You will get a real-time tracking web browser application

Lampros M.Status: Offline
Lampros M. Lampros M.
4.9
Top Rated

Let a pro handle the details

Buy Web Application Programming services from Lampros, priced and ready to go.
Lampros M.Status: Offline
Lampros M. Lampros M.
4.9
Top Rated

Let a pro handle the details

Buy Web Application Programming services from Lampros, priced and ready to go.

Project details

The implemented shiny web browser application can be used for real-time tracking. The application could be utilized in the following example use cases,

 • vehicles
 • flights
 • wildlife animals

The current status of the application makes use of an API (Application Programming Interface) to display registration numbers in real-time (every 15 seconds) and can be adjusted depending on the requirements.
The price of this Project is negotiable.

What's included $450

These options are included with the project scope.

$450
  • Delivery Time 2 days
  • Number of Revisions 0
    • Content Upload
4.9
68 reviews
93% Complete
6% Complete
1% Complete
1% Complete
(0)
1% Complete
(0)

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Lampros M.Status: Offline

About Lampros

Lampros M.Status: Offline
R, Python, Remote Sensing, Deep Learning and Machine Learning Analyst
100% Job Success
4.9  (68 reviews)
Paramythia, Greece - 5:26 pm local time
For more than a decade, I utilize the R and Python programming languages to process, visualize and extract information from data and for almost five years for Geospatial analysis. I'm the author / maintainer of R packages (I've submitted more than 10 to CRAN). You can view my Github profile at the following weblink: github.com/mlampros

I work with R and Rstudio on a daily basis. I can work with machine learning algorithms based on almost all CRAN, Github or Gitlab repositories. I can utilize visualization R packages such as ggplot2, plotly, tmap, leaflet, mapview. I can create shiny applications (shiny.rstudio.com/gallery/) and report my results in .pdf, word, .html or any other available format using Rmarkdown.

Moreover, I'm capable of using the hybrid 'Rcpp' and 'RcppArmadillo' R packages to improve the efficiency of R code and the Keras and Pytorch deep learning libraries for regression, classification, object detection or image segmentation (with or without pre-trained models).

Steps for completing your project

After purchasing the project, send requirements so Lampros can start the project.

Delivery time starts when Lampros receives requirements from you.

Lampros works on your project following the steps below.

Revisions may occur after the delivery date.

Implementation of the real-time application

Implementation of the real-time application depending on the client's requirements

deployment of the web browser application

The application will be deployed to shinyapps.io so that it can be accessed by the client

Review the work, release payment, and leave feedback to Lampros.