Design and Development of IoT-Based Tracking for Humans using Arduino
Technological advancement and innovation in the field of biometric identification technology and security of lives and properties have enabled the evolution of intelligent monitoring systems. In light of this, this paper intends to present the results of the hardware platform set up for the data collection of human tracking that would ultimately be integrated into the Kalman Filter Algorithm (KFA) to be developed in our further work. To provide a fast tool for creating a VLSI test bench, particularly for sensors, Arduino Mega 2560 was chosen and used as the heart of this hardware platform. As a consequence, its working principle and other applications were explored in this paper. Furthermore, since a two-dimensional Kalman Filter model would be developed, the positions and velocities of the object to be tracked (i.e., humans) were estimated in both x- and y-directions in a tabular form.
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