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In this paper, we report a wind energy harvesting system for Internet of Things (IoT)-based environment monitoring (e.g., temperature and humidity, etc.) for potential agricultural applications. A wind-driven electromagnetic energy harvester using rotational magnet pole-pairs (rotor) with a back-iron shield was designed, analyzed, fabricated, and characterized. Our analysis (via finite element method magnetic simulations) shows that a back-iron shield enhances the magnetic flux density on the front side of a rotor where the series connected coils interact and convert the captured mechanical energy (wind energy) into electrical energy by means of electromagnetic induction. A prototype energy harvester was fabricated and tested under various wind speeds. A custom power management circuit was also designed, manufactured, and successfully implemented in real-time environmental monitoring. The experimental results show that the harvester can generate a maximum average power of 1.02 mW and maximum power efficiency of 73% (with power management circuit) while operated at 4.5 m/s wind speed. The system-level demonstration shows that this wind-driven energy harvesting system is capable of powering a commercial wireless sensor that transmits temperature and humidity data to a smartphone for more than 200 min after charging its battery for only 10 min. The experimental results indicate that the proposed wind-driven energy harvesting system can potentially be implemented in energetically autonomous IoT for smart agriculture applications.

We report the design, fabrication, and characterization of a prototype that meets the form, fit, and function of a household 1.5 V AA battery, but which can be wirelessly recharged without removal from the host device. The prototype system comprises a low-frequency electrodynamic wireless power transmission (EWPT) receiver, a lithium polymer energy storage cell, and a power management circuit (PMC), all contained within a 3D-printed package. The EWPT receiver and overall system are experimentally characterized using a 238 Hz sinusoidal magnetic charging field and either a 1000 µF electrolytic capacitor or a lithium polymer (LiPo) cell as the storage cell. The system demonstrates a minimal operating field as low as 50 µTrms (similar in magnitude to Earth’s magnetic field). At this minimum charging field, the prototype transfers a maximum dc current of 50 µA to the capacitor, corresponding to a power delivery of 118 µW. The power effectiveness of the power management system is approximately 49%; with power effectiveness defined as the ratio between actual output power and the maximum possible power the EWPT receiver can transfer to a pure resistive load at a given field strength.

This paper presents a hybrid electromechanical transformer that passively transfers electrical power between galvanically isolated ports by coupling electrodynamic and piezoelectric transducers. The use of these two complementary electromechanical transduction methods along with a high-Q mechanical resonance affords very large transformations of voltage, current, or impedance at particular electrical frequencies. A chip-size prototype is designed, simulated, fabricated, and experimentally characterized. The 7.6 mm × 7.6 mm × 1.65 mm device achieves an open-circuit voltage gain of 31.4 and 48.7 when operating as a step-up transformer at 729.5 Hz and 1015 Hz resonance frequencies, respectively. When operating as a step-down transformer, the resonance frequencies and the corresponding voltage gains are 728 Hz, 1002 Hz, and 0.0097, 0.0128, respectively. In one operational mode, the system shows a minimum power dissipation of only 0.9 µW corresponding to a power conversion efficiency of 11.8%.

Wearable devices can be used for monitoring vital physical and physiological signs remotely, as well as for interacting with computers. Widespread adoption of wearables is somewhat hindered by the duration time they can be used without re‐recharging. To ensure uninterrupted operation, these devices need a constant and battery‐less energy supply. Scavenging energy from the wearable's surroundings is, therefore, an essential step towards achieving genuinely autonomous and self‐powered devices. While energy harvesting technologies may not completely eliminate the battery storage unit, they can ensure a maximum duration of use. Piezoelectric energy harvesting is a promising and efficient technique to generate electricity for powering wearable devices in response to body movements. Consequently, we systematically survey the range of technologies used for scavenging energy from the human body, with a particular focus on the upper‐limb area. According to our review and in comparison to other upper limb locations, highest power densities can be achieved from piezoelectric transducers located on the wrist. For short and fast battery charging needs, we therefore review the range of materials, architectures and devices used to scavenge energy from these upper‐limb areas. We provide comparisons as well as recommendations and possible future directions for harvesting energy using this promising technique. Upper limbs provide enormous potential for harvesting mechanical energy from the human body during daily movements. This paper systematically reviews a range of piezoelectric energy harvesters for powering wearable devices that are mounted on the upper limb. Accordingly, maximum power density can be achieved on the wrist. Recommendations regarding the piezoelectric materials, architectures and configurations are also provided.

We present a human-limb driven piezoelectric energy harvester using two mass-loaded unimorph piezoelectric beams clamped on two flexible sidewalls. Since vibration generated by human-limb motion has low-frequency and high amplitude characteristics, the energy harvester has been designed to up-convert the low-frequency human-limb vibration by mechanical impact of a spring less spherical metallic ball. However, instead of direct mechanical impact on the power generating elements (unimorph piezoelectric beams), the ball impacts on the bases (flexible sidewalls) of each beam to avoid mechanical wear of the piezo-materials. While excited by human-limb motion, the ball impacts consecutively on the flexible sidewalls which transfer impulsive forces to the loaded mass of the respective unimorph beam. The beam vibrates at its own resonant frequency and causes voltage generation by virtue of piezoelectric effect. A proof-of-concept prototype has been fabricated and tested. At optimum load condition, each unimorph piezoelectric generator generates 96 µW average power while excited at 4.96 Hz frequency and ~2 g acceleration. The device with series connected generators is capable of generating maximum 175 µW average power. Improved design and further optimization would be able to increase its power generation capability (as well as power density) to be used in wearable devices applications.

