The principal objective of this article is to categorically review and compare the state of the art vibration based energy harvesting approaches. To evaluate the contemporary methodologies with respect to their physics, average power output and operational frequencies, systematically divided and easy readable tables are presented followed by the description of the energy harvesting methods. Energy harvesting is the process of obtaining electrical energy from the surrounding vibratory mechanical systems through an energy conversion method using smart structures, like, piezoelectric, electrostatic materials. Recent advancements in low power electronic gadgets, micro electro mechanical systems, and wireless sensors have significantly increased local power demand. In order to circumvent the energy demand; to allow limitless power supply, and to avoid chemical waste from conventional batteries, low power local energy harvesters are proposed for harvesting energy from different ambient energy sources. Piezoelectric materials have received tremendous interest in energy harvesting technology due to its unique ability to capitalize the ambient vibrations to generate electric potential. Their crystalline configuration allows the material to convert mechanical strain energy into electrical potential, and vice versa. This article discusses the various approaches in vibration based energy scavenging where piezoelectric materials are employed as the energy conversion medium.

The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult due to its Nasta’liq writing style. Nasta’liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping of characters. Therefore, the work done for recognition of Arabic script cannot be directly applied to Urdu recognition. We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta’liq writing style. Experiments show that MDLSTM attained a recognition accuracy of 98% for the unconstrained Urdu Nasta’liq printed text, which significantly outperforms the state-of-the-art techniques.

Electrochemical Impedance Spectroscopy (EIS) is a powerful and proven tool for analyzing AC impedance response. A conventional three electrode EIS method was used to perform the investigation in the present study. Saturated potassium chloride solution was used as the electrolyte and three different material rods were used as working electrodes. Different configurations of electrode area were exposed to the electrolyte as an active area to investigate electrode geometry effects. Counter to working electrode distance was also altered while keeping the working electrode effective area constant to explore the AC response dependence on the variation of ion travel distance. Some controlled experiments were done to validate the experimental setup and to provide a control condition for comparison with experimental results. A frequency range of 100 mHz to 1 MHz was used for all experiments. In our analysis, we have found a noteworthy influence of electrode geometry on AC impedance response. For all electrodes, impedance decreases with the increase of effective area of the electrolyte. High frequency impedance is not as dependent on geometry as low frequency response. The observed phase shift angle drops in the high frequency region with increased working electrode area, whereas at low frequency the reverse is true. Resistance and capacitive reactance both decrease with an increase of area, but resistance response is more pronounce than reactance. For lower frequencies, small changes in working area produce very distinctive EIS variations. Electrode material as well as geometry was systematically varied in the present study. From these and other studies, we hope to develop a fundamental foundation for understanding specific changes in local geometry in fuel cell (and other) electrodes as a method of designing local morphology for specific performance.

This letter presents the possibility of energy scavenging (ES) utilizing the physics of acousto-elastic metamaterial (AEMM) at low frequencies (<∼3KHz). It is proposed to use the AEMM in a dual mode (Acoustic Filter and Energy Harvester), simultaneously. AEMM’s are typically reported for filtering acoustic waves by trapping or guiding the acoustic energy, whereas this letter shows that the dynamic energy trapped inside the soft constituent (matrix) of metamaterials can be significantly harvested by strategically embedding piezoelectric wafers in the matrix. With unit cell AEMM model, we experimentally asserted that at lower acoustic frequencies (< ∼3 KHz), maximum power in the micro Watts (∼35µW) range can be generated, whereas, recently reported phononic crystal based metamaterials harvested only nano Watt (∼30nW) power against 10KΩ resistive load. Efficient energy scavengers at low acoustic frequencies are almost absent due to large required size relevant to the acoustic wavelength. Here we report sub wave length scale energy scavengers utilizing the coupled physics of local, structural and matrix resonances. Upon validation of the argument through analytical, numerical and experimental studies, a multi-frequency energy scavenger (ES) with multi-cell model is designed with varying geometrical properties capable of scavenging energy (power output from ∼10µW – ∼90µW) between 0.2 KHz and 1.5 KHz acoustic frequencies.

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