 minutes). These lessons include strategies to address secondary effects at larger scales and parameters with the most impact to improve future designs.

Concept Design and Analysis of Self Sustainable Triboelectric Pacemaker

The heart is one of the most crucial organs for the functioning of the human body. Due to aging and various other ailments like cardiomyopathy and congestive heart failure, the functioning of the heart tends to drop or stop in serious conditions. In such conditions, a bio-medical device called the cardiac pacemaker is used. The pacemaker is a small device that will be placed in the dysfunctional heart that sends electrical impulses to the heart muscles whenever the functioning decreases or ceases. But the pacemaker existing in the market has a low battery life and has to be replaced every few years which is a painful process for the people using it. Therefore, to overcome this predicament in this study we have designed and developed a self-sustaining pacemaker that can generate its electricity from the pacing of the heart itself thereby increasing its battery life generously. This pacemaker works on the principle of tribe-electricity. The model of this pacemaker is designed using SolidWorks and the electrical circuit for the same is simulated using Simulink.

Research on residual life prediction method of lithium ion battery for pure electric vehicle

To overcome the complexity of the lithium-ion battery inside the chemical reaction resulting in a low battery life remaining prediction accuracy, the paper proposes a new electric vehicle lithium ion battery remaining life prediction method based on a correlation vector machine. According to the operating characteristics of lithium-ion batteries in electric vehicles, this method selects health factors that affect battery life, and selects related factors. According to the marginal likelihood function, the factor weights are integrated to obtain the health factor sequence target. Relevance vector machine is used to optimise and evaluate the characteristics of health factors, and complete the prediction of electric vehicle lithium-ion battery capacity and remaining battery life. Comparative experiments show that the prediction effect and stability of the method in this paper are better, and the minimum prediction error is only 0.013.

Comparative Analysis of Nodes Transmission Power in Wireless Sensor Network

Wireless Sensor Networks are one of the major technology boons which has revamped the whole standard of transmission phenomenon. Sensor nodes are the backbone of WSN which carry out huge responsibility of transmission between neighbouring nodes for effective communication and task performance. The major challenge faced by sensor nodes is the optimal transmission power which leads to low battery life. Moreover, altering the power for nodes transmission after their installation in a network is a very tedious task. In this paper, a comparative analysis is being done on different node transmission power methods and various techniques are studied which can strengthen the network connectivity for an efficient communication.

PGS1, a new low cost and low power Portable Geo-physical Station “All in One”. Design and test

PGS1 is a new compact portable seismic station, designed at INGV OBS and Earth Lab, that is specifically intended for the deployment of dense arrays of seismographs on-shore. With its low cost, compact design, high data-quality and long battery life, PGS1 is a perfect solution for seismic monitoring networks. PGS1 design is based on a solid polypropylene suitcase, containing a complete data acquisition system, two battery packs and a photovoltaic panel. The new Earth Lab 5s medium-period seismic sensor is included. The whole system meets the IP67 standard requirements both in transport and in acquisition configuration. PGS1 is normally equipped with one battery pack, one more pack can be added inside the suitcase achieving 40 days of battery life. The station is equipped with a photovoltaic panel, useful to extend the deployment length. Inside the suitcase, there are compartments where to store the seismic sensor, the photovoltaic panel and all the cables. Therefore, the station is very easy to transport.