Piezoelectric materials are widely referred to as "smart" materials because they can transduce mechanical pressure acting on them to electrical signals and vice versa. They are extensively utilized in harvesting mechanical energy from vibrations, human motion, mechanical loads, etc., and converting them into electrical energy for low power devices. Piezoelectric transduction offers high scalability, simple device designs, and high-power densities compared to electro-magnetic/static and triboelectric transducers. This review aims to give a holistic overview of recent developments in piezoelectric nanostructured materials, polymers, polymer nanocomposites, and piezoelectric films for implementation in energy harvesting. The progress in fabrication techniques, morphology, piezoelectric properties, energy harvesting performance, and underpinning fundamental mechanisms for each class of materials, including polymer nanocomposites using conducting, non-conducting, and hybrid fillers are discussed. The emergent application horizon of piezoelectric energy harvesters particularly for wireless devices and self-powered sensors is highlighted, and the current challenges and future prospects are critically discussed.

Piezoelectric Materials for Energy Harvesting and Sensing Applications: Roadmap for Future Smart Materials

Healthcare sector is probably the most benefited from the applications of nanotechnology. The nanotechnology, in the forms of nanomedicine, nanoimplants, nanobiosensors along with the internet of nano things (IoNT), has the potential to bring a revolutionizing advancement in the field of medicine and healthcare services. The primary aim of this paper is to explore the clinical and medical possibilities of these different implementations of nanotechnology. This paper provides a comprehensive overview of nanotechnology, biosensors, nanobiosensors, and IoNT. Furthermore, multilevel taxonomies of nanotechnology, nanoparticles, biosensors, nanobiosensors, and nanozymes are presented. The potential medical and clinical applications of these technologies are discussed in details with several examples. This paper specifically focuses on IoNT and its role in healthcare. In addition to describing a general architecture of IoNT for healthcare, the communication architecture of the IoNT is also explained. The challenges in the successful realization of IoNT are also discussed critically, along with a special discussion on internet of bio-nano things (IoBNT) and its potential in making IoNT more compatible to human body.

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Advancing Modern Healthcare With Nanotechnology, Nanobiosensors, and Internet of Nano Things: Taxonomies, Applications, Architecture, and Challenges

The world is rapidly adopting renewable energy alternatives at a remarkable rate to address the ever-increasing environmental crisis of CO2 emissions. Renewable Energy Systems (RES) offers enormous potential to decarbonize the environment because they produce no greenhouse gases or other polluting emissions. However, the RES relies on natural resources for energy generation, such as sunlight, wind, water, geothermal, which are generally unpredictable and reliant on weather, season, and year. To account for these intermittencies, renewable energy can be stored using various techniques and then used in a consistent and controlled manner as needed. Several researchers from around the world have made substantial contributions over the last century to developing novel methods of energy storage that are efficient enough to meet increasing energy demand and technological breakthroughs. This review attempts to provide a critical review of the advancements in the Energy Storage System (ESS) from 1850–2022, including its evolution, classification, operating principles and comparison. 

Energy storage systems: A review

Lithium-ion batteries are the most used these days for charging electric vehicles (EV). It is important to study the aging of batteries because the deterioration of their characteristics largely determines the cost, efficiency, and environmental impact of electric vehicles, especially full-electric ones. The estimation of batteries’ state-condition is also very important for improving energy efficiency, lengthening the life cycle, minimizing costs and ensuring safe implementation of batteries in electric vehicles. However, batteries with large temporal variables and non-linear characteristics are often affected by random factors affecting the equivalent internal resistance (EIR), battery state of charge (SoC), and state of health (SoH) in EV applications. The estimation of batteries’ parameters is a complex process, due to its dependence on various factors such as batteries age and ambient temperature, among others. A good estimate of SoC and internal resistance leads to long battery life and disaster prevention in the event of a battery failure. The classification of estimation methodologies for internal parameters and the charging status of batteries will be very helpful in choosing the appropriate method for the development of a reliable and secure battery management system (BMS) and an energy management strategy for electric vehicles.

