Pregled bibliografske jedinice broj: 1089001
Context-based System for User-Centric Smart Environment
Context-based System for User-Centric Smart Environment // 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
Split: Institute of Electrical and Electronics Engineers (IEEE), 2020. 9238215, 5 doi:10.23919/softcom50211.2020.9238215 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1089001 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Context-based System for User-Centric Smart
Environment
Autori
Mandaric, Katarina ; Skocir, Pavle ; Jezic, Gordan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
/ - Split : Institute of Electrical and Electronics Engineers (IEEE), 2020
ISBN
978-953-290-099-6
Skup
28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
Mjesto i datum
Hvar, Hrvatska; online, 17.09.2020. - 19.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Cognitive Internet of Things, Artificial Neural Networks, User-Centricity, Smart Lighting
Sažetak
Internet of Things (IoT) solutions are becoming ubiquitous in various application domains. In homes and offices, IoT systems enable remote and scheduled operation of heating, ventilation and air conditioning (HVAC) systems, lighting control, control of kitchen and other home appliances, etc. Available solutions in the smart home domain mainly enable controlling systems and appliances remotely, e.g., by using a smartphone, or manually setting the times in which systems and appliances should operate. In this paper we propose a system for indoor lighting control which sets the colors and brightness of the lamps based on the context: time of the day, current lighting conditions in the room, and having users in the focus - their lighting preferences in the room. Feed-forward neural networks are used for learning about the most pleasing settings. The major advantage of this system is its user- centricity, i.e., taking into account users' color and brightness preferences. The system is evaluated on twenty-two (22) users in a laboratory environment and demonstrates general user score rate of 68.18% as "great" and 31.82% as "good".
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-1986 - Pametne usluge usmjerene čovjeku u interoperabilnim i decentraliziranim okolinama Interneta stvari (IoT4us) (Podnar Žarko, Ivana, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb