scholarly journals A Kriging algorithm for location fingerprinting based on received signal strength

2015 ◽  
Author(s):  
Chao Liu ◽  
Aroland Kiring ◽  
Naveed Salman ◽  
Lyudmila Mihaylova ◽  
Inaki Esnaola
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Location Fingerprinting

scholarly journals Dealing with Insufficient Location Fingerprints in Wi-Fi Based Indoor Location Fingerprinting

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Kai Dong ◽  
Zhen Ling ◽  
Xiangyu Xia ◽  
Haibo Ye ◽  
Wenjia Wu ◽  
...  
Keyword(s):  
Value Added ◽  
Likelihood Estimation ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Stochastic Gradient Descent ◽  
Indoor Environments ◽  
Localization Accuracy ◽  
Indoor Location ◽  
Location Fingerprinting ◽  
Gradient Descent Algorithm

The development of the Internet of Things has accelerated research in the indoor location fingerprinting technique, which provides value-added localization services for existing WLAN infrastructures without the need for any specialized hardware. The deployment of a fingerprinting based localization system requires an extremely large amount of measurements on received signal strength information to generate a location fingerprint database. Nonetheless, this requirement can rarely be satisfied in most indoor environments. In this paper, we target one but common situation when the collected measurements on received signal strength information are insufficient, and show limitations of existing location fingerprinting methods in dealing with inadequate location fingerprints. We also introduce a novel method to reduce noise in measuring the received signal strength based on the maximum likelihood estimation, and compute locations from inadequate location fingerprints by using the stochastic gradient descent algorithm. Our experiment results show that our proposed method can achieve better localization performance even when only a small quantity of RSS measurements is available. Especially when the number of observations at each location is small, our proposed method has evident superiority in localization accuracy.

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

2019 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Riski Fitriani
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Received Signal Strength Indicator ◽  
Landslide Early Warning ◽  
Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.

2.4 GHz RF Received Signal Strength Based Node Separation in WSN Monitoring Infrastructure for Millet and Rice Vegetation

2021 ◽  
pp. 1-1
Author(s):  
Pankaj Pal ◽  
Rashmi Priya Sharma ◽  
Sachin Tripathi ◽  
Chiranjeev Kumar ◽  
Dharavath Ramesh
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Strength Based
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