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Traditional Internet of Things (IoT) sensors rely on batteries that need tobe replaced or recharged frequently which impedes their pervasive deployment. Apromising alternative is to employ energy harvesters that convert theenvironmental energy into electrical energy. Kinetic Energy Harvesting (KEH)converts the ambient motion/vibration energy into electrical energy to powerthe IoT sensor nodes. However, most previous works employ KEH withoutdynamically tracking the optimal operating point of the transducer for maximumpower output. In this paper, we systematically analyse the relation between theoperating point of the transducer and the corresponding energy yield. To thisend, we explore the voltage-current characteristics of the KEH transducer tofind its Maximum Power Point (MPP). We show how this operating point can beapproximated in a practical energy harvesting circuit. We design two hardwarecircuit prototypes to evaluate the performance of the proposed mechanism andanalyse the harvested energy using a precise load shaker under a wide set ofcontrolled conditions typically found in human-centric applications. We analysethe dynamic current-voltage characteristics and specify the relation betweenthe MPP sampling rate and harvesting efficiency which outlines the need fordynamic MPP tracking. The results show that the proposed energy harvestingmechanism outperforms the conventional method in terms of generated power andoffers at least one order of magnitude higher power than the latter.

Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT