scholarly journals Received signal strength indicator-based decentralised control for robust long-range aerial networking using directional antennas

2017 ◽  
Vol 11 (11) ◽  
pp. 1838-1847 ◽  
Author(s):  
Jing Yan ◽  
Yan Wan ◽  
Shengli Fu ◽  
Junfei Xie ◽  
Songwei Li ◽  
...  
Keyword(s):  
Long Range ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Directional Antennas ◽  
Received Signal Strength Indicator ◽  
Decentralised Control

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.

A Framework for RF-Visual SLAM for Cooperative Multi-Agent System

2015 ◽  
pp. 697-727
Author(s):  
Herdawatie Abdul Kadir ◽  
Mohd Rizal Arshad
Keyword(s):  
Mobile Agent ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Local Information ◽  
Reliable Data ◽  
Working Environment ◽  
Visual Slam ◽  
Received Signal Strength Indicator ◽  
Localization And Mapping ◽  
Multi Agent

This chapter provides a framework for radio frequency visual simultaneous localization and mapping problems for a team of agents consisting of three blimps and beacons. In a cooperative system, each agent must establish reliable data sharing during a mission. Under these conditions, a framework was proposed which allows each agent to share the local information using peer-to-peer networking schemes. The RF-vSLAM algorithm seeks to acquire a map during navigation, simultaneously localizing itself using the map and received signal strength indicator information to predict the distance between agents. In this chapter, the authors address the problem of detection features using SIFT algorithms. The authors have considered the sea surface as the working environment. In this research, the framework consisted of two types of agents, where beacon representing the static agent and blimp representing the homogeneous mobile agent. The communication exchange between these two types of agents is an environmentally friendly monitoring system that preserves natural value of the selected area.

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