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    Energy harvesting from human and machine motion for wireless electronic devices

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    Kinetic energy harvesting

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    This paper reviews kinetic energy harvesting as a potential localised power supply for wireless applications. Harvesting devices are typically implemented as resonant devices of which the power output depends upon the size of the inertial mass, the frequency and amplitude of the driving vibrations, the maximum available mass displacement and the damping. Three transduction mechanisms are currently primarily employed to convert mechanical into electrical energy: electromagnetic, piezoelectric and electrostatic. Piezoelectric and electrostatic mechanisms are best suited to small size MEMS implementations, but the power output from such devices is at present limited to a few microwatts. An electromagnetic generator implemented with discrete components has produced a power 120 ?W with the highest recorded efficiency to date of 51% for a device of this size reported to date. The packaged device is 0.8 cm3 and weighs 1.6 grams. The suitability of the technology in space applications will be determined by the nature of the available kinetic energy and the required level of output power. A radioactively coupled device may present an opportunity where suitable vibrations do not exist

    Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things

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    Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.Comment: 15 pages, 11 figure

    Future of smart cardiovascular implants

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    Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such as central line access failure, atherosclerosis and reporting on vascular grafts for renal dialysis. Here we review the latest advances in the field of cardiovascular medical implants, providing a broad overview of the application of their use in the context of cardiovascular disease rather than an in-depth analysis of the current state of the art. We cover their powering, communication and the challenges faced in their fabrication. We focus specifically on those devices required to maintain vascular access such as ones used to treat arterial disease, a major source of heart attacks and strokes. We look forward to advances in these technologies in the future and their implementation to improve the human condition
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