Larranaga, JanireMuguira Urtubi, LeireLópez Garde, Juan ManuelVázquez Gómez, Juan Ignacio2024-12-182024-12-182010Larranaga, J., Muguira, L., Lopez-Garde, J.-M., & Vazquez, J.-I. (2010). An environment adaptive ZigBee-based indoor positioning algorithm. 2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010 - Conference Proceedings. https://doi.org/10.1109/IPIN.2010.5647828978142445864610.1109/IPIN.2010.5647828http://hdl.handle.net/20.500.14454/2179Ponencia presentada en la 2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010, celebrada en Zúrich entre el 15 y 17 de septiembre de 2010.Lately, there has been significant progress in the field of wireless communications and networking. Furthermore, the number of applications that require context information as the user's location will increase in the coming years. However, this issue still has not been solved indoors due to the RF (Radio Frequency) signals' behaviour in this kind of scenarios. In this paper, we present a robust, easy to deploy and flexible indoor localization system based on ZigBee Wireless Sensor Networks. It is important to mention that our localization system is based on RSSI (Received Signal Strength Indicator) level measurements since this information can be obtained directly from the messages exchanged between nodes, so no extra hardware is required. Our localization system consists of two phases: calibration and localization. Anytime a blind node needs to be located, our system performs calibration using a matrices system, so that the environment can be characterized, taking into account possible changes on it since the last request. Then, in the localization phase, the central server processes all the information and calculates the blind node's position with the new iterative algorithm we present. With this indoor positioning algorithm we can estimate the blind node's position with a good resolution (3 m average error), so we can say that this ZigBee localization algorithm provides very promising results.eng© 2010 IEEEAdaptive algorithmIndoor positioningRSSIZigBeeconference paper2024-12-18