Standaard Boekhandel gebruikt cookies en gelijkaardige technologieën om de website goed te laten werken en je een betere surfervaring te bezorgen.
Hieronder kan je kiezen welke cookies je wilt inschakelen:
Technische en functionele cookies
Deze cookies zijn essentieel om de website goed te laten functioneren, en laten je toe om bijvoorbeeld in te loggen. Je kan deze cookies niet uitschakelen.
Analytische cookies
Deze cookies verzamelen anonieme informatie over het gebruik van onze website. Op die manier kunnen we de website beter afstemmen op de behoeften van de gebruikers.
Marketingcookies
Deze cookies delen je gedrag op onze website met externe partijen, zodat je op externe platformen relevantere advertenties van Standaard Boekhandel te zien krijgt.
Je kan maximaal 250 producten tegelijk aan je winkelmandje toevoegen. Verwijdere enkele producten uit je winkelmandje, of splits je bestelling op in meerdere bestellingen.
Various applications of Wireless Sensor Networks (WSNs) require accurate localization of sensor nodes. The quantity and locations of anchor nodes, which serve as reference points for distance estimates, as well as the localization process itself, affect the localization accuracy. Furthermore, because numerous communications are sent between nodes for localization, energy consumption must be considered. This work presents an energy-aware and accurate localization method. It is based on a combined anchor deployment and energy-aware localization. The proper number and distribution of anchors have been investigated to achieve full network coverage and connectivity based on an efficient and heterogeneous hexagonal deployment. Later, energy-aware localization is performed in three stages: Initialization, signal acquisition, and anchor selection. The initialization step allows the network to be adaptable to sudden changes by establishing anchor connectivity and creating the neighbors' list. Meanwhile, the Received Signal Strength Indicator (RSSI) is used for distance measurements between nodes, with the implementation of a Kalman filter to reduce signal attenuation and noise. Later, the anchor selection is done using fuzzy logic with inference parameters: RSSI, node density, and residual energy. This step ensures that only operable anchors engage in localization, while anchors with inadequate energy sources remain intact to ensure their future availability.