IoT Indoor Localization with AI Technique
Matteo D’Aloia, Annalisa Longo, Gianluca Guadagno, Mariano Pulpito, Paolo Fornarelli, Pietro Nicola Laera, Dario Manni, María Rízzí
Abstract
In this paper, an innovative method for indoor localization based on Bluetooth Low Energy (BLE4) technology has been developed. By employing a mobile beacon, a wearable device and stationary anchors, the conceived tracking system is able to predict people position within buildings. Adopting the received signal strength indicator and a machine learning approach, good accuracy is reached without limiting the freedom and privacy of users.
Topics & Concepts
Bluetooth Low EnergyLimitingComputer scienceWearable computerBluetoothSignal strengthInternet of ThingsPosition (finance)Wearable technologyReal-time computingEnergy (signal processing)Tracking (education)SIGNAL (programming language)Artificial intelligenceEmbedded systemWirelessTelecommunicationsEngineeringEconomicsStatisticsMechanical engineeringMathematicsFinanceProgramming languagePsychologyPedagogyIndoor and Outdoor Localization TechnologiesBluetooth and Wireless Communication TechnologiesUnderwater Vehicles and Communication Systems