Estimation of Lithium-Ion Batteries State-Condition in Electric Vehicle Applications: Issues and State of the Art

Smartphones as ubiquitous gadgets are rapidly becoming more intelligent and context-aware as sensing, networking, and processing capabilities advance. These devices provide users with a comprehensive platform to undertake activities such as socializing, communicating, sending and receiving e-mails, and storing and accessing personal data at any time and from any location. Nowadays, smartphones are used to store a multitude of private and sensitive data including bank account information, personal identifiers, account passwords and credit card information. Many users remain permanently signed in and, as a result, their mobile devices are vulnerable to security and privacy risks through assaults by criminals. Passcodes, PINs, pattern locks, facial verification, and fingerprint scans are all susceptible to various assaults including smudge attacks, side-channel attacks, and shoulder-surfing attacks. To solve these issues, this research introduces a new continuous authentication framework called DeepAuthen, which identifies smartphone users based on their physical activity patterns as measured by the accelerometer, gyroscope, and magnetometer sensors on their smartphone. We conducted a series of tests on user authentication using several deep learning classifiers, including our proposed deep learning network termed DeepConvLSTM on the three benchmark datasets UCI-HAR, WISDM-HARB and HMOG. Results demonstrated that combining various motion sensor data obtained the highest accuracy and energy efficiency ratio (EER) values for binary classification. We also conducted a thorough examination of the continuous authentication outcomes, and the results supported the efficacy of our framework.

Deep Learning Approaches for Continuous Authentication Based on Activity Patterns Using Mobile Sensing.

The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone’s energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device’s energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone’s power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones’ batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed.

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Power Consumption Analysis, Measurement, Management, and Issues: A State-of-the-Art Review of Smartphone Battery and Energy Usage

The evolution of the internet has steered an enormous amount of travel reviews of hotels on the web. People referring to these reviews are often overloaded and confused by the sheer amount of infor...

Sentiment analysis from travellers’ reviews using enhanced conjunction rule based approach for feature-specific evaluation of hotels

The operational characteristics of a cyber-physical system (CPS) may deviate from the certified system due to intended (in case of cheating) or unintended (wear and tear) reasons. A modification suggested to the original certification process requires the CPS operation to satisfy a contract that allows for testing the CPS deployment with variations of the standard test case. Doping test is then utilized to attempt to derive a test case that satisfies the input contract but violates the output regulations. Although a significant step towards verifying oper-ational characteristics of CPS, the search mechanism in doping test is only limited to the input space of the cyber subsystem and ignores the characteristics of the dynamic interactions in a CPS. This results in test cases that are practically unfeasible for the CPS to replicate. This paper proposes CyPhyTest that makes test case search aware of the multidimensional interactions between the cyber and physical subsystems and addresses practical dynamical system problems like Zeno behavior and dynamical model divergence. CyPhyTest, dynamically modulates the input search space by predicting and limiting input variations that can potentially cause divergence or Zeno behavior. We show the usage of the CyPhyTest framework in identifying a contract violating test case for an automobile emission control system equipped with a Volkswagen-like cheating device.

CyPhyTest: Cyber Physical Interaction Aware Test Case Generation to Identify Operational Changes

Gestures that share similarities in their forms and are related in their meanings, should be easier for learners to recognize and incorporate into their existing lexicon. In that regard, to be more readily accepted as standard by the Deaf and Hard of Hearing community, technical gestures in American Sign Language (ASL) will optimally share similar forms with their lexical neighbors. We utilize a lexical database of ASL, ASL-LEX, to identify lexical relations within a set of technical gestures. We use automated identification for 3 unique sub-lexical properties in ASL- location, handshape and movement. EdGCon assigned an iconicity rating based on the lexical property similarities of the new gesture with an existing set of technical gestures and the relatedness of the meaning of the new technical word to that of the existing set of technical words. We collected 30 ad hoc crowdsourced technical gestures from different internet websites and tested them against 31 gestures from the DeafTEC technical corpus. We found that EdGCon was able to correctly auto-assign the iconicity ratings 80.76% of the time.

Aranyak Maity

Papers

Power Consumption Analysis, Measurement, Management, and Issues: A State-of-the-Art Review of Smartphone Battery and Energy Usage

Sentiment analysis from travellers’ reviews using enhanced conjunction rule based approach for feature-specific evaluation of hotels

CyPhyTest: Cyber Physical Interaction Aware Test Case Generation to Identify Operational Changes

EdGCon: Auto-assigner of Iconicity Ratings Grounded by Lexical Properties to Aid in Generation of Technical Gestures