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https://github.com/abdullah-alrefaey/indoor-localization


https://github.com/abdullah-alrefaey/indoor-localization

esp8266 localization meteorjs

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README

          

Person Tracking via Wireless


Submitted to: Dr. Tamer Basha


2020 - 2021


Group ID: 03

| Name | Section | B.N Number | E-mail |
|-------------------------|---------|--------------|-------------------------------|
| Ahmed Salah Eldin | 1 | 5 | salo7a98x@gmail.com |
| Ahmad Abdelmageed Ahmad | 1 | 8 | ahmedmageed19@gmail.com |
| Ahmad Mahdy Mohammed | 1 | 9 | ahmadmahdy3098@gmail.com |
| Abdullah Mohammed Sabry | 2 | 7 | abdullah.m.alrefaey@gmail.com |

## Packages Installations

npm install --save firebase

## The Data

Localziation system built using machine learning classifiers, data is collected at Cairo University Faculty of Engineering Biomedical Engineering Department. The Data is a collection of WiFi\`s RSSI\`s (dbm) of Wifi Networks available in the department. RSSI measurements represent the relative quality of a received signal on a device. RSSI indicates the power level being received after any possible loss at the antenna and cable level. The higher the RSSI value, the stronger the signal. When measured in negative numbers, the number that is closer to zero usually means better signal. As an example -50 is a pretty good signal, -75 - is fairly reasonable, and -100 is no signal at all. Identifying a patient\`s location in a hospital is useful for many reasons one of which is to identify points of conjestions and try to rearrange the hospital survices, also used to identify how many patients are in the hospital.

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