Energy harvesting from human-body-induced motion is mostly challenging due to the low-frequency, high-amplitude nature of the motion, which makes the use of conventional cantilevered spring-mass oscillators unrealizable. Frequency up-conversion by mechanical impact is an effective way to overcome the challenge. However, direct impact on the transducer element (especially, piezoelectric) increases the risk of damaging it and raises questions on the reliability of the energy harvester. In order to overcome this shortcoming, we proposed a transverse mechanical impact driven frequency up-converted hybrid energy harvester for human-limb motion. It utilizes the integration of both piezoelectric and electromagnetic transducers in a given size that allows more energy to be harvested from a single mechanical motion, which, in turn, further improves the power density. While excited by human-limb motion, a freely-movable non-magnetic sphere exerts transverse impact by periodically sliding over a seismic mass attached to a double-clamped piezoelectric bimorph beam. This allows the beam to vibrate at its resonant frequency and generates power by means of the piezoelectric effect. A magnet attached to the beam also takes part in generating power by inducing voltage in a coil adjacent to it. A mathematical model has been developed and experimentally corroborated. At a periodic limb-motion of 5.2 Hz, maximum 93 µW and 61 µW average powers (overall 8 µW·cm−3 average power density) were generated by the piezoelectric and the electromagnetic transducers, respectively. Moreover, the prototype successfully demonstrated the application of low-power electronics via suitable AC-DC converters.

Internet of Things (IoT) opens new horizons by enabling automated procedures without human interaction using IP connectivity. IoT deals with devices, called things, represented as any items from our daily life that are enhanced with computing or communication facilities. Among various mobile communications, Zigbee communication is broadly used in controlling or monitoring applications due to its low data rate and low power consumption. Securing IoT systems has been the main concern for the research community. In this paper, different security threats of Zigbee networks in the IoT platform have been addressed to predict the potential security threats of Zigbee protocol and a Security Improvement Framework (SIF) has been designed for intelligent monitoring in an office/corporate environment. Our proposed SIF can predict and protect against various potential malicious attacks in the Zigbee network and respond accordingly through a notification to the system administrator. This framework (SIF) is designed to make automated decisions immediately based on real-time data which are defined by the system administrator. Finally, the designed SIF has been implemented in an office security system as a case study for real-time monitoring. This office security system is evaluated based on the capacity of detecting potential security attacks. The evaluation results show that the proposed SIF is capable of detecting and protecting against several potential security attacks efficiently, enabling a more secure way of intelligent monitoring in the IoT platform.

The world is heavily suffering from the COVID-19 pandemic for more than a year, with over 191 million confirmed cases and more than 4.1 million deaths to date. Previous studies have explored several risk factors for coronavirus disease 2019 (COVID-19), but there is still a lack of association with ABO blood type. This study aimed to find out the relationship between the ABO blood group and COVID-19 outcomes in Bangladesh. This retrospective cross-sectional study was conducted in the intensive care unit (ICU) of a tertiary-level COVID-dedicated hospital in Dhaka city, Bangladesh, between April 2020 and November 2020. Records from 771 critically ill patients were extracted who were confirmed for COVID-19 by reverse transcriptase-polymerase chain reaction (RT-PCR) assay, and blood grouping records were available in the health records. The blood groups were 37.35%, 17.38%, 26.46%, and 18.81% for A, B, AB, and O type, respectively. Clinical symptoms were significantly more common in patients with blood type A ( < 0.05). Patients with blood type A had higher WBC counts and peak serum ferritin levels and both were statistically significant ( < 0.001). Patients with blood type A had a greater need for supplemental oxygen, and they were more likely to die in comparison to the patients with other blood types ( < 0.05). In multivariable analysis, our primary outcome death was significantly associated with blood type A (AOR: 3.49, 95% CI: 1.57-7.73) while adjusting for age, male gender, and non-communicable diseases. Based on this study results, it can be concluded that the COVID-19 patients with blood type A have a higher chance of death and other complications. The authors recommend blood grouping before treating the COVID-19 patients, and healthcare workers should prioritize treating the patients based on that result.

To meet their commitments to Paris climate accord, governments around the world have begun to introduce emission pricing schemes such as carbon taxes with the intention of curbing the greenhouse gas (GHG) emissions and at the same time promoting the development of low-carbon technologies. However, adoption of such taxes has prompted major concerns among the industries, especially for large emitters such as petrochemical manufacturing plants, since it will substantially increase their operating costs and hence directly affect their competitiveness in the global market. This paper proposes a bottom-up framework for modeling the potential impacts of a carbon tax introduction on petrochemical selling prices. The framework has been developed using a set of mathematical equations that links the amount of GHG emissions with the carbon tax rates. The required increases in the petrochemical product prices are then projected for compensating the incurred emission costs. The goal is to retain the same production revenues prior to carbon tax imposition—this is known as tax passing strategy. To illustrate the approach, a case study involving productions and supply chains of four petrochemical products—acetic acid, bisphenol-A, nylon-6,6, and polypropylene—is considered.