This paper proposes design and analysis of electromagnetic energy harvester using MEMS technology. The energy harvester is intended to harvest energy from low frequency ambient vibrations that is less than 100Hz. The design would consist of a cantilever which is the simplest MEMS structure which can further be used to power the amplifiers. These amplifiers can be used to amplify the low amplitude and low frequency vibration signals. The work intends to explore the opportunities in harnessing vibrations induced by the live loads, such as laden Lorries & Buses on bridges, to harvest energy in the form of generated voltage. A cantilever based electromagnetic energy harvester can be employed to capture these miniscule level of vibrations and convert them into electrical energy. The Faraday's law of electromagnetic induction is the fundament idea utilized to design the cantilever beam simulated with dimensions of 2500x500μm. The material plays a vital role in sensitivity and hence NdFeB is selected as magnetic material whereas Aluminum as the conducting coil electrode material. The voltage of 2.34mV is generated using single cantilever beam energy harvester. An array of six such cantilevers generates a voltage of 3.27mV. The simulation results confirm that the low ambient vibrations can be effectively utilized to generate useful energy

A novel, portable deep learning-assisted smartphone-based electrochemiluminescence (ECL) cost-effective (~10$) sensing platform was developed and used for selective detection of lactate. Low-cost, fast prototyping screen printing and wax printing methods with paper-based substrate were used to fabricate miniaturized single-pair electrode ECL platforms. The lab-made 3D-printed portable black box served as a reaction chamber. This portable platform was integrated with a smartphone and a buck-boost converter, eliminating the need for expensive CCD cameras, photomultiplier tubes, and bulky power supplies. This advancement makes this platform ideal for point-of-care testing applications. Foremost, the integration of a deep learning approach served to enhance not just the accuracy of the ECL sensors, but also to expedite the diagnostic procedure. The deep learning models were trained (3600 ECL images) and tested (900 ECL images) using ECL images obtained from experimentation. Herein, for user convenience, an Android application with a graphical user interface was developed. This app performs several tasks, which include capturing real-time images, cropping them, and predicting the concentration of required bioanalytes through deep learning. The device’s capability to work in a real environment was tested by performing lactate sensing. The fabricated ECL device shows a good liner range (from 50 µM to 2000 µM) with an acceptable limit of detection value of 5.14 µM. Finally, various rigorous analyses, including stability, reproducibility, and unknown sample analysis, were conducted to check device durability and stability. Therefore, the developed platform becomes versatile and applicable across various domains by harnessing deep learning as a cutting-edge technology and integrating it with a smartphone.

Piezoelectric microgenerator is an incredible method which makes a self‐powered wireless sensor node. It is a process of converting ambient energy into electrical energy. Flexible microgenerator goes well with many natural curved, rough and arbitrary surfaces such as human bodies, organisms, clothes and structure surfaces. Zinc oxide and polymer have been used as piezoelectric material and substrate, respectively, for biocompatible device. The harmonic analysis was carried out using finite element method (FEM) tool to examine the effect of the electrodes on the output voltage. Microgenerators with different electrodes were fabricated and examined their performance. Traditional parallel plate metal electrodes (PPEs) are prone to cracks and internal defects on bending or stretching, thus mesh electrodes (MEs) has been proposed. Copper MEs based microgenerator has performed at par. Open‐circuit electric potential of 2.8 V _PEAK , 435 mV _RMS for ME against electric potential of 2.3 V _PEAK , 430 mV _RMS and 0.9 V, 340 V _PEAK , 40 mV _RMS for interdigitated electrodes (IDEs) and PPE, respectively, were recorded. Design, fabrication, electrical characterisation and comparative evaluation of microgenerator with three different electrodes are presented.

Recently, battery powered RFID tags have attracted attention as the latest technology for commodity management. Every day, we come across many applications where passive and active RFID tags are used. But active tags not really portable due to battery which demands frequent charging and replacement. As battery technology is not advancing by the same rate, thus we need to think concretely for an alternate energy sources. An attempt has been made to model an innovative source of energy using lead zirconium titanate as piezoelectric material. The model comprises of three major components i.e. stack of piezoelectric plates,voltage multiplier circuit, super capacitor as storage device. The random vibrations were treated as a source of mechanical energy.