A genetic based indoor positioning algorithm using Wi-Fi received signal strength and motion data

<span lang="EN-GB">The recent trend in location-based services has led to a proliferation of studies indoor positioning technology. Wi-Fi</span><span lang="VI"> received signal strength </span><span lang="EN-US">indicator</span><span (RSSI) lang="EN-GB">Fingerprinting and pedestrian dead reckoning (PDR) are the two best representatives from both approaches. This</span><span research lang="EN-GB">proposed genetic algorithm combine Wi-Fi Fingerprinting PDR. By taking advantage PDR</span><span algorithm</span><span lang="EN-GB">, we only need collect limited</span><span number of</span><span lang="EN-GB"> points for fingerprint dataset with known coordinates, then target trajectories' position can be estimated high accuracy. Results our experiments simulations have shown that even scenario noisy inertial</span><span measurement unit (</span><span lang="EN-GB">IMU</span><span lang="VI">)</span><span sensors data, using RSSI measurements coordinate 8 points, proposed method was able achieve 1.589 meters average distance error which is 34.4 percent lower than conventional method.</span>