n this paper we focus our attention on the world of Internet of Things (IoT) objects and their potential for human indoor localization. Our aim is to investigate how Received Signal Strength (RSS) can be effectively used for identifying the position of a person at home, by exploiting common IoT communication networks. We propose a plug and play solution where the Anchor Nodes (ANs) are represented by smart objects located in the house, while the Unknown Node (UN) can be any smart object held by the user. The proposed solution automatically identifies the rooms where the smart objects are placed, by comparing a fuzzy weighted distance matrix derived from the anchor signals, with a threshold weighted distance matrix derived from the distances between rooms. The information can be easily integrated in any IoT environment to provide the estimation of the user position, without requiring the a priori knowledge of the positions of the anchor nodes. © 2016 IEEE.
Room occupancy detection: Combining RSS analysis and fuzzy logic / Baldini, A.; Ciabattoni, Lucio; Felicetti, R.; Ferracuti, Francesco; Longhi, Sauro; Monteriu', Andrea; Freddi, Alessandro. - ELETTRONICO. - 2016-:(2016), pp. 69-72. (Intervento presentato al convegno 6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016 tenutosi a Consumer Electronics and Home Appliances Show (IFA), deu nel 2016) [10.1109/ICCE-Berlin.2016.7684720].
Room occupancy detection: Combining RSS analysis and fuzzy logic
CIABATTONI, LUCIO;Felicetti, R.;FERRACUTI, FRANCESCO;LONGHI, SAURO;MONTERIU', Andrea;FREDDI, ALESSANDRO
2016-01-01
Abstract
n this paper we focus our attention on the world of Internet of Things (IoT) objects and their potential for human indoor localization. Our aim is to investigate how Received Signal Strength (RSS) can be effectively used for identifying the position of a person at home, by exploiting common IoT communication networks. We propose a plug and play solution where the Anchor Nodes (ANs) are represented by smart objects located in the house, while the Unknown Node (UN) can be any smart object held by the user. The proposed solution automatically identifies the rooms where the smart objects are placed, by comparing a fuzzy weighted distance matrix derived from the anchor signals, with a threshold weighted distance matrix derived from the distances between rooms. The information can be easily integrated in any IoT environment to provide the estimation of the user position, without requiring the a priori knowledge of the positions of the anchor nodes. © 2016 